From 7e49274e04cfc4b3ffec3724cad17d8862da3f2a Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Wed, 16 Nov 2022 16:05:13 +0800 Subject: [PATCH 01/12] update new aikit code --- .../scripts/mecharm_topics.py | 2 + .../ai_mecharm_270/launch/vision_wio.launch | 8 +- .../scripts/advance_detect_obj_color.py | 493 +++++++++++++ .../scripts/advance_detect_obj_img_folder.py | 644 +++++++++++++++++ mycobot_ai/ai_mycobot_280/res/blue/goal9.jpeg | Bin 0 -> 3533 bytes .../ai_mycobot_280/res/gray/goal10.jpeg | Bin 0 -> 3416 bytes .../ai_mycobot_280/res/green/goal12.jpeg | Bin 0 -> 3572 bytes mycobot_ai/ai_mycobot_280/res/red/goal8.jpeg | Bin 0 -> 4012 bytes mycobot_ai/ai_mycobot_280/res/red/goal9.jpeg | Bin 0 -> 3616 bytes mycobot_ai/ai_mycobot_280/res/takephoto.jpeg | Bin 64540 -> 42627 bytes .../scripts/advance_detect_obj_color.py | 479 +++++++++++++ .../scripts/advance_detect_obj_img_folder.py | 660 ++++++++++++++++++ mycobot_ai/ai_mycobot_280/scripts/test.py | 17 +- .../launch/vision_wio.launch | 6 +- .../ai_mypalletizer_260/res/blue/goal9.jpeg | Bin 0 -> 2808 bytes .../ai_mypalletizer_260/res/gray/goal9.jpeg | Bin 0 -> 3155 bytes .../ai_mypalletizer_260/res/green/goal12.jpeg | Bin 0 -> 4376 bytes .../ai_mypalletizer_260/res/green/goal14.jpeg | Bin 0 -> 2451 bytes .../ai_mypalletizer_260/res/red/goal8.jpeg | Bin 0 -> 2991 bytes .../ai_mypalletizer_260/res/takephoto.jpeg | Bin 46764 -> 48769 bytes .../scripts/advance_detect_obj_color.py | 550 +++++++++++++++ .../scripts/advance_detect_obj_img_folder.py | 628 +++++++++++++++++ .../ai_mypalletizer_260/scripts/test.py | 31 +- .../mypalletizer_260/config/mypal_260.rviz | 247 +------ .../launch/communication_topic.launch | 2 +- .../scripts/mypal_topics.py | 16 +- 26 files changed, 3548 insertions(+), 235 deletions(-) create mode 100644 mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py create mode 100644 mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py create mode 100644 mycobot_ai/ai_mycobot_280/res/blue/goal9.jpeg create mode 100644 mycobot_ai/ai_mycobot_280/res/gray/goal10.jpeg create mode 100644 mycobot_ai/ai_mycobot_280/res/green/goal12.jpeg create mode 100644 mycobot_ai/ai_mycobot_280/res/red/goal8.jpeg create mode 100644 mycobot_ai/ai_mycobot_280/res/red/goal9.jpeg create mode 100644 mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py create mode 100644 mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py create mode 100644 mycobot_ai/ai_mypalletizer_260/res/blue/goal9.jpeg create mode 100644 mycobot_ai/ai_mypalletizer_260/res/gray/goal9.jpeg create mode 100644 mycobot_ai/ai_mypalletizer_260/res/green/goal12.jpeg create mode 100644 mycobot_ai/ai_mypalletizer_260/res/green/goal14.jpeg create mode 100644 mycobot_ai/ai_mypalletizer_260/res/red/goal8.jpeg create mode 100644 mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py create mode 100644 mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py diff --git a/mecharm/mecharm_communication/scripts/mecharm_topics.py b/mecharm/mecharm_communication/scripts/mecharm_topics.py index 02c3934..5039b0d 100755 --- a/mecharm/mecharm_communication/scripts/mecharm_topics.py +++ b/mecharm/mecharm_communication/scripts/mecharm_topics.py @@ -71,6 +71,8 @@ class MycobotTopics(object): rospy.init_node("mycobot_topics") rospy.loginfo("start ...") port = rospy.get_param("~port", os.popen("ls /dev/ttyUSB*").readline()[:-1]) + if not port: + port = rospy.get_param("~port", os.popen("ls /dev/ttyACM*").readline()[:-1]) baud = rospy.get_param("~baud", 115200) rospy.loginfo("%s,%s" % (port, baud)) self.mc = MyCobot(port, baud) diff --git a/mycobot_ai/ai_mecharm_270/launch/vision_wio.launch b/mycobot_ai/ai_mecharm_270/launch/vision_wio.launch index 51eb78b..6b6f132 100644 --- a/mycobot_ai/ai_mecharm_270/launch/vision_wio.launch +++ b/mycobot_ai/ai_mecharm_270/launch/vision_wio.launch @@ -2,8 +2,8 @@ - - + + @@ -14,13 +14,13 @@ - + - + diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py new file mode 100644 index 0000000..ec46a57 --- /dev/null +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py @@ -0,0 +1,493 @@ +#!/usr/bin/env python2 +# -*- coding:utf-8 -*- +import cv2 +import numpy as np +import time +import os,sys +import rospy +from visualization_msgs.msg import Marker +from pymycobot.mycobot import MyCobot +from moving_utils import Movement + + +IS_CV_4 = cv2.__version__[0] == '4' +__version__ = "1.0" +# Adaptive seeed + + +class Object_detect(Movement): + + def __init__(self, camera_x = 140, camera_y = 5): # m5 + # def __init__(self, camera_x = 140, camera_y = -5): # pi + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + + # declare 270 + self.mc = None + + # 移动角度 + self.move_angles = [ + [0, 0, 0, 0, 90, 0], # point to grab + [-33.31, 2.02, -10.72, -0.08, 95, -54.84], # init the point + ] + + # 移动坐标 + self.move_coords = [ + [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket + [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket + [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket + [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + ] + + # which robot: USB* is m5; ACM* is wio; AMA* is raspi + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + self.raspi = False + if "dev" in self.robot_m5: + self.Pin = [2, 5] + # self.Pin = [5] + elif "dev" in self.robot_wio: + # self.Pin = [20, 21] + self.Pin = [2, 5] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + # choose place to set cube + self.color = 0 + # parameters to calculate camera clipping parameters + self.x1 = self.x2 = self.y1 = self.y2 = 0 + # set cache of real coord + self.cache_x = self.cache_y = 0 + # set color HSV + self.HSV = { + "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], + "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], + "green": [np.array([35, 43, 46]), np.array([77, 255, 255])], + "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], + "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], + } + # use to calculate coord between cube and 270 + self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 + # The coordinates of the grab center point relative to the 270 + self.camera_x, self.camera_y = camera_x, camera_y + # The coordinates of the cube relative to the 270 + self.c_x, self.c_y = 0, 0 + # The ratio of pixels to actual values + self.ratio = 0 + # Get ArUco marker dict that can be detected. + self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) + # Get ArUco marker params. + self.aruco_params = cv2.aruco.DetectorParameters_create() + + # init a node and a publisher + rospy.init_node("marker", anonymous=True) + self.pub = rospy.Publisher('/cube', Marker, queue_size=1) + # init a Marker + self.marker = Marker() + self.marker.header.frame_id = "/joint1" + self.marker.ns = "cube" + self.marker.type = self.marker.CUBE + self.marker.action = self.marker.ADD + self.marker.scale.x = 0.04 + self.marker.scale.y = 0.04 + self.marker.scale.z = 0.04 + self.marker.color.a = 1.0 + self.marker.color.g = 1.0 + self.marker.color.r = 1.0 + + # marker position initial + self.marker.pose.position.x = 0 + self.marker.pose.position.y = 0 + self.marker.pose.position.z = 0.03 + self.marker.pose.orientation.x = 0 + self.marker.pose.orientation.y = 0 + self.marker.pose.orientation.z = 0 + self.marker.pose.orientation.w = 1.0 + + # publish marker + def pub_marker(self, x, y, z=0.03): + self.marker.header.stamp = rospy.Time.now() + self.marker.pose.position.x = x + self.marker.pose.position.y = y + self.marker.pose.position.z = z + self.marker.color.g = self.color + self.pub.publish(self.marker) + + # pump_control pi + def gpio_status(self, flag): + if flag: + # self.GPIO.output(20, 0) + self.GPIO.output(21, 0) + else: + # self.GPIO.output(20, 1) + self.GPIO.output(21, 1) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + # self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + # self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + # send Angle to move 270 + print(color) + self.mc.send_angles(self.move_angles[0], 30) + time.sleep(4) + + # send coordinates to move 270 + self.mc.send_coords([x, y, 140, 179.12, -0.18, 179.46], 30, 0) + time.sleep(3) + self.pub_marker(x/1000.0, y/1000.0, 140/1000.0) + + + self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 + # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi + time.sleep(3) + self.pub_marker(x/1000.0, y/1000.0, 90/1000.0) + + + # open pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + tmp = [] + while True: + if not tmp: + tmp = self.mc.get_angles() + else: + break + time.sleep(0.5) + + # print(tmp) + self.mc.send_angles([tmp[0], 17.22, -32.51, tmp[3], 97, tmp[5]],30) + time.sleep(3) + + + + self.mc.send_coords(self.move_coords[color], 30, 1) + self.pub_marker(self.move_coords[color][0]/1000.0, + self.move_coords[color][1]/1000.0, + self.move_coords[color][2]/1000.0) + time.sleep(3) + + # close pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + + if color == 1: + self.pub_marker( + self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02) + elif color == 0: + self.pub_marker( + self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0) + + self.mc.send_angles(self.move_angles[1], 30) + time.sleep(1.5) + + # decide whether grab cube + def decide_move(self, x, y, color): + print(x, y, self.cache_x, self.cache_y) + # detect the cube status move or run + if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init 270 + def run(self): + if "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_wio: + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-33.31, 2.02, -10.72, -0.08, 95, -54.84], 30) + time.sleep(3) + + # draw aruco + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText(img, "({},{})".format(x, y), (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params + ) + + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and 270 + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0/ratio + + # calculate the coords between cube and 270 + def get_position(self, x, y): + return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + frame = frame[int(self.y2*0.78):int(self.y1*1.1), + int(self.x1*0.86):int(self.x2*1.08)] + return frame + + # detect cube color + def color_detect(self, img): + # set the arrangement of color'HSV + x = y = 0 + for mycolor, item in self.HSV.items(): + # print("mycolor:",mycolor) + redLower = np.array(item[0]) + redUpper = np.array(item[1]) + + # transfrom the img to model of gray + hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) + # print("hsv",hsv) + + # wipe off all color expect color in range + mask = cv2.inRange(hsv, item[0], item[1]) + + # a etching operation on a picture to remove edge roughness + erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2) + + # the image for expansion operation, its role is to deepen the color depth in the picture + dilation = cv2.dilate(erosion, np.ones( + (1, 1), np.uint8), iterations=2) + + # adds pixels to the image + target = cv2.bitwise_and(img, img, mask=dilation) + + # the filtered image is transformed into a binary image and placed in binary + ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY) + + # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected + contours, hierarchy = cv2.findContours( + dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + + if len(contours) > 0: + # do something about misidentification + boxes = [ + box + for box in [cv2.boundingRect(c) for c in contours] + if min(img.shape[0], img.shape[1]) / 10 + < min(box[2], box[3]) + < min(img.shape[0], img.shape[1]) / 1 + ] + if boxes: + for box in boxes: + x, y, w, h = box + # find the largest object that fits the requirements + c = max(contours, key=cv2.contourArea) + # get the lower left and upper right points of the positioning object + x, y, w, h = cv2.boundingRect(c) + # locate the target by drawing rectangle + cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2) + # calculate the rectangle center + x, y = (x*2+w)/2, (y*2+h)/2 + # calculate the real coordinates of 270 relative to the target + + if mycolor == "red": + self.color = 0 + elif mycolor == "green": + self.color = 1 + elif mycolor == "cyan": + self.color = 2 + else: + self.color = 3 + + if abs(x) + abs(y) > 0: + return x, y + else: + return None + +if __name__ == "__main__": + + # open the camera + cap_num = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + if not cap.isOpened(): + cap.open() + # init a class of Object_detect + detect = Object_detect() + # init 270 + detect.run() + + _init_ = 20 + init_num = 0 + nparams = 0 + num = 0 + real_sx = real_sy = 0 + while cv2.waitKey(1) < 0: + # read camera + _, frame = cap.read() + # deal img + frame = detect.transform_frame(frame) + if _init_ > 0: + _init_ -= 1 + continue + + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1)/20.0, + (detect.sum_y1)/20.0, + (detect.sum_x2)/20.0, + (detect.sum_y2)/20.0, + ) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and 270 + if nparams < 10: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and 270 + detect.set_params( + (detect.sum_x1+detect.sum_x2)/20.0, + (detect.sum_y1+detect.sum_y2)/20.0, + abs(detect.sum_x1-detect.sum_x2)/10.0 + + abs(detect.sum_y1-detect.sum_y2)/10.0 + ) + print("ok") + continue + + # get detect result + detect_result = detect.color_detect(frame) + if detect_result is None: + cv2.imshow("figure", frame) + continue + else: + x, y = detect_result + # calculate real coord between cube and 270 + real_x, real_y = detect.get_position(x, y) + if num == 20: + detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0) + detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color) + num = real_sx = real_sy = 0 + + else: + num += 1 + real_sy += real_y + real_sx += real_x + + cv2.imshow("figure", frame) + + # close the window + if cv2.waitKey(1) & 0xFF == ord('q'): + cap.release() + cv2.destroyAllWindows() + sys.exit() \ No newline at end of file diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py new file mode 100644 index 0000000..f2bc2c1 --- /dev/null +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py @@ -0,0 +1,644 @@ +#!/usr/bin/env python2 +# encoding:utf-8 +from multiprocessing import Process, Pipe +import cv2 +import numpy as np +import time +import os,sys +import rospy +from visualization_msgs.msg import Marker +from moving_utils import Movement +from pymycobot.mycobot import MyCobot + +IS_CV_4 = cv2.__version__[0] == '4' +__version__ = "1.0" # Adaptive seeed + + +class Object_detect(Movement): + + def __init__(self, camera_x = 145, camera_y = -5): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + + # declare 270 + self.mc = None + # 移动角度 + self.move_angles = [ + [0, 0, 0, 0, 90, 0], # point to grab + [-33.31, 2.02, -10.72, -0.08, 95, -54.84], # init the point + ] + + # 移动坐标 + self.move_coords = [ + [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket + [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket + [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket + [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + ] + + # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed + self.raspi = False + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + if "dev" in self.robot_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + # self.Pin = [20, 21] + self.Pin = [2, 5] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + + # choose place to set cube + self.color = 0 + # parameters to calculate camera clipping parameters + self.x1 = self.x2 = self.y1 = self.y2 = 0 + # set cache of real coord + self.cache_x = self.cache_y = 0 + + # use to calculate coord between cube and mycobot + self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 + # The coordinates of the grab center point relative to the mycobot + self.camera_x, self.camera_y = camera_x, camera_y + # The coordinates of the cube relative to the mycobot + self.c_x, self.c_y = 0, 0 + # The ratio of pixels to actual values + self.ratio = 0 + # Get ArUco marker dict that can be detected. + self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) + # Get ArUco marker params. + self.aruco_params = cv2.aruco.DetectorParameters_create() + + # init a node and a publisher + rospy.init_node("marker", anonymous=True) + self.pub = rospy.Publisher('/cube', Marker, queue_size=1) + # init a Marker + self.marker = Marker() + self.marker.header.frame_id = "/joint1" + self.marker.ns = "cube" + self.marker.type = self.marker.CUBE + self.marker.action = self.marker.ADD + self.marker.scale.x = 0.04 + self.marker.scale.y = 0.04 + self.marker.scale.z = 0.04 + self.marker.color.a = 1.0 + self.marker.color.g = 1.0 + self.marker.color.r = 1.0 + + # marker position initial + self.marker.pose.position.x = 0 + self.marker.pose.position.y = 0 + self.marker.pose.position.z = 0.03 + self.marker.pose.orientation.x = 0 + self.marker.pose.orientation.y = 0 + self.marker.pose.orientation.z = 0 + self.marker.pose.orientation.w = 1.0 + + self.cache_x = self.cache_y = 0 + + # publish marker + def pub_marker(self, x, y, z=0.03): + self.marker.header.stamp = rospy.Time.now() + self.marker.pose.position.x = x + self.marker.pose.position.y = y + self.marker.pose.position.z = z + self.marker.color.g = self.color + self.pub.publish(self.marker) + + # pump_control pi + def gpio_status(self, flag): + if flag: + # self.GPIO.output(20, 0) + self.GPIO.output(21, 0) + else: + # self.GPIO.output(20, 1) + self.GPIO.output(21, 1) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + # self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + # self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + # send Angle to move 270 + self.mc.send_angles(self.move_angles[0], 30) + time.sleep(7) + + print("x %s ,y %s" % (x,y)) + # send coordinates to move 270 根据不同底板机械臂，调整吸泵高度 + self.mc.send_coords([x, y, 140, 179.12, -0.18, 179.46], 30, 0) + time.sleep(7) + print("ntm") + + self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 + # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi + # self.mc.send_coords([x, y, 92, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 + time.sleep(6) + + # open pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + tmp = [] + while True: + if not tmp: + tmp = self.mc.get_angles() + else: + break + time.sleep(0.5) + + # print(tmp) + self.mc.send_angles([tmp[0], 17.22, -32.51, tmp[3], 97, tmp[5]],30) + time.sleep(6) + + + self.mc.send_coords(self.move_coords[color], 30, 1) + self.pub_marker(self.move_coords[color][0] / 1000.0, + self.move_coords[color][1] / 1000.0, + self.move_coords[color][2] / 1000.0) + time.sleep(6) + + # close pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + + self.mc.send_angles(self.move_angles[1], 30) + time.sleep(6) + + # decide whether grab cube + def decide_move(self, x, y, color): + print(x, y, self.cache_x, self.cache_y) + # detect the cube status move or run + if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init 270 + def run(self): + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-33.31, 2.02, -10.72, -0.08, 95, -54.84], 30) + time.sleep(3) + + # draw aruco + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText( + img, + "({},{})".format(x, y), + (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, + 1, + (243, 0, 0), + 2, + ) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params) + + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int( + (point_11[0] + point_21[0] + point_31[0] + point_41[0]) / + 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) + / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int( + (point_1[0] + point_2[0] + point_3[0] + point_4[0]) / + 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / + 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and mycobot + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0 / ratio + + # calculate the coords between cube and mycobot + def get_position(self, x, y): + return ((y - self.c_y) * self.ratio + + self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15), + int(self.x1 * 0.7):int(self.x2 * 1.15)] + return frame + + # according the class_id to get object name + def id_class_name(self, class_id): + for key, value in self.labels.items(): + if class_id == int(key): + return value + + # detect object + def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection): + i = 0 + MIN_MATCH_COUNT = 5 + # sift = cv2.xfeatures2d.SIFT_create() + + # find the keypoints and descriptors with SIFT + # kp = [] + # des = [] + kp = kp_list + des = desc_list + + # for i in goal: + # kp0, des0 = sift.detectAndCompute(i, None) + # kp.append(kp0) + # des.append(des0) + + # kp1, des1 = sift.detectAndCompute(goal, None) + # kp2, des2 = sift.detectAndCompute(img, None) + kp2, des2 = kp_img, desc_img + + # FLANN parameters + FLANN_INDEX_KDTREE = 0 + index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) + search_params = dict(checks=50) # or pass empty dictionary + flann = cv2.FlannBasedMatcher(index_params, search_params) + + x, y = 0, 0 + try: + for i in range(len(des)): + matches = flann.knnMatch(des[i], des2, k=2) + # store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。 + good = [] + for m, n in matches: + if m.distance < 0.7 * n.distance: + good.append(m) + + # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时 + if len(good) > MIN_MATCH_COUNT: + + # extract corresponding point pairs from matching 从匹配中提取出对应点对 + # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引 + src_pts = np.float32([kp[i][m.queryIdx].pt + for m in good]).reshape(-1, 1, 2) + dst_pts = np.float32([kp2[m.trainIdx].pt + for m in good]).reshape(-1, 1, 2) + + # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵 + M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, + 5.0) + matchesMask = mask.ravel().tolist() + # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置 + h, w, d = goal[i].shape + pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1], + [w - 1, 0]]).reshape(-1, 1, 2) + dst = cv2.perspectiveTransform(pts, M) + coord = (dst[0][0] + dst[1][0] + dst[2][0] + + dst[3][0]) / 4.0 + connection.send((DRAW_COORDS, coord)) + # cv2.putText(img, "{}".format(coord), (50, 60), + # fontFace=None, fontScale=1, + # color=(0, 255, 0), lineType=1) + print(format(dst[0][0][0])) + x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] + + dst[3][0][0]) / 4.0 + y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] + + dst[3][0][1]) / 4.0 + + # bound box 绘制边框 + # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + connection.send((DRAW_RECT, dst)) + # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA) + except Exception as e: + pass + + if x + y > 0: + return x, y + else: + return None + +# The path to save the image folder +def parse_folder(folder): + restore = [] + # path = '' + path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mecharm_270/' + folder + path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mecharm_270/' + folder + + if os.path.exists(path1): + path = path1 + elif os.path.exists(path2): + path = path2 + + # print("path:",path) + for i, j, k in os.walk(path): + for l in k: + restore.append(cv2.imread(folder + '/{}'.format(l))) + return restore + +def compute_keypoints_and_descriptors(sift, images_lists): + kp_list = [] + desc_list = [] + for images in images_lists: + kp_tmp = [] + desc_tmp = [] + for img in images: + kp, desc = sift.detectAndCompute(img, None) + kp_tmp.append(kp) + desc_tmp.append(desc) + kp_list.append(kp_tmp) + desc_list.append(desc_tmp) + + return kp_list, desc_list + +GET_FRAME = 1 +STOP_PROCESSING = 2 +DRAW_COORDS = 3 +DRAW_RECT = 4 +CLEAR_DRAW = 5 +CROP_FRAME = 6 + +def get_frame(connection): + connection.send(GET_FRAME) + frame = connection.recv() + return frame + +def process_transform_frame(frame, x1, y1, x2, y2): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) +# if x1 != x2: + # the cutting ratio here is adjusted according to the actual situation +# frame = frame[int(y2 * 0.2):int(y1 * 1.15), +# int(x1 * 0.7):int(x2 * 1.15)] + return frame + +def process_display_frame(connection): + cap_num = 0 + coord = None + dst = None + x1 = 0 + y1 = 0 + x2 = 0 + y2 = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + if not cap.isOpened(): + cap.open() + while cv2.waitKey(1) < 0: + _, frame = cap.read() + frame = process_transform_frame(frame, x1, y1, x2, y2) + if connection.poll(): + request = connection.recv() + if request == GET_FRAME: + connection.send(frame) + elif request == CLEAR_DRAW: + coord = None + dst = None + elif type(request) is tuple: + if request[0] == DRAW_COORDS: + coord = request[1] + elif request[0] == DRAW_RECT: + dst = request[1] + elif request[0] == CROP_FRAME: + x1 = request[1] + y1 = request[2] + x2 = request[3] + y2 = request[4] + + if not coord is None: + cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None, + fontScale=1, color=(0, 255, 0), lineType=1) + if not dst is None: + frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + cv2.imshow("figure", frame) + time.sleep(0.04) + connection.send(STOP_PROCESSING) + +def run(): + parent_conn, child_conn = Pipe() + child = Process(target = process_display_frame, args=(child_conn,)) + child.start() + + res_queue = [[], [], [], []] + res_queue[0] = parse_folder('res/red') + res_queue[1] = parse_folder('res/green') + res_queue[2] = parse_folder('res/blue') + res_queue[3] = parse_folder('res/gray') + + + sift = cv2.xfeatures2d.SIFT_create() + kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue) + + # init a class of Object_detect + detect = Object_detect() + + # init mycobot + detect.run() + + # _init_ = 20 # + init_num = 0 + nparams = 0 + # num = 0 + # real_sx = real_sy = 0 + while True: + start_time = time.time() + if parent_conn.poll(): + data = parent_conn.recv() + if data == STOP_PROCESSING: + break + # read camera + frame = get_frame(parent_conn) + # deal img + #frame = detect.transform_frame(frame) + + # if _init_ > 0: + # _init_ -= 1 + # continue + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0, + ) + parent_conn.send((CROP_FRAME, + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0)) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and mycobot + if nparams < 10: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + print ("ok") + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and mycobot + detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0, + (detect.sum_y1 + detect.sum_y2) / 20.0, + abs(detect.sum_x1 - detect.sum_x2) / 10.0 + + abs(detect.sum_y1 - detect.sum_y2) / 10.0) + print("ok") + continue + + # get detect result + kp_img, desc_img = sift.detectAndCompute(frame, None) + frame = get_frame(parent_conn) + for i, v in enumerate(res_queue): + # HACK: to update frame every time + detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn) + if detect_result: + x, y = detect_result + # calculate real coord between cube and mycobot + real_x, real_y = detect.get_position(x, y) + detect.color = i + detect.pub_marker(real_x / 1000.0, real_y / 1000.0) + detect.decide_move(real_x, real_y, detect.color) + # if num == 5: + # detect.color = i + # detect.pub_marker(real_sx / 5.0 / 1000.0, + # real_sy / 5.0 / 1000.0) + # detect.decide_move(real_sx / 5.0, real_sy / 5.0, + # detect.color) + # num = real_sx = real_sy = 0 + # else: + # num += 1 + # real_sy += real_y + # real_sx += real_x + parent_conn.send(CLEAR_DRAW) + + # cv2.imshow("figure", frame) + time.sleep(0.05) + end_time = time.time() + print("loop_time = ", end_time - start_time) + + # close 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zAA0FE$V*>4d1Q0^Lz>3Ev*UVlH{D}kTG7|n5d_-0QiaLvFKx9|_*Cav(_$4RSc_Y=b~I7wkR zA;&;R@h?zEy?lmmCwCNkICyfp zOQfy42(2yktDzOT!zaunVm9SJgtuxd=PA>! 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init mycobot + def run(self): + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20) + time.sleep(3) + + # draw aruco + + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText(img, "({},{})".format(x, y), (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params + ) + + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and mycobot + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0/ratio + + # calculate the coords between cube and mycobot + def get_position(self, x, y): + return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + frame = frame[int(self.y2*0.78):int(self.y1*1.1), + int(self.x1*0.86):int(self.x2*1.08)] + return frame + + # detect cube color + def color_detect(self, img): + # set the arrangement of color'HSV + x = y = 0 + for mycolor, item in self.HSV.items(): + redLower = np.array(item[0]) + redUpper = np.array(item[1]) + # transfrom the img to model of gray + hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) + # wipe off all color expect color in range + mask = cv2.inRange(hsv, item[0], item[1]) + # a etching operation on a picture to remove edge roughness + erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2) + # the image for expansion operation, its role is to deepen the color depth in the picture + dilation = cv2.dilate(erosion, np.ones( + (1, 1), np.uint8), iterations=2) + + + # adds pixels to the image + target = cv2.bitwise_and(img, img, mask=dilation) + # the filtered image is transformed into a binary image and placed in binary + ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY) + # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected + contours, hierarchy = cv2.findContours( + dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + + if len(contours) > 0: + # do something about misidentification + boxes = [ + box + for box in [cv2.boundingRect(c) for c in contours] + if min(img.shape[0], img.shape[1]) / 10 + < min(box[2], box[3]) + < min(img.shape[0], img.shape[1]) / 1 + ] + if boxes: + for box in boxes: + x, y, w, h = box + # find the largest object that fits the requirements + c = max(contours, key=cv2.contourArea) + # get the lower left and upper right points of the positioning object + x, y, w, h = cv2.boundingRect(c) + # locate the target by drawing rectangle + cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2) + # calculate the rectangle center + x, y = (x*2+w)/2, (y*2+h)/2 + # calculate the real coordinates of mycobot relative to the target + if mycolor == "red": + self.color = 0 + + elif mycolor == "green": + self.color = 1 + + elif mycolor == "cyan": + self.color = 2 + + else: + self.color = 3 + + + if abs(x) + abs(y) > 0: + return x, y + else: + return None + + +if __name__ == "__main__": + # open the camera + cap_num = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + + if not cap.isOpened(): + cap.open() + # init a class of Object_detect + detect = Object_detect() + # init mycobot + detect.run() + + _init_ = 20 # + init_num = 0 + nparams = 0 + num = 0 + real_sx = real_sy = 0 + while cv2.waitKey(1) < 0: + # read camera + _, frame = cap.read() + # deal img + frame = detect.transform_frame(frame) + + if _init_ > 0: + _init_ -= 1 + continue + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1)/20.0, + (detect.sum_y1)/20.0, + (detect.sum_x2)/20.0, + (detect.sum_y2)/20.0, + ) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and mycobot + if nparams < 10: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and mycobot + detect.set_params( + (detect.sum_x1+detect.sum_x2)/20.0, + (detect.sum_y1+detect.sum_y2)/20.0, + abs(detect.sum_x1-detect.sum_x2)/10.0 + + abs(detect.sum_y1-detect.sum_y2)/10.0 + ) + print ("ok") + continue + + # get detect result + detect_result = detect.color_detect(frame) + if detect_result is None: + cv2.imshow("figure", frame) + continue + else: + x, y = detect_result + # calculate real coord between cube and mycobot + real_x, real_y = detect.get_position(x, y) + if num == 20: + detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0) + detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color) + num = real_sx = real_sy = 0 + + else: + num += 1 + real_sy += real_y + real_sx += real_x + + cv2.imshow("figure", frame) diff --git a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py new file mode 100644 index 0000000..68a1432 --- /dev/null +++ b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py @@ -0,0 +1,660 @@ +# encoding:utf-8 +#!/usr/bin/env python2 + +from multiprocessing import Process, Pipe +import cv2 +import numpy as np +import time +import os,sys +import rospy +from visualization_msgs.msg import Marker +from pymycobot.mycobot import MyCobot +from moving_utils import Movement + +IS_CV_4 = cv2.__version__[0] == '4' +__version__ = "1.0" # Adaptive seeed + + +class Object_detect(Movement): + + def __init__(self, camera_x = 155, camera_y = 10): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + self.mc = None + + # 移动角度 + self.move_angles = [ + [-7.11, -6.94, -55.01, -24.16, 0, -15], # init the point + [18.8, -7.91, -54.49, -23.02, -0.79, -14.76], # point to grab + ] + + # 移动坐标 + self.move_coords = [ + [132.2, -136.9, 200.8, -178.24, -3.72, -107.17], # above the red bucket + [238.8, -124.1, 204.3, -169.69, -5.52, -96.52], # green + [115.8, 177.3, 210.6, 178.06, -0.92, -6.11], # blue + [-6.9, 173.2, 201.5, 179.93, 0.63, 33.83], # gray + ] + # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed + self.raspi = False + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + if "dev" in self.robot_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + self.Pin = [2, 5] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + + # choose place to set cube + self.color = 0 + # parameters to calculate camera clipping parameters + self.x1 = self.x2 = self.y1 = self.y2 = 0 + # set cache of real coord + self.cache_x = self.cache_y = 0 + # load model of img recognition + # self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb") + # self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt") + # self.label_path = os.path.join(dir_path, "labels.json") + # # load class labels + # self.labels = json.load(open(self.label_path)) + + # use to calculate coord between cube and mycobot + self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 + # The coordinates of the grab center point relative to the mycobot + self.camera_x, self.camera_y = camera_x, camera_y + # The coordinates of the cube relative to the mycobot + self.c_x, self.c_y = 0, 0 + # The ratio of pixels to actual values + self.ratio = 0 + # Get ArUco marker dict that can be detected. + self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) + # Get ArUco marker params. + self.aruco_params = cv2.aruco.DetectorParameters_create() + + # if IS_CV_4: + # self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path) + # else: + # print('Load tensorflow model need the version of opencv is 4.') + # exit(0) + # init a node and a publisher + rospy.init_node("marker", anonymous=True) + self.pub = rospy.Publisher('/cube', Marker, queue_size=1) + # init a Marker + self.marker = Marker() + self.marker.header.frame_id = "/joint1" + self.marker.ns = "cube" + self.marker.type = self.marker.CUBE + self.marker.action = self.marker.ADD + self.marker.scale.x = 0.04 + self.marker.scale.y = 0.04 + self.marker.scale.z = 0.04 + self.marker.color.a = 1.0 + self.marker.color.g = 1.0 + self.marker.color.r = 1.0 + + # marker position initial + self.marker.pose.position.x = 0 + self.marker.pose.position.y = 0 + self.marker.pose.position.z = 0.03 + self.marker.pose.orientation.x = 0 + self.marker.pose.orientation.y = 0 + self.marker.pose.orientation.z = 0 + self.marker.pose.orientation.w = 1.0 + + self.cache_x = self.cache_y = 0 + + # publish marker + def pub_marker(self, x, y, z=0.03): + self.marker.header.stamp = rospy.Time.now() + self.marker.pose.position.x = x + self.marker.pose.position.y = y + self.marker.pose.position.z = z + self.marker.color.g = self.color + self.pub.publish(self.marker) + + def gpio_status(self, flag): + if flag: + # self.GPIO.output(20, 0) + self.GPIO.output(21, 0) + else: + self.GPIO.output(20, 1) + # self.GPIO.output(21, 1) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + # self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + # self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + # send Angle to move mycobot + print (color) + self.mc.send_angles(self.move_angles[1], 25) + time.sleep(3) + + # send coordinates to move mycobot + self.mc.send_coords([x, y, 190.6, 179.87, -3.78, -62.75], 25, 1) # usb :rx,ry,rz -173.3, -5.48, -57.9 + time.sleep(3) + + # self.mc.send_coords([x, y, 150, 179.87, -3.78, -62.75], 25, 0) + # time.sleep(3) + + # self.mc.send_coords([x, y, 105, 179.87, -3.78, -62.75], 25, 0) + self.mc.send_coords([x, y, 103, 179.87, -3.78, -62.75], 25, 0) + + time.sleep(3) + + # open pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + tmp = [] + while True: + if not tmp: + tmp = self.mc.get_angles() + else: + break + time.sleep(0.5) + + # print(tmp) + self.mc.send_angles([tmp[0], -0.71, -54.49, -23.02, -0.79, tmp[5]],25) # [18.8, -7.91, -54.49, -23.02, -0.79, -14.76] + time.sleep(5) + + + + self.mc.send_coords(self.move_coords[color], 25, 1) + self.pub_marker(self.move_coords[color][0]/1000.0, self.move_coords[color] + [1]/1000.0, self.move_coords[color][2]/1000.0) + time.sleep(4) + + # close pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(4) + + self.mc.send_angles(self.move_angles[0], 25) + time.sleep(3) + + # decide whether grab cube + def decide_move(self, x, y, color): + print(x, y, self.cache_x, self.cache_y) + # detect the cube status move or run + if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init mycobot + def run(self): + if "dev" in self.robot_wio : + self.mc = MyCobot(self.robot_wio, 115200) + elif "dev" in self.robot_m5: + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyCobot(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20) + time.sleep(3) + + # draw aruco + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText( + img, + "({},{})".format(x, y), + (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, + 1, + (243, 0, 0), + 2, + ) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params) + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int( + (point_11[0] + point_21[0] + point_31[0] + point_41[0]) / + 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) + / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int( + (point_1[0] + point_2[0] + point_3[0] + point_4[0]) / + 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / + 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and mycobot + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0 / ratio + + # calculate the coords between cube and mycobot + def get_position(self, x, y): + return ((y - self.c_y) * self.ratio + + self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15), + int(self.x1 * 0.7):int(self.x2 * 1.15)] + return frame + + # according the class_id to get object name + def id_class_name(self, class_id): + for key, value in self.labels.items(): + if class_id == int(key): + return value + + # detect object + def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection): + i = 0 + MIN_MATCH_COUNT = 5 + # sift = cv2.xfeatures2d.SIFT_create() + + # find the keypoints and descriptors with SIFT + # kp = [] + # des = [] + kp = kp_list + des = desc_list + + # for i in goal: + # kp0, des0 = sift.detectAndCompute(i, None) + # kp.append(kp0) + # des.append(des0) + + # kp1, des1 = sift.detectAndCompute(goal, None) + # kp2, des2 = sift.detectAndCompute(img, None) + kp2, des2 = kp_img, desc_img + + # FLANN parameters + FLANN_INDEX_KDTREE = 0 + index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) + search_params = dict(checks=50) # or pass empty dictionary + flann = cv2.FlannBasedMatcher(index_params, search_params) + + x, y = 0, 0 + try: + for i in range(len(des)): + matches = flann.knnMatch(des[i], des2, k=2) + # store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。 + good = [] + for m, n in matches: + if m.distance < 0.7 * n.distance: + good.append(m) + + # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时 + if len(good) > MIN_MATCH_COUNT: + + # extract corresponding point pairs from matching 从匹配中提取出对应点对 + # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引 + src_pts = np.float32([kp[i][m.queryIdx].pt + for m in good]).reshape(-1, 1, 2) + dst_pts = np.float32([kp2[m.trainIdx].pt + for m in good]).reshape(-1, 1, 2) + + # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵 + M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, + 5.0) + matchesMask = mask.ravel().tolist() + # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置 + h, w, d = goal[i].shape + pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1], + [w - 1, 0]]).reshape(-1, 1, 2) + dst = cv2.perspectiveTransform(pts, M) + coord = (dst[0][0] + dst[1][0] + dst[2][0] + + dst[3][0]) / 4.0 + connection.send((DRAW_COORDS, coord)) + # cv2.putText(img, "{}".format(coord), (50, 60), + # fontFace=None, fontScale=1, + # color=(0, 255, 0), lineType=1) + print(format(dst[0][0][0])) + x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] + + dst[3][0][0]) / 4.0 + y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] + + dst[3][0][1]) / 4.0 + + # bound box 绘制边框 + # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + connection.send((DRAW_RECT, dst)) + # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA) + except Exception as e: + pass + + if x + y > 0: + return x, y + else: + return None + +# The path to save the image folder +def parse_folder(folder): + restore = [] + path = '' + path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/' + folder + path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/' + folder + if os.path.exists(path1): + path = path1 + elif os.path.exists(path2): + path = path2 + + # print("path:",path) + + for i, j, k in os.walk(path): + for l in k: + restore.append(cv2.imread(folder + '/{}'.format(l))) + return restore + +def compute_keypoints_and_descriptors(sift, images_lists): + kp_list = [] + desc_list = [] + for images in images_lists: + kp_tmp = [] + desc_tmp = [] + for img in images: + kp, desc = sift.detectAndCompute(img, None) + kp_tmp.append(kp) + desc_tmp.append(desc) + kp_list.append(kp_tmp) + desc_list.append(desc_tmp) + + return kp_list, desc_list + +GET_FRAME = 1 +STOP_PROCESSING = 2 +DRAW_COORDS = 3 +DRAW_RECT = 4 +CLEAR_DRAW = 5 +CROP_FRAME = 6 + +def get_frame(connection): + connection.send(GET_FRAME) + frame = connection.recv() + return frame + +def process_transform_frame(frame, x1, y1, x2, y2): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) +# if x1 != x2: + # the cutting ratio here is adjusted according to the actual situation +# frame = frame[int(y2 * 0.2):int(y1 * 1.15), +# int(x1 * 0.7):int(x2 * 1.15)] + return frame + +def process_display_frame(connection): + cap_num = 0 + coord = None + dst = None + x1 = 0 + y1 = 0 + x2 = 0 + y2 = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + if not cap.isOpened(): + cap.open() + while cv2.waitKey(1) < 0: + _, frame = cap.read() + frame = process_transform_frame(frame, x1, y1, x2, y2) + if connection.poll(): + request = connection.recv() + if request == GET_FRAME: + connection.send(frame) + elif request == CLEAR_DRAW: + coord = None + dst = None + elif type(request) is tuple: + if request[0] == DRAW_COORDS: + coord = request[1] + elif request[0] == DRAW_RECT: + dst = request[1] + elif request[0] == CROP_FRAME: + x1 = request[1] + y1 = request[2] + x2 = request[3] + y2 = request[4] + + if not coord is None: + cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None, + fontScale=1, color=(0, 255, 0), lineType=1) + if not dst is None: + frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + cv2.imshow("figure", frame) + time.sleep(0.04) + connection.send(STOP_PROCESSING) + +def run(): + parent_conn, child_conn = Pipe() + child = Process(target = process_display_frame, args=(child_conn,)) + child.start() + + # Object_detect().take_photo() + # Object_detect().cut_photo() + # goal = Object_detect().distinguist() + + res_queue = [[], [], [], []] + res_queue[0] = parse_folder('res/red') + res_queue[1] = parse_folder('res/green') + res_queue[2] = parse_folder('res/blue') + res_queue[3] = parse_folder('res/gray') + + # res_queue = [] + # res_queue.extend(parse_folder('res/red')) + # res_queue.extend(parse_folder('res/green')) + # res_queue.extend(parse_folder('res/gray')) + # res_queue.extend(parse_folder('res/blue')) + + sift = cv2.xfeatures2d.SIFT_create() + kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue) + + # init a class of Object_detect + detect = Object_detect() + # init mycobot + detect.run() + + # _init_ = 20 # + init_num = 0 + nparams = 0 + # num = 0 + # real_sx = real_sy = 0 + while True: + start_time = time.time() + if parent_conn.poll(): + data = parent_conn.recv() + if data == STOP_PROCESSING: + break + # read camera + frame = get_frame(parent_conn) + # deal img + #frame = detect.transform_frame(frame) + + # if _init_ > 0: + # _init_ -= 1 + # continue + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0, + ) + parent_conn.send((CROP_FRAME, + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0)) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and mycobot + if nparams < 10: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + print ("ok") + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and mycobot + detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0, + (detect.sum_y1 + detect.sum_y2) / 20.0, + abs(detect.sum_x1 - detect.sum_x2) / 10.0 + + abs(detect.sum_y1 - detect.sum_y2) / 10.0) + print("ok") + continue + + # get detect result + kp_img, desc_img = sift.detectAndCompute(frame, None) + frame = get_frame(parent_conn) + for i, v in enumerate(res_queue): + # HACK: to update frame every time + detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn) + if detect_result: + x, y = detect_result + # calculate real coord between cube and mycobot + real_x, real_y = detect.get_position(x, y) + detect.color = i + detect.pub_marker(real_x / 1000.0, real_y / 1000.0) + detect.decide_move(real_x, real_y, detect.color) + # if num == 5: + # detect.color = i + # detect.pub_marker(real_sx / 5.0 / 1000.0, + # real_sy / 5.0 / 1000.0) + # detect.decide_move(real_sx / 5.0, real_sy / 5.0, + # detect.color) + # num = real_sx = real_sy = 0 + # else: + # num += 1 + # real_sy += real_y + # real_sx += real_x + parent_conn.send(CLEAR_DRAW) + + # cv2.imshow("figure", frame) + time.sleep(0.05) + end_time = time.time() + # print("loop_time = ", end_time - start_time) + + # close the window + if cv2.waitKey(1) & 0xFF == ord('q'): + # cap.release() + cv2.destroyAllWindows() + sys.exit() + child.join() + + +if __name__ == "__main__": + run() + # Object_detect().take_photo() + # Object_detect().cut_photo() diff --git a/mycobot_ai/ai_mycobot_280/scripts/test.py b/mycobot_ai/ai_mycobot_280/scripts/test.py index 816215a..0e4aead 100755 --- a/mycobot_ai/ai_mycobot_280/scripts/test.py +++ b/mycobot_ai/ai_mycobot_280/scripts/test.py @@ -1,14 +1,14 @@ # -*- coding: utf-8 -*- from pymycobot.mycobot import MyCobot from pymycobot.genre import Angle -from pymycobot import PI_PORT, PI_BAUD # 当使用树莓派版本的mycobot时，可以引用这两个变量进行MyCobot初始化 + # 当使用树莓派版本的mycobot时，可以引用这两个变量进行MyCobot初始化 import time mc = MyCobot("/dev/ttyACM0", 115200) # mc = MyCobot("/dev/ttyUSB0", 115200) # mc = MyCobot("/dev/ttyAMA0", 1000000) -mc.send_angles([0,0,0,0,0,0], 25) +# mc.send_angles([0,0,0,0,0,0], 25) # print(mc.get_angles()) # mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0.0, -15], 30) # time.sleep(4) @@ -42,3 +42,16 @@ mc.send_angles([0,0,0,0,0,0], 25) # print("angles:%s"% mc.get_angles()) # print("coords:%s"% mc.get_coords()) # print("\n") +move_coords = [ + [132.2, -136.9, 200.8, -178.24, -3.72, -107.17], # above the red bucket + [232.5, -124.6, 212.8, -169.94, -5.88, -97.63], # green + [115.8, 177.3, 210.6, 178.06, -0.92, -6.11], # blue + [-6.9, 173.2, 201.5, 179.93, 0.63, 33.83], # gray + ] + +# mc.send_coords(move_coords[1],20, 1) +# mc.send_angles([-13.44, -57.3, 0.7, -22.76, -4.74, -6.76], 20) +mc.send_coords([238.8, -124.1, 204.3, -169.69, -5.52, -96.52], 20, 1) +time.sleep(3) +print(mc.get_angles()) +print(mc.get_coords()) \ No newline at end of file diff --git a/mycobot_ai/ai_mypalletizer_260/launch/vision_wio.launch b/mycobot_ai/ai_mypalletizer_260/launch/vision_wio.launch index 51eb78b..5548425 100644 --- a/mycobot_ai/ai_mypalletizer_260/launch/vision_wio.launch +++ b/mycobot_ai/ai_mypalletizer_260/launch/vision_wio.launch @@ -2,8 +2,8 @@ - - + + @@ -14,7 +14,7 @@ - + diff --git a/mycobot_ai/ai_mypalletizer_260/res/blue/goal9.jpeg b/mycobot_ai/ai_mypalletizer_260/res/blue/goal9.jpeg new file mode 100644 index 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b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py @@ -0,0 +1,550 @@ +# -*- coding:utf-8 -*- +#!/usr/bin/env python2 +import cv2 +import numpy as np +import time +import os,sys +import rospy +from visualization_msgs.msg import Marker +from pymycobot.mypalletizer import MyPalletizer +from moving_utils import Movement + + +IS_CV_4 = cv2.__version__[0] == '4' +__version__ = "1.0" +# Adaptive seeed + + +class Object_detect(Movement): + + def __init__(self, camera_x = 160, camera_y = 10): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + + # declare mypal260 + self.mc = None + + # 移动角度 + self.move_angles = [ + [0, 0, 0, 0], # init the point + [-29.0, 5.88, -4.92, -76.28], # point to grab + [17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab + ] + + # 移动坐标 + self.move_coords = [ + [132.6, -155.6, 211.8, -20.9], # above the red bucket + [232.5, -134.1, 197.7, -45.26], # above the green bucket + [111.6, 159, 221.5, -120], # above the blue bucket + [-15.9, 164.6, 217.5, -119.35], # above the gray bucket + ] + + # which robot: USB* is m5; ACM* is wio; AMA* is raspi + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + self.raspi = False + if "dev" in self.robot_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + # self.Pin = [20, 21] + self.Pin = [2, 5] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + # choose place to set cube + self.color = 0 + # parameters to calculate camera clipping parameters + self.x1 = self.x2 = self.y1 = self.y2 = 0 + # set cache of real coord + self.cache_x = self.cache_y = 0 + + self.HSV = { + "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], + "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], + "green": [np.array([70, 100, 100]), np.array([90, 255, 255])], # [77, 255, 255] + "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], + "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], # np.array([78, 43, 46]), np.array([99, 255, 255]) + } + + # set color HSV + # self.HSV = { + # # "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], + # "yellow": [np.array([22, 93, 70]), np.array([45, 255, 245])], + # "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], + # # "green": [np.array([35, 43, 46]), np.array([77, 255, 255])], + # "green": [np.array([35, 55, 30]), np.array([88, 255, 255])], + # "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], + # # "blue": [np.array([-10, 100, 100]), np.array([10, 255, 255])], + # "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], + # } + # self.HSV = { + # # "yellow": [np.array([11, 85, 70]), np.array([59, 255, 245])], + # "yellow": [np.array([22, 93, 0]), np.array([45, 255, 245])], + # "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], + # "green": [np.array([35, 43, 35]), np.array([90, 255, 255])], + # # "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], + # "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], + # } + # use to calculate coord between cube and mypal260 + self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 + # The coordinates of the grab center point relative to the mypal260 + self.camera_x, self.camera_y = camera_x, camera_y + # The coordinates of the cube relative to the mypal260 + self.c_x, self.c_y = 0, 0 + # The ratio of pixels to actual values + self.ratio = 0 + # Get ArUco marker dict that can be detected. + self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) + # Get ArUco marker params. + self.aruco_params = cv2.aruco.DetectorParameters_create() + + # init a node and a publisher + rospy.init_node("marker", anonymous=True) + self.pub = rospy.Publisher('/cube', Marker, queue_size=1) + # init a Marker + self.marker = Marker() + self.marker.header.frame_id = "/joint1" + self.marker.ns = "cube" + self.marker.type = self.marker.CUBE + self.marker.action = self.marker.ADD + self.marker.scale.x = 0.04 + self.marker.scale.y = 0.04 + self.marker.scale.z = 0.04 + self.marker.color.a = 1.0 + self.marker.color.g = 1.0 + self.marker.color.r = 1.0 + + # marker position initial + self.marker.pose.position.x = 0 + self.marker.pose.position.y = 0 + self.marker.pose.position.z = 0.03 + self.marker.pose.orientation.x = 0 + self.marker.pose.orientation.y = 0 + self.marker.pose.orientation.z = 0 + self.marker.pose.orientation.w = 1.0 + + # publish marker + def pub_marker(self, x, y, z=0.03): + self.marker.header.stamp = rospy.Time.now() + self.marker.pose.position.x = x + self.marker.pose.position.y = y + self.marker.pose.position.z = z + self.marker.color.g = self.color + self.pub.publish(self.marker) + + # pump_control pi + def gpio_status(self, flag): + if flag: + # self.GPIO.output(20, 0) + self.GPIO.output(21, 0) + else: + # self.GPIO.output(20, 1) + self.GPIO.output(21, 1) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + # self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + # self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + # send Angle to move mypal260 + print(color) + self.mc.send_angles(self.move_angles[0], 20) + time.sleep(3) + + # send coordinates to move mypal260 + self.mc.send_coords([x, y, 160, 0], 20, 0) + time.sleep(1.5) + self.mc.send_coords([x, y, 101, 0], 20, 0) + time.sleep(1.5) + + # open pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + self.mc.send_angle(2, 0, 20) + time.sleep(0.3) + self.mc.send_angle(3, -20, 20) + time.sleep(2) + + self.mc.send_coords(self.move_coords[color], 20, 1) + self.pub_marker(self.move_coords[color][0]/1000.0, self.move_coords[color] + [1]/1000.0, self.move_coords[color][2]/1000.0) + time.sleep(3) + + # close pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + + if color == 1: + self.pub_marker( + self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02) + elif color == 0: + self.pub_marker( + self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0) + + self.mc.send_angles(self.move_angles[1], 20) + time.sleep(1.5) + + # decide whether grab cube + def decide_move(self, x, y, color): + print(x, y, self.cache_x, self.cache_y) + # detect the cube status move or run + if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init mypal260 + def run(self): + if "dev" in self.robot_m5: + self.mc = MyPalletizer(self.robot_m5, 115200) + elif "dev" in self.robot_wio: + self.mc = MyPalletizer(self.robot_wio, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyPalletizer(self.robot_raspi, 1000000) + if not self.raspi: + print('start pump') + self.pub_pump(False, self.Pin) + print('end') + self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) + time.sleep(3) + + # draw aruco + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText(img, "({},{})".format(x, y), (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params + ) + + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and mypal260 + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0/ratio + + # calculate the coords between cube and mypal260 + def get_position(self, x, y): + return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + # frame = frame[int(self.y2*0.2):int(self.y1*1.15), + # int(self.x1*0.7):int(self.x2*1.15)] + frame = frame[int(self.y2*0.78):int(self.y1*1.1), + int(self.x1*0.86):int(self.x2*1.08)] + return frame + + # detect cube color + def color_detect(self, img): + # set the arrangement of color'HSV + x = y = 0 + for mycolor, item in self.HSV.items(): + # print("mycolor:",mycolor) + redLower = np.array(item[0]) + redUpper = np.array(item[1]) + + # transfrom the img to model of gray + hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) + # print("hsv",hsv) + + # wipe off all color expect color in range + mask = cv2.inRange(hsv, item[0], item[1]) + + # a etching operation on a picture to remove edge roughness + erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2) + + # the image for expansion operation, its role is to deepen the color depth in the picture + dilation = cv2.dilate(erosion, np.ones( + (1, 1), np.uint8), iterations=2) + + # adds pixels to the image + target = cv2.bitwise_and(img, img, mask=dilation) + + # the filtered image is transformed into a binary image and placed in binary + ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY) + + # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected + contours, hierarchy = cv2.findContours( + dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) + + if len(contours) > 0: + # do something about misidentification + boxes = [ + box + for box in [cv2.boundingRect(c) for c in contours] + if min(img.shape[0], img.shape[1]) / 10 + < min(box[2], box[3]) + < min(img.shape[0], img.shape[1]) / 1 + ] + if boxes: + for box in boxes: + x, y, w, h = box + # find the largest object that fits the requirements + c = max(contours, key=cv2.contourArea) + # get the lower left and upper right points of the positioning object + x, y, w, h = cv2.boundingRect(c) + # locate the target by drawing rectangle + cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2) + # calculate the rectangle center + x, y = (x*2+w)/2, (y*2+h)/2 + # calculate the real coordinates of mypal260 relative to the target + if mycolor == "red": + self.color = 0 + break + elif mycolor == "blue": + self.color = 2 + break + elif mycolor == "green": + self.color = 1 + break + elif mycolor == "cyan": + self.color = 2 + break + + elif mycolor == "yellow": + self.color = 3 + break + + # elif mycolor == "green": + # self.color = 1 + + # if mycolor == "red": + # self.color = 0 + # break + # elif mycolor == "green": + # self.color = 1 + # print('green') + # break + # elif mycolor == "cyan": + # self.color = 2 + # break + # elif mycolor == "blue": + # self.color = 2 + # break + # elif mycolor == "yellow": + # self.color = 3 + # break + # if mycolor == "yellow": + + # self.color = 3 + # print(mycolor) + # break + + # elif mycolor == "red": + # self.color = 0 + # print(mycolor) + # break + + # elif mycolor == "cyan" or mycolor == "blue": + # self.color = 2 + # print(mycolor) + # break + + # # elif mycolor == "blue": + # # self.color =2 + # # break + # else: + # self.color = 1 + # print(mycolor) + # # break + + if abs(x) + abs(y) > 0: + return x, y + else: + return None + +if __name__ == "__main__": + + # open the camera + cap_num = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + if not cap.isOpened(): + cap.open() + # init a class of Object_detect + detect = Object_detect() + # init mypal260 + detect.run() + + _init_ = 20 + init_num = 0 + nparams = 0 + num = 0 + real_sx = real_sy = 0 + while cv2.waitKey(1) < 0: + # read camera + _, frame = cap.read() + # deal img + frame = detect.transform_frame(frame) + if _init_ > 0: + _init_ -= 1 + continue + + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1)/20.0, + (detect.sum_y1)/20.0, + (detect.sum_x2)/20.0, + (detect.sum_y2)/20.0, + ) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and mypal260 + if nparams < 10: + if detect.get_calculate_params(frame) is None: + cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and mypal260 + detect.set_params( + (detect.sum_x1+detect.sum_x2)/20.0, + (detect.sum_y1+detect.sum_y2)/20.0, + abs(detect.sum_x1-detect.sum_x2)/10.0 + + abs(detect.sum_y1-detect.sum_y2)/10.0 + ) + print("ok") + continue + + # get detect result + detect_result = detect.color_detect(frame) + if detect_result is None: + cv2.imshow("figure", frame) + continue + else: + x, y = detect_result + # calculate real coord between cube and mypal260 + real_x, real_y = detect.get_position(x, y) + if num == 20: + detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0) + detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color) + num = real_sx = real_sy = 0 + + else: + num += 1 + real_sy += real_y + real_sx += real_x + + cv2.imshow("figure", frame) + + # close the window + if cv2.waitKey(1) & 0xFF == ord('q'): + cap.release() + cv2.destroyAllWindows() + sys.exit() \ No newline at end of file diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py new file mode 100644 index 0000000..01a7153 --- /dev/null +++ b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py @@ -0,0 +1,628 @@ +#!/usr/bin/env python2 +# encoding:utf-8 +from multiprocessing import Process, Pipe +import cv2 +import numpy as np +import time +import os,sys +import rospy +from visualization_msgs.msg import Marker +from moving_utils import Movement +from pymycobot.mypalletizer import MyPalletizer + +IS_CV_4 = cv2.__version__[0] == '4' +__version__ = "1.0" # Adaptive seeed + + +class Object_detect(Movement): + + def __init__(self, camera_x = 160, camera_y = 10): + # inherit the parent class + super(Object_detect, self).__init__() + # get path of file + dir_path = os.path.dirname(__file__) + + # declare mypal260 + self.mc = None + # 移动角度 + self.move_angles = [ + [0, 0, 0, 0], # init the point + [-29.0, 5.88, -4.92, -76.28], # point to grab + [17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab + ] + + # 移动坐标 + self.move_coords = [ + [132.6, -155.6, 211.8, -20.9], # above the red bucket + [232.5, -134.1, 197.7, -45.26], # above the green bucket + [111.6, 159, 221.5, -120], # above the blue bucket + [-15.9, 164.6, 217.5, -119.35], # above the gray bucket + ] + # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed + self.raspi = False + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + if "dev" in self.robot_m5: + self.Pin = [2, 5] + elif "dev" in self.robot_wio: + self.Pin = [2, 5] + for i in self.move_coords: + i[2] -= 20 + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + import RPi.GPIO as GPIO + GPIO.setwarnings(False) + self.GPIO = GPIO + GPIO.setmode(GPIO.BCM) + GPIO.setup(20, GPIO.OUT) + GPIO.setup(21, GPIO.OUT) + GPIO.output(20, 1) + GPIO.output(21, 1) + self.raspi = True + if self.raspi: + self.gpio_status(False) + # choose place to set cube + self.color = 0 + # parameters to calculate camera clipping parameters + self.x1 = self.x2 = self.y1 = self.y2 = 0 + # set cache of real coord + self.cache_x = self.cache_y = 0 + + # use to calculate coord between cube and mycobot + self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 + # The coordinates of the grab center point relative to the mycobot + self.camera_x, self.camera_y = camera_x, camera_y + # The coordinates of the cube relative to the mycobot + self.c_x, self.c_y = 0, 0 + # The ratio of pixels to actual values + self.ratio = 0 + # Get ArUco marker dict that can be detected. + self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) + # Get ArUco marker params. + self.aruco_params = cv2.aruco.DetectorParameters_create() + + + # init a node and a publisher + rospy.init_node("marker", anonymous=True) + self.pub = rospy.Publisher('/cube', Marker, queue_size=1) + # init a Marker + self.marker = Marker() + self.marker.header.frame_id = "/joint1" + self.marker.ns = "cube" + self.marker.type = self.marker.CUBE + self.marker.action = self.marker.ADD + self.marker.scale.x = 0.04 + self.marker.scale.y = 0.04 + self.marker.scale.z = 0.04 + self.marker.color.a = 1.0 + self.marker.color.g = 1.0 + self.marker.color.r = 1.0 + + # marker position initial + self.marker.pose.position.x = 0 + self.marker.pose.position.y = 0 + self.marker.pose.position.z = 0.03 + self.marker.pose.orientation.x = 0 + self.marker.pose.orientation.y = 0 + self.marker.pose.orientation.z = 0 + self.marker.pose.orientation.w = 1.0 + + self.cache_x = self.cache_y = 0 + + # publish marker + def pub_marker(self, x, y, z=0.03): + self.marker.header.stamp = rospy.Time.now() + self.marker.pose.position.x = x + self.marker.pose.position.y = y + self.marker.pose.position.z = z + self.marker.color.g = self.color + self.pub.publish(self.marker) + + # pump_control pi + def gpio_status(self, flag): + if flag: + self.GPIO.output(20, 0) + self.GPIO.output(21, 0) + else: + self.GPIO.output(20, 1) + self.GPIO.output(21, 1) + + # 开启吸泵 m5 + def pump_on(self): + # 让2号位工作 + # self.mc.set_basic_output(2, 0) + # 让5号位工作 + self.mc.set_basic_output(5, 0) + + # 停止吸泵 m5 + def pump_off(self): + # 让2号位停止工作 + # self.mc.set_basic_output(2, 1) + # 让5号位停止工作 + self.mc.set_basic_output(5, 1) + + # Grasping motion + def move(self, x, y, color): + print(color) + # send Angle to move mypal260 + self.mc.send_angles(self.move_angles[0], 20) + time.sleep(3) + + # send coordinates to move mypal260 根据不同底板机械臂，调整吸泵高度 + self.mc.send_coords([x, y, 160, 0], 20, 0) + time.sleep(1.5) + self.mc.send_coords([x, y, 101, 0], 20, 0) + time.sleep(1.5) + + # open pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_on() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(True) + time.sleep(1.5) + + self.mc.send_angle(2, 0, 20) + time.sleep(0.3) + self.mc.send_angle(3, -18, 20) + time.sleep(2) + + self.mc.send_coords(self.move_coords[color], 20, 1) + self.pub_marker(self.move_coords[color][0] / 1000.0, + self.move_coords[color][1] / 1000.0, + self.move_coords[color][2] / 1000.0) + time.sleep(3) + + # close pump + if "dev" in self.robot_m5 or "dev" in self.robot_wio: + self.pump_off() + elif "dev" in self.robot_raspi or "dev" in self.robot_jes: + self.gpio_status(False) + time.sleep(6) + + self.mc.send_angles(self.move_angles[1], 20) + time.sleep(1.5) + + # decide whether grab cube + def decide_move(self, x, y, color): + print(x, y, self.cache_x, self.cache_y) + # detect the cube status move or run + if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm + self.cache_x, self.cache_y = x, y + return + else: + self.cache_x = self.cache_y = 0 + # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 + self.move(x, y, color) + + # init mypal260 + def run(self): + if "dev" in self.robot_m5: + self.mc = MyPalletizer(self.robot_m5, 115200) + elif "dev" in self.robot_wio: + self.mc = MyPalletizer(self.robot_wio, 115200) + elif "dev" in self.robot_raspi: + self.mc = MyPalletizer(self.robot_raspi, 1000000) + if not self.raspi: + self.pub_pump(False, self.Pin) + self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) + time.sleep(3) + + # draw aruco + def draw_marker(self, img, x, y): + # draw rectangle on img + cv2.rectangle( + img, + (x - 20, y - 20), + (x + 20, y + 20), + (0, 255, 0), + thickness=2, + lineType=cv2.FONT_HERSHEY_COMPLEX, + ) + # add text on rectangle + cv2.putText( + img, + "({},{})".format(x, y), + (x, y), + cv2.FONT_HERSHEY_COMPLEX_SMALL, + 1, + (243, 0, 0), + 2, + ) + + # get points of two aruco + def get_calculate_params(self, img): + # Convert the image to a gray image + gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + # Detect ArUco marker. + corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( + gray, self.aruco_dict, parameters=self.aruco_params) + + """ + Two Arucos must be present in the picture and in the same order. + There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. + Determine the center of the aruco by the four corners of the aruco. + """ + if len(corners) > 0: + if ids is not None: + if len(corners) <= 1 or ids[0] == 1: + return None + x1 = x2 = y1 = y2 = 0 + point_11, point_21, point_31, point_41 = corners[0][0] + x1, y1 = int( + (point_11[0] + point_21[0] + point_31[0] + point_41[0]) / + 4.0), int( + (point_11[1] + point_21[1] + point_31[1] + point_41[1]) + / 4.0) + point_1, point_2, point_3, point_4 = corners[1][0] + x2, y2 = int( + (point_1[0] + point_2[0] + point_3[0] + point_4[0]) / + 4.0), int( + (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / + 4.0) + return x1, x2, y1, y2 + return None + + # set camera clipping parameters + def set_cut_params(self, x1, y1, x2, y2): + self.x1 = int(x1) + self.y1 = int(y1) + self.x2 = int(x2) + self.y2 = int(y2) + print(self.x1, self.y1, self.x2, self.y2) + + # set parameters to calculate the coords between cube and mycobot + def set_params(self, c_x, c_y, ratio): + self.c_x = c_x + self.c_y = c_y + self.ratio = 220.0 / ratio + + # calculate the coords between cube and mycobot + def get_position(self, x, y): + return ((y - self.c_y) * self.ratio + + self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y) + + """ + Calibrate the camera according to the calibration parameters. + Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. + If two ARuco values have been calculated, clip the video. + """ + + def transform_frame(self, frame): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) + if self.x1 != self.x2: + # the cutting ratio here is adjusted according to the actual situation + frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15), + int(self.x1 * 0.7):int(self.x2 * 1.15)] + return frame + + # according the class_id to get object name + def id_class_name(self, class_id): + for key, value in self.labels.items(): + if class_id == int(key): + return value + + # detect object + def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection): + i = 0 + MIN_MATCH_COUNT = 5 + # sift = cv2.xfeatures2d.SIFT_create() + + # find the keypoints and descriptors with SIFT + # kp = [] + # des = [] + kp = kp_list + des = desc_list + + # for i in goal: + # kp0, des0 = sift.detectAndCompute(i, None) + # kp.append(kp0) + # des.append(des0) + + # kp1, des1 = sift.detectAndCompute(goal, None) + # kp2, des2 = sift.detectAndCompute(img, None) + kp2, des2 = kp_img, desc_img + + # FLANN parameters + FLANN_INDEX_KDTREE = 0 + index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) + search_params = dict(checks=50) # or pass empty dictionary + flann = cv2.FlannBasedMatcher(index_params, search_params) + + x, y = 0, 0 + try: + for i in range(len(des)): + matches = flann.knnMatch(des[i], des2, k=2) + # store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。 + good = [] + for m, n in matches: + if m.distance < 0.7 * n.distance: + good.append(m) + + # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时 + if len(good) > MIN_MATCH_COUNT: + + # extract corresponding point pairs from matching 从匹配中提取出对应点对 + # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引 + src_pts = np.float32([kp[i][m.queryIdx].pt + for m in good]).reshape(-1, 1, 2) + dst_pts = np.float32([kp2[m.trainIdx].pt + for m in good]).reshape(-1, 1, 2) + + # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵 + M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, + 5.0) + matchesMask = mask.ravel().tolist() + # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置 + h, w, d = goal[i].shape + pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1], + [w - 1, 0]]).reshape(-1, 1, 2) + dst = cv2.perspectiveTransform(pts, M) + coord = (dst[0][0] + dst[1][0] + dst[2][0] + + dst[3][0]) / 4.0 + connection.send((DRAW_COORDS, coord)) + # cv2.putText(img, "{}".format(coord), (50, 60), + # fontFace=None, fontScale=1, + # color=(0, 255, 0), lineType=1) + print(format(dst[0][0][0])) + x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] + + dst[3][0][0]) / 4.0 + y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] + + dst[3][0][1]) / 4.0 + + # bound box 绘制边框 + # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + connection.send((DRAW_RECT, dst)) + # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA) + except Exception as e: + pass + + if x + y > 0: + return x, y + else: + return None + +# The path to save the image folder +def parse_folder(folder): + restore = [] + path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mypalletizer_260/' + folder + path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mypalletizer_260/' + folder + + if os.path.exists(path1): + path = path1 + elif os.path.exists(path2): + path = path2 + + for i, j, k in os.walk(path): + for l in k: + restore.append(cv2.imread(folder + '/{}'.format(l))) + return restore + +def compute_keypoints_and_descriptors(sift, images_lists): + kp_list = [] + desc_list = [] + for images in images_lists: + kp_tmp = [] + desc_tmp = [] + for img in images: + kp, desc = sift.detectAndCompute(img, None) + kp_tmp.append(kp) + desc_tmp.append(desc) + kp_list.append(kp_tmp) + desc_list.append(desc_tmp) + + return kp_list, desc_list + +GET_FRAME = 1 +STOP_PROCESSING = 2 +DRAW_COORDS = 3 +DRAW_RECT = 4 +CLEAR_DRAW = 5 +CROP_FRAME = 6 + +def get_frame(connection): + connection.send(GET_FRAME) + frame = connection.recv() + return frame + +def process_transform_frame(frame, x1, y1, x2, y2): + # enlarge the image by 1.5 times + fx = 1.5 + fy = 1.5 + frame = cv2.resize(frame, (0, 0), + fx=fx, + fy=fy, + interpolation=cv2.INTER_CUBIC) +# if x1 != x2: + # the cutting ratio here is adjusted according to the actual situation +# frame = frame[int(y2 * 0.2):int(y1 * 1.15), +# int(x1 * 0.7):int(x2 * 1.15)] + return frame + +def process_display_frame(connection): + cap_num = 0 + coord = None + dst = None + x1 = 0 + y1 = 0 + x2 = 0 + y2 = 0 + cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) + if not cap.isOpened(): + cap.open() + while cv2.waitKey(1) < 0: + _, frame = cap.read() + frame = process_transform_frame(frame, x1, y1, x2, y2) + if connection.poll(): + request = connection.recv() + if request == GET_FRAME: + connection.send(frame) + elif request == CLEAR_DRAW: + coord = None + dst = None + elif type(request) is tuple: + if request[0] == DRAW_COORDS: + coord = request[1] + elif request[0] == DRAW_RECT: + dst = request[1] + elif request[0] == CROP_FRAME: + x1 = request[1] + y1 = request[2] + x2 = request[3] + y2 = request[4] + + if not coord is None: + cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None, + fontScale=1, color=(0, 255, 0), lineType=1) + if not dst is None: + frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) + cv2.imshow("figure", frame) + time.sleep(0.04) + connection.send(STOP_PROCESSING) + +def run(): + parent_conn, child_conn = Pipe() + child = Process(target = process_display_frame, args=(child_conn,)) + child.start() + + res_queue = [[], [], [], []] + res_queue[0] = parse_folder('res/red') + res_queue[1] = parse_folder('res/green') + res_queue[2] = parse_folder('res/blue') + res_queue[3] = parse_folder('res/gray') + + sift = cv2.xfeatures2d.SIFT_create() + kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue) + + # init a class of Object_detect + detect = Object_detect() + + # init mycobot + detect.run() + + # _init_ = 20 # + init_num = 0 + nparams = 0 + # num = 0 + # real_sx = real_sy = 0 + while True: + start_time = time.time() + if parent_conn.poll(): + data = parent_conn.recv() + if data == STOP_PROCESSING: + break + # read camera + frame = get_frame(parent_conn) + # deal img + #frame = detect.transform_frame(frame) + + # if _init_ > 0: + # _init_ -= 1 + # continue + # calculate the parameters of camera clipping + if init_num < 20: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + init_num += 1 + continue + elif init_num == 20: + detect.set_cut_params( + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0, + ) + parent_conn.send((CROP_FRAME, + (detect.sum_x1) / 20.0, + (detect.sum_y1) / 20.0, + (detect.sum_x2) / 20.0, + (detect.sum_y2) / 20.0)) + detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 + init_num += 1 + continue + + # calculate params of the coords between cube and mycobot + if nparams < 10: + if detect.get_calculate_params(frame) is None: + # cv2.imshow("figure", frame) + continue + else: + x1, x2, y1, y2 = detect.get_calculate_params(frame) + detect.draw_marker(frame, x1, y1) + detect.draw_marker(frame, x2, y2) + detect.sum_x1 += x1 + detect.sum_x2 += x2 + detect.sum_y1 += y1 + detect.sum_y2 += y2 + nparams += 1 + print ("ok") + continue + elif nparams == 10: + nparams += 1 + # calculate and set params of calculating real coord between cube and mycobot + detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0, + (detect.sum_y1 + detect.sum_y2) / 20.0, + abs(detect.sum_x1 - detect.sum_x2) / 10.0 + + abs(detect.sum_y1 - detect.sum_y2) / 10.0) + print("ok") + continue + + # get detect result + kp_img, desc_img = sift.detectAndCompute(frame, None) + frame = get_frame(parent_conn) + for i, v in enumerate(res_queue): + # HACK: to update frame every time + detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn) + if detect_result: + x, y = detect_result + # calculate real coord between cube and mycobot + real_x, real_y = detect.get_position(x, y) + detect.color = i + detect.pub_marker(real_x / 1000.0, real_y / 1000.0) + detect.decide_move(real_x, real_y, detect.color) + # if num == 5: + # detect.color = i + # detect.pub_marker(real_sx / 5.0 / 1000.0, + # real_sy / 5.0 / 1000.0) + # detect.decide_move(real_sx / 5.0, real_sy / 5.0, + # detect.color) + # num = real_sx = real_sy = 0 + # else: + # num += 1 + # real_sy += real_y + # real_sx += real_x + parent_conn.send(CLEAR_DRAW) + + # cv2.imshow("figure", frame) + time.sleep(0.05) + end_time = time.time() + # print("loop_time = ", end_time - start_time) + + # close the window + if cv2.waitKey(1) & 0xFF == ord('q'): + # cap.release() + cv2.destroyAllWindows() + sys.exit() + + child.join() + + +if __name__ == "__main__": + run() + # Object_detect().take_photo() + # Object_detect().cut_photo() diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/test.py b/mycobot_ai/ai_mypalletizer_260/scripts/test.py index d73de19..1d232e0 100755 --- a/mycobot_ai/ai_mypalletizer_260/scripts/test.py +++ b/mycobot_ai/ai_mypalletizer_260/scripts/test.py @@ -4,7 +4,7 @@ from pymycobot.genre import Angle from pymycobot import PI_PORT, PI_BAUD # 当使用树莓派版本的mycobot时，可以引用这两个变量进行MyCobot初始化 import time,os -mc = MyPalletizer(os.popen("ls /dev/ttyUSB*").readline()[:-1], 115200) +# mc = MyPalletizer(os.popen("ls /dev/ttyUSB*").readline()[:-1], 115200) # mc = MyPalletizer("/dev/ttyAMA0", 1000000) # mc.send_angles([-29.0, 5.88, -4.92, -76.28],25) # init the point coords:[155.3, -86.1, 218.4, -47.28] @@ -13,8 +13,8 @@ mc = MyPalletizer(os.popen("ls /dev/ttyUSB*").readline()[:-1], 115200) # mc.send_angles([-47.1, 10.19, -10.1, -76.37],25) # above the red bucket; coords:[127.3, -137.1, 219.2, -29.26] # time.sleep(1.5) -mc.send_angles([0,0,-15,0],25) -time.sleep(2) +# mc.send_angles([0,0,-15,0],25) +# time.sleep(2) # mc.send_coords([141.2, -142.0, 206.2, -26.8],25,1) # above the red bucket # time.sleep(2) @@ -38,4 +38,27 @@ time.sleep(2) # mc.set_servo_calibration(1) # mc.set_servo_calibration(2) # mc.set_servo_calibration(3) -# mc.set_servo_calibration(4) \ No newline at end of file +# mc.set_servo_calibration(4) + +import sys +import numpy as np +import cv2 + +print("Please enter blue:") +blue = input() +print("Please enter green:") +green = input() +print("Please enter red:") +red = input() + +color = np.uint8([[[blue, green, red]]]) +hsv_color = cv2.cvtColor(color, cv2.COLOR_BGR2HSV) + +hue = hsv_color[0][0][0] + +print("Lower bound is :") +print("[" + str(hue - 10) + ", 100, 100]\n") + +print("Upper bound is :"), +print("[" + str(hue + 10) + ", 255, 255]") + diff --git a/mypalletizer_260/mypalletizer_260/config/mypal_260.rviz b/mypalletizer_260/mypalletizer_260/config/mypal_260.rviz index 4e1a0a5..2c84dd7 100644 --- a/mypalletizer_260/mypalletizer_260/config/mypal_260.rviz +++ b/mypalletizer_260/mypalletizer_260/config/mypal_260.rviz @@ -8,8 +8,9 @@ Panels: - /Status1 - /RobotModel1 - /TF1 + - /Marker1 Splitter Ratio: 0.5 - Tree Height: 601 + Tree Height: 607 - Class: rviz/Selection Name: Selection - Class: rviz/Tool Properties @@ -18,7 +19,7 @@ Panels: - /2D Nav Goal1 - /Publish Point1 Name: Tool Properties - Splitter Ratio: 0.5886790156364441 + Splitter Ratio: 0.588679016 - Class: rviz/Views Expanded: - /Current View1 @@ -29,8 +30,6 @@ Panels: Name: Time SyncMode: 0 SyncSource: "" -Preferences: - PromptSaveOnExit: true Toolbars: toolButtonStyle: 2 Visualization Manager: @@ -42,7 +41,7 @@ Visualization Manager: Color: 160; 160; 164 Enabled: true Line Style: - Line Width: 0.029999999329447746 + Line Width: 0.0299999993 Value: Lines Name: Grid Normal Cell Count: 0 @@ -69,6 +68,11 @@ Visualization Manager: Show Axes: false Show Trail: false Value: true + env: + Alpha: 1 + Show Axes: false + Show Trail: false + Value: true link1: Alpha: 1 Show Axes: false @@ -107,6 +111,8 @@ Visualization Manager: All Enabled: true base: Value: true + env: + Value: true link1: Value: true link2: @@ -117,13 +123,15 @@ Visualization Manager: Value: true link5: Value: true - Marker Scale: 0.30000001192092896 + Marker Scale: 0.300000012 Name: TF Show Arrows: true Show Axes: true Show Names: true Tree: base: + env: + {} link1: link2: link3: @@ -132,6 +140,14 @@ Visualization Manager: {} Update Interval: 0 Value: true + - Class: rviz/Marker + Enabled: true + Marker Topic: /cube + Name: Marker + Namespaces: + {} + Queue Size: 100 + Value: true Enabled: true Global Options: Background Color: 48; 48; 48 @@ -147,10 +163,7 @@ Visualization Manager: - Class: rviz/FocusCamera - Class: rviz/Measure - Class: rviz/SetInitialPose - Theta std deviation: 0.2617993950843811 Topic: /initialpose - X std deviation: 0.5 - Y std deviation: 0.5 - Class: rviz/SetGoal Topic: /move_base_simple/goal - Class: rviz/PublishPoint @@ -160,33 +173,33 @@ Visualization Manager: Views: Current: Class: rviz/Orbit - Distance: 1.2028908729553223 + Distance: 1.20289087 Enable Stereo Rendering: - Stereo Eye Separation: 0.05999999865889549 + Stereo Eye Separation: 0.0599999987 Stereo Focal Distance: 1 Swap Stereo Eyes: false Value: false Focal Point: X: 0 Y: 0 - Z: 0.10758385062217712 + Z: 0.107583851 Focal Shape Fixed Size: true - Focal Shape Size: 0.05000000074505806 + Focal Shape Size: 0.0500000007 Invert Z Axis: false Name: Current View - Near Clip Distance: 0.009999999776482582 - Pitch: 0.42039862275123596 + Near Clip Distance: 0.00999999978 + Pitch: 0.420398623 Target Frame: Value: Orbit (rviz) - Yaw: 1.1754094362258911 + Yaw: 1.17540944 Saved: ~ Window Geometry: Displays: collapsed: false - Height: 892 + Height: 888 Hide Left Dock: false Hide Right Dock: false - QMainWindow State: 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+ QMainWindow State: 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Selection: collapsed: false Time: @@ -198,201 +211,3 @@ Window Geometry: Width: 1568 X: 144 Y: 41 - -# Panels: -# - Class: rviz/Displays -# Help Height: 78 -# Name: Displays -# Property Tree Widget: -# Expanded: -# - /Global Options1 -# - /Status1 -# - /RobotModel1 -# - /TF1 -# Splitter Ratio: 0.5 -# Tree Height: 775 -# - Class: rviz/Selection -# Name: Selection -# - Class: rviz/Tool Properties -# Expanded: -# - /2D Pose Estimate1 -# - /2D Nav Goal1 -# - /Publish Point1 -# Name: Tool Properties -# Splitter Ratio: 0.588679016 -# - Class: rviz/Views -# Expanded: -# - /Current View1 -# Name: Views -# Splitter Ratio: 0.5 -# - Class: rviz/Time -# Experimental: false -# Name: Time -# SyncMode: 0 -# SyncSource: "" -# Toolbars: -# toolButtonStyle: 2 -# Visualization Manager: -# Class: "" -# Displays: -# - Alpha: 0.5 -# Cell Size: 1 -# Class: rviz/Grid -# Color: 160; 160; 164 -# Enabled: true -# Line Style: -# Line Width: 0.0299999993 -# Value: Lines -# Name: Grid -# Normal Cell Count: 0 -# Offset: -# X: 0 -# Y: 0 -# Z: 0 -# Plane: XY -# Plane Cell Count: 10 -# Reference Frame: -# Value: true -# - Alpha: 1 -# Class: rviz/RobotModel -# Collision Enabled: false -# Enabled: true -# Links: -# All Links Enabled: true -# Expand link Details: false -# Expand Link Details: false -# Expand Tree: false -# Link Tree Style: Links in Alphabetic Order -# base: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true -# link1: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true -# link2: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true -# link3: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true -# link4: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true -# link5: -# Alpha: 1 -# Show Axes: false -# Show Trail: false -# Value: true - -# Name: RobotModel -# Robot Description: robot_description -# TF Prefix: "" -# Update Interval: 0 -# Value: true -# Visual Enabled: true -# - Class: rviz/TF -# Enabled: true -# Frame Timeout: 15 -# Frames: -# All Enabled: true -# base: -# Value: true -# link1: -# Value: true -# link2: -# Value: true -# link3: -# Value: true -# link4: -# Value: true -# link5: -# Value: true - -# Marker Scale: 0.300000012 -# Name: TF -# Show Arrows: true -# Show Axes: true -# Show Names: true -# Tree: -# base: -# link1: -# link2: -# link3: -# link4: -# link5: -# {} -# Update Interval: 0 -# Value: true -# Enabled: true -# Global Options: -# Background Color: 48; 48; 48 -# Default Light: true -# Fixed Frame: base -# Frame Rate: 30 -# Name: root -# Tools: -# - Class: rviz/Interact -# Hide Inactive Objects: true -# - Class: rviz/MoveCamera -# - Class: rviz/Select -# - Class: rviz/FocusCamera -# - Class: rviz/Measure -# - Class: rviz/SetInitialPose -# Topic: /initialpose -# - Class: rviz/SetGoal -# Topic: /move_base_simple/goal -# - Class: rviz/PublishPoint -# Single click: true -# Topic: /clicked_point -# Value: true -# Views: -# Current: -# Class: rviz/Orbit -# Distance: 1.20289087 -# Enable Stereo Rendering: -# Stereo Eye Separation: 0.0599999987 -# Stereo Focal Distance: 1 -# Swap Stereo Eyes: false -# Value: false -# Focal Point: -# X: 0 -# Y: 0 -# Z: 0.107583851 -# Focal Shape Fixed Size: true -# Focal Shape Size: 0.0500000007 -# Invert Z Axis: false -# Name: Current View -# Near Clip Distance: 0.00999999978 -# Pitch: 0.440398335 -# Target Frame: -# Value: Orbit (rviz) -# Yaw: 0.430389732 -# Saved: ~ -# Window Geometry: -# Displays: -# collapsed: false -# Height: 1056 -# Hide Left Dock: false -# Hide Right Dock: false -# QMainWindow State: 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-# Selection: -# collapsed: false -# Time: -# collapsed: false -# Tool Properties: -# collapsed: false -# Views: -# collapsed: false -# Width: 1855 -# X: 65 -# Y: 24 diff --git a/mypalletizer_260/mypalletizer_communication/launch/communication_topic.launch b/mypalletizer_260/mypalletizer_communication/launch/communication_topic.launch index 6cf9d22..3966f37 100644 --- a/mypalletizer_260/mypalletizer_communication/launch/communication_topic.launch +++ b/mypalletizer_260/mypalletizer_communication/launch/communication_topic.launch @@ -1,5 +1,5 @@ - + diff --git a/mypalletizer_260/mypalletizer_communication/scripts/mypal_topics.py b/mypalletizer_260/mypalletizer_communication/scripts/mypal_topics.py index 49deb6e..0655778 100755 --- a/mypalletizer_260/mypalletizer_communication/scripts/mypal_topics.py +++ b/mypalletizer_260/mypalletizer_communication/scripts/mypal_topics.py @@ -67,11 +67,17 @@ class MypalTopics(object): rospy.init_node("mypal_topics") rospy.loginfo("start ...") - port = rospy.get_param("~port", os.popen("ls /dev/ttyUSB*").readline()[:-1]) - print(port) - baud = rospy.get_param("~baud", 115200) - rospy.loginfo("%s,%s" % (port, baud)) - self.mc = MyPalletizer(port, baud) + port_m5 = rospy.get_param("~port", os.popen("ls /dev/ttyUSB*").readline()[:-1]) + # if not port: + port_wio = rospy.get_param("~port", os.popen("ls /dev/ttyACM*").readline()[:-1]) + if "dev" in port_m5: + baud = rospy.get_param("~baud", 115200) + rospy.loginfo("%s,%s" % (port_m5, baud)) + self.mc = MyPalletizer(port_m5, baud) + elif "dev" in port_wio: + baud = rospy.get_param("~baud", 115200) + rospy.loginfo("%s,%s" % (port_wio, baud)) + self.mc = MyPalletizer(port_wio, baud) self.lock = threading.Lock() def start(self): From 8a8032e93aa8816488ecf34fc2f332af7b796d9f Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Wed, 16 Nov 2022 18:16:56 +0800 Subject: [PATCH 02/12] update new aikit code --- mycobot_ai/ai_mecharm_270/res/blue/goal9.jpeg | Bin 0 -> 2944 bytes 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+++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py @@ -17,8 +17,8 @@ __version__ = "1.0" class Object_detect(Movement): - def __init__(self, camera_x = 140, camera_y = 5): # m5 - # def __init__(self, camera_x = 140, camera_y = -5): # pi + def __init__(self, camera_x = 148, camera_y = 5): # m5 + # def __init__(self, camera_x = 148, camera_y = -5): # pi # inherit the parent class super(Object_detect, self).__init__() # get path of file @@ -35,10 +35,10 @@ class Object_detect(Movement): # 移动坐标 self.move_coords = [ - [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket - [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket - [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket - [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + [109.1, -118.8, 164.9, -179.02, 11.07, 132.93], # above the red bucket + [178.4, -98.5, 172.7, -175.8, 41.25, 159.41], # above the green bucket + [97.9, 139.9, 170.7, 163.54, 2.03, 156.04], # above the blue bucket + [-1.8, 143.8, 172.4, 170.69, -4.62, 161.79], # above the gray bucket ] # which robot: USB* is m5; ACM* is wio; AMA* is raspi @@ -165,9 +165,9 @@ class Object_detect(Movement): self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 - # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi + # self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi time.sleep(3) - self.pub_marker(x/1000.0, y/1000.0, 90/1000.0) + self.pub_marker(x/1000.0, y/1000.0, 103/1000.0) # open pump diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py index f2bc2c1..1eadbbf 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py @@ -16,7 +16,7 @@ __version__ = "1.0" # Adaptive seeed class Object_detect(Movement): - def __init__(self, camera_x = 145, camera_y = -5): + def __init__(self, camera_x = 148, camera_y = 5): # inherit the parent class super(Object_detect, self).__init__() # get path of file @@ -32,10 +32,10 @@ class Object_detect(Movement): # 移动坐标 self.move_coords = [ - [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket - [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket - [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket - [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + [109.1, -118.8, 164.9, -179.02, 11.07, 132.93], # above the red bucket + [178.4, -98.5, 172.7, -175.8, 41.25, 159.41], # above the green bucket + [97.9, 139.9, 170.7, 163.54, 2.03, 156.04], # above the blue bucket + [-1.8, 143.8, 172.4, 170.69, -4.62, 161.79], # above the gray bucket ] # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed @@ -147,18 +147,17 @@ class Object_detect(Movement): def move(self, x, y, color): # send Angle to move 270 self.mc.send_angles(self.move_angles[0], 30) - time.sleep(7) + time.sleep(4) print("x %s ,y %s" % (x,y)) # send coordinates to move 270 根据不同底板机械臂，调整吸泵高度 self.mc.send_coords([x, y, 140, 179.12, -0.18, 179.46], 30, 0) - time.sleep(7) - print("ntm") + time.sleep(3) self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi # self.mc.send_coords([x, y, 92, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 - time.sleep(6) + time.sleep(3) # open pump if "dev" in self.robot_m5 or "dev" in self.robot_wio: From a60a94aea05f92dad9ee042a2d49c77543e0e666 Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Thu, 17 Nov 2022 14:01:46 +0800 Subject: [PATCH 03/12] fix color --- .../scripts/advance_detect_obj_color.py | 12 +-- .../scripts/advance_detect_obj_color.py | 9 +- .../scripts/advance_detect_obj_color.py | 92 +++---------------- 3 files changed, 25 insertions(+), 88 deletions(-) diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py index ebd2336..ba75b97 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py @@ -77,7 +77,7 @@ class Object_detect(Movement): self.HSV = { "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], - "green": [np.array([35, 43, 46]), np.array([77, 255, 255])], + "green": [np.array([35, 43, 35]), np.array([90, 255, 255])], "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], } @@ -321,15 +321,15 @@ class Object_detect(Movement): def color_detect(self, img): # set the arrangement of color'HSV x = y = 0 + gs_img = cv2.GaussianBlur(img, (3, 3), 0) # 高斯模糊 + # transfrom the img to model of gray + hsv = cv2.cvtColor(gs_img, cv2.COLOR_BGR2HSV) + for mycolor, item in self.HSV.items(): # print("mycolor:",mycolor) redLower = np.array(item[0]) redUpper = np.array(item[1]) - # transfrom the img to model of gray - hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) - # print("hsv",hsv) - # wipe off all color expect color in range mask = cv2.inRange(hsv, item[0], item[1]) @@ -376,7 +376,7 @@ class Object_detect(Movement): self.color = 0 elif mycolor == "green": self.color = 1 - elif mycolor == "cyan": + elif mycolor == "cyan" or mycolor == "blue": self.color = 2 else: self.color = 3 diff --git a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py index 0809e89..da893b8 100644 --- a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py +++ b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py @@ -316,11 +316,13 @@ class Object_detect(Movement): def color_detect(self, img): # set the arrangement of color'HSV x = y = 0 + gs_img = cv2.GaussianBlur(img, (3, 3), 0) # 高斯模糊 + # transfrom the img to model of gray + hsv = cv2.cvtColor(gs_img, cv2.COLOR_BGR2HSV) + for mycolor, item in self.HSV.items(): redLower = np.array(item[0]) redUpper = np.array(item[1]) - # transfrom the img to model of gray - hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) # wipe off all color expect color in range mask = cv2.inRange(hsv, item[0], item[1]) # a etching operation on a picture to remove edge roughness @@ -365,7 +367,7 @@ class Object_detect(Movement): elif mycolor == "green": self.color = 1 - elif mycolor == "cyan": + elif mycolor == "cyan" or mycolor == "blue": self.color = 2 else: @@ -400,7 +402,6 @@ if __name__ == "__main__": _, frame = cap.read() # deal img frame = detect.transform_frame(frame) - if _init_ > 0: _init_ -= 1 continue diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py index 6d3e902..4f79979 100644 --- a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py +++ b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py @@ -73,33 +73,15 @@ class Object_detect(Movement): # set cache of real coord self.cache_x = self.cache_y = 0 + # set color HSV self.HSV = { "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], - "green": [np.array([70, 100, 100]), np.array([90, 255, 255])], # [77, 255, 255] + "green": [np.array([35, 43, 35]), np.array([90, 255, 255])], # [77, 255, 255] "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], # np.array([78, 43, 46]), np.array([99, 255, 255]) } - - # set color HSV - # self.HSV = { - # # "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], - # "yellow": [np.array([22, 93, 70]), np.array([45, 255, 245])], - # "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], - # # "green": [np.array([35, 43, 46]), np.array([77, 255, 255])], - # "green": [np.array([35, 55, 30]), np.array([88, 255, 255])], - # "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], - # # "blue": [np.array([-10, 100, 100]), np.array([10, 255, 255])], - # "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], - # } - # self.HSV = { - # # "yellow": [np.array([11, 85, 70]), np.array([59, 255, 245])], - # "yellow": [np.array([22, 93, 0]), np.array([45, 255, 245])], - # "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], - # "green": [np.array([35, 43, 35]), np.array([90, 255, 255])], - # # "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], - # "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])], - # } + # use to calculate coord between cube and mypal260 self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 # The coordinates of the grab center point relative to the mypal260 @@ -328,14 +310,14 @@ class Object_detect(Movement): def color_detect(self, img): # set the arrangement of color'HSV x = y = 0 + gs_img = cv2.GaussianBlur(img, (3, 3), 0) # 高斯模糊 + # transfrom the img to model of gray + hsv = cv2.cvtColor(gs_img, cv2.COLOR_BGR2HSV) + for mycolor, item in self.HSV.items(): # print("mycolor:",mycolor) redLower = np.array(item[0]) redUpper = np.array(item[1]) - - # transfrom the img to model of gray - hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) - # print("hsv",hsv) # wipe off all color expect color in range mask = cv2.inRange(hsv, item[0], item[1]) @@ -380,64 +362,18 @@ class Object_detect(Movement): # calculate the real coordinates of mypal260 relative to the target if mycolor == "red": self.color = 0 - break - elif mycolor == "blue": - self.color = 2 - break + elif mycolor == "green": self.color = 1 - break - elif mycolor == "cyan": + + elif mycolor == "cyan" or mycolor == "blue": self.color = 2 - break - - elif mycolor == "yellow": - self.color = 3 - break - - # elif mycolor == "green": - # self.color = 1 - # if mycolor == "red": - # self.color = 0 - # break - # elif mycolor == "green": - # self.color = 1 - # print('green') - # break - # elif mycolor == "cyan": - # self.color = 2 - # break - # elif mycolor == "blue": - # self.color = 2 - # break - # elif mycolor == "yellow": - # self.color = 3 - # break - # if mycolor == "yellow": - - # self.color = 3 - # print(mycolor) - # break - - # elif mycolor == "red": - # self.color = 0 - # print(mycolor) - # break - - # elif mycolor == "cyan" or mycolor == "blue": - # self.color = 2 - # print(mycolor) - # break - - # # elif mycolor == "blue": - # # self.color =2 - # # break - # else: - # self.color = 1 - # print(mycolor) - # # break + else: + self.color = 3 + + if abs(x) + abs(y) > 0: return x, y else: From cf705e0dbb422476bc797071becc96c3d01c372f Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Thu, 17 Nov 2022 16:09:25 +0800 Subject: [PATCH 04/12] update --- mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py | 4 ++-- .../ai_mecharm_270/scripts/advance_detect_obj_img_folder.py | 4 ++-- .../ai_mypalletizer_260/scripts/advance_detect_obj_color.py | 2 +- .../scripts/advance_detect_obj_img_folder.py | 2 +- 4 files changed, 6 insertions(+), 6 deletions(-) diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py index ba75b97..90c4967 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_color.py @@ -164,10 +164,10 @@ class Object_detect(Movement): self.pub_marker(x/1000.0, y/1000.0, 140/1000.0) - self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 + self.mc.send_coords([x, y, 96, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 # self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi time.sleep(3) - self.pub_marker(x/1000.0, y/1000.0, 103/1000.0) + self.pub_marker(x/1000.0, y/1000.0, 96/1000.0) # open pump diff --git a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py index 1eadbbf..43da98f 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py +++ b/mycobot_ai/ai_mecharm_270/scripts/advance_detect_obj_img_folder.py @@ -154,7 +154,7 @@ class Object_detect(Movement): self.mc.send_coords([x, y, 140, 179.12, -0.18, 179.46], 30, 0) time.sleep(3) - self.mc.send_coords([x, y, 103, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 + self.mc.send_coords([x, y, 96, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi # self.mc.send_coords([x, y, 92, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 time.sleep(3) @@ -176,7 +176,7 @@ class Object_detect(Movement): # print(tmp) self.mc.send_angles([tmp[0], 17.22, -32.51, tmp[3], 97, tmp[5]],30) - time.sleep(6) + time.sleep(3) self.mc.send_coords(self.move_coords[color], 30, 1) diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py index 4f79979..3c4293e 100644 --- a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py +++ b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_color.py @@ -162,7 +162,7 @@ class Object_detect(Movement): # send coordinates to move mypal260 self.mc.send_coords([x, y, 160, 0], 20, 0) time.sleep(1.5) - self.mc.send_coords([x, y, 101, 0], 20, 0) + self.mc.send_coords([x, y, 96, 0], 20, 0) time.sleep(1.5) # open pump diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py index 01a7153..6ded356 100644 --- a/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py +++ b/mycobot_ai/ai_mypalletizer_260/scripts/advance_detect_obj_img_folder.py @@ -152,7 +152,7 @@ class Object_detect(Movement): # send coordinates to move mypal260 根据不同底板机械臂，调整吸泵高度 self.mc.send_coords([x, y, 160, 0], 20, 0) time.sleep(1.5) - self.mc.send_coords([x, y, 101, 0], 20, 0) + self.mc.send_coords([x, y, 96, 0], 20, 0) time.sleep(1.5) # open pump From be8834ded1384f3f43bbe871344aa4052477a42b Mon Sep 17 00:00:00 2001 From: weijian Date: Fri, 2 Dec 2022 16:45:22 +0800 Subject: [PATCH 05/12] update --- mycobot_280/mycobot_280/scripts/1245.jpg | Bin 31972 -> 0 bytes mycobot_280/mycobot_280/scripts/3a4.bmp | Bin 1683414 -> 0 bytes .../mycobot_280/scripts/calibration_camera.py | 199 ------- mycobot_280/mycobot_280/scripts/mtx_dist.npz | Bin 476 -> 0 bytes mycobot_280/mycobot_280/scripts/test.py | 68 --- .../ai_mecharm_270/scripts/color_test.py | 164 ------ .../scripts/advance_detect_obj_color.py | 480 --------------- .../ai_mycobot_280/scripts/aikit_img.py | 555 ----------------- .../ai_mycobot_280/scripts/encode_test.py | 248 -------- .../ai_mypalletizer_260/scripts/aikit_img.py | 557 ------------------ 10 files changed, 2271 deletions(-) delete mode 100644 mycobot_280/mycobot_280/scripts/1245.jpg delete mode 100644 mycobot_280/mycobot_280/scripts/3a4.bmp delete mode 100644 mycobot_280/mycobot_280/scripts/calibration_camera.py delete mode 100644 mycobot_280/mycobot_280/scripts/mtx_dist.npz delete mode 100755 mycobot_280/mycobot_280/scripts/test.py delete mode 100644 mycobot_ai/ai_mecharm_270/scripts/color_test.py delete mode 100644 mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py delete mode 100644 mycobot_ai/ai_mycobot_280/scripts/aikit_img.py delete mode 100644 mycobot_ai/ai_mycobot_280/scripts/encode_test.py delete mode 100644 mycobot_ai/ai_mypalletizer_260/scripts/aikit_img.py diff --git a/mycobot_280/mycobot_280/scripts/1245.jpg b/mycobot_280/mycobot_280/scripts/1245.jpg deleted file mode 100644 index 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@@ -1,199 +0,0 @@ -#!/usr/bin/python3 -# -*- coding: UTF-8 -*- -import os -import numpy as np -import cv2 as cv - -import cv2 -import matplotlib.pyplot as plt - -# 生成一张630*890的全黑图片 -# img = np.zeros((630,890,3),np.uint8) -# plt.imshow(img[:,:,::-1]) - -# while True: -# # plt.show() -# cv2.imshow('img', img) - -# key = cv2.waitKey(0) -# if key == ord('q'): -# break -# elif key == ord('s'): -# cv2.imwrite('/home/h/catkin_ws/src/mycobot_ros/mycobot_280/mycobot_280/scripts/123.png', img) -# print('saved') - -# cv2.destroyAllWindows() - -path = os.path.join(os.path.dirname(__file__), "3a4.bmp") -print(path) - -frame = cv2.imread(path) -row, col, nc = frame.shape - -width_of_roi = 90 -# 这里是对全黑图片做处理，将图片以黑白间隔的形式zh -for j in range(row): - data = frame[j] - for i in range(col): - f = int(i / width_of_roi) % 2 ^ int(j / width_of_roi) % 2 - if f: - frame[j][i][0] = 255 - frame[j][i][1] = 255 - frame[j][i][2] = 255 -cv2.imshow("", frame) -cv2.waitKey(0) & 0xFF == ord("q") -cv2.imwrite(os.path.join(os.path.dirname(__file__), "1245.jpg"), frame) - - -# import os -# import cv2 -# import threading - -# if_save = False -# # 设置摄像头编号（由于电脑型号不同，分配给USB摄像头的编号也可能不同，一般为0或1） -# cap_num = int(input("Input the camare number:")) -# # 设置所存储的图片名称，设置为1，即表示从1开始累加存储。如：1.jpg,2.jpg,3.jpg...... -# name = int(input("Input start name, use number:")) - -# cap = cv2.VideoCapture(cap_num) -# dir_path = os.path.dirname(__file__) - -# def save(): -# global if_save -# while True: -# input("Input any to save a image:") -# if_save = True - -# # 开启线程进行摄像头拍摄 -# t = threading.Thread(target=save) -# # 设置为异步运行 -# t.setDaemon(True) -# t.start() - -# while cv2.waitKey(1) != ord("q"): -# _, frame = cap.read() -# if if_save: -# # 设置名称为当前路径下，否则会因为运行环境的原因使得存储位置发生变化 -# img_name = os.path.join(dir_path,str(name)+".jpg") -# # 存储图片 -# cv2.imwrite(img_name, frame) -# print("Save {} successful.".format(img_name)) -# name += 1 -# if_save = False -# cv2.imshow("", frame) - - -# import os -# import glob -# import numpy as np -# import cv2 as cv -# from pprint import pprint - -# obj_points = [] # 3d点在现实世界的位置。 -# img_points = [] # 2d点在图片中的位置。 - -# gray = None - -# def calibration_camera(row, col, path=None, cap_num=None, saving=False): -# """校准摄像头 - -# 参数说明: -# row (int): 网格中的行数。 -# col (int): 网格中的列数。 -# path (string): 存放校准图片的位置。 -# cap_num (int): 表示摄像头的编号，一般0或1 -# saving (bool): 是否存放相机矩阵和失真系数(.npz). -# """ - -# # 终止准则/失效准则 -# criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001) -# # 准备物体点, 比如 (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0) -# obj_p = np.zeros((row * col, 3), np.float32) -# obj_p[:, :2] = np.mgrid[0:row, 0:col].T.reshape(-1, 2) -# # 组用于存储来自所有图像的对象点和图像点。 - - -# def _find_grid(img): -# # 使用函数外的参数 -# global gray, obj_points, img_points -# # 将图片转换为灰色度图片 -# gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) -# # 寻找棋盘的角落 -# ret, corners = cv.findChessboardCorners(gray, (row, col), None) -# # 如果找到，则添加处理后的2d点和3d点 -# if ret == True: -# obj_points.append(obj_p) -# corners2 = cv.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria) -# img_points.append(corners) -# # 在图片中绘制并展示所寻找到的角 -# cv.drawChessboardCorners(img, (row, col), corners2, ret) - -# # 要求必须选择使用图片校准或者摄像头实时捕获校准中的一种 -# if path and cap_num: -# raise Exception("The parameter `path` and `cap_num` only need one.") -# # 图片校准 -# if path: -# # 获取当前路径中的所有图片 -# images = glob.glob(os.path.join(path, "*.jpg")) -# pprint(images) -# # 对获取的每张图片进行处理 -# for f_name in images: -# # 读取图片 -# img = cv.imread(f_name) -# _find_grid(img) -# # 展示图片 -# cv.imshow("img", img) -# # 图片展示等待0.5s -# cv.waitKey(500) -# # 摄像头实时捕获校准 -# if cap_num: -# # 开启摄像头 -# cap = cv.VideoCapture(cap_num) -# while True: -# # 读取摄像头开启后的每帧图片 -# _, img = cap.read() -# _find_grid(img) -# cv.imshow("img", img) -# cv.waitKey(500) -# print(len(obj_points)) -# if len(obj_points) > 14: -# break -# # 销毁展示窗口 -# cv.destroyAllWindows() -# # 通过计算获取的3d点和2d点得出相机矩阵和失真系数 -# ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera( -# obj_points, img_points, gray.shape[::-1], None, None -# ) -# print("ret: {}".format(ret)) -# print("matrix:") -# pprint(mtx) -# print("distortion: {}".format(dist)) -# # 决定是否存储所计算出的参数 -# if saving: -# np.savez(os.path.join(os.path.dirname(__file__), "camera_mtx_dist.npz"), mtx=mtx, dist=dist) - -# mean_error = 0 -# for i in range(len(obj_points)): -# img_points_2, _ = cv.projectPoints(obj_points[i], rvecs[i], tvecs[i], mtx, dist) -# error = cv.norm(img_points[i], img_points_2, cv.NORM_L2) / len(img_points_2) -# mean_error += error -# print("total error: {}".format(mean_error / len(obj_points))) - -# return mtx, dist - -# if __name__ == "__main__": -# path = os.path.dirname(__file__) -# mtx, dist = calibration_camera(8, 6, path, saving=True) -# # 设置是否需要测试计算出的参数 -# if_test = input("If testing the result (default: no), [yes/no]:") -# if if_test not in ["y", "Y", "yes", "Yes"]: -# exit(0) - -# cap_num = int(input("Input camera number:")) -# cap = cv.VideoCapture(cap_num) -# while cv.waitKey(1) != ord("q"): -# _, img = cap.read() -# h, w = img.shape[:2] -# # 相机校准 -# dst = cv.undistort(img, mtx, dist) -# cv.imshow("", dst) \ No newline at end of file diff --git a/mycobot_280/mycobot_280/scripts/mtx_dist.npz b/mycobot_280/mycobot_280/scripts/mtx_dist.npz deleted file mode 100644 index 88f1cee94b75077c8812ba2091aa185d6dc84a4e..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 476 zcmWIWW@Zs#0D)6E?}OAD)ql?bvO$;~h;vIS^zsTSC;Nr^21GJ4xG_|#r=%7q7pYq* zsN1AjsOu=Gr{x!w6eZ@x=NF}8(>1*t&3hOv%hcmLl9DKZX=&)e^wv_QWm*>%6#=k7DwbJF*3 zZQOO?^1gNZ1H2iTM3`|0F2olM3=NGS7Br~QHKBV7p=mFW3G-rrH!B-Rh6xC>fpjz@ Ghz9^x<#y)) diff --git a/mycobot_280/mycobot_280/scripts/test.py b/mycobot_280/mycobot_280/scripts/test.py deleted file mode 100755 index a6d3a01..0000000 --- a/mycobot_280/mycobot_280/scripts/test.py +++ /dev/null @@ -1,68 +0,0 @@ -#!/usr/bin/python -# -*- coding: UTF-8 -*- - -from pymycobot.mycobot import MyCobot -import time -import threading -import os - -print(os.path.join(os.path.dirname(__file__))) - -mc = MyCobot('/dev/ttyUSB0', 115200) -mc.set_tool_reference([-50,0,0,0,0,0]) -mc.set_end_type(1) - -init_angles = [0, 0.52, -85.69, 0.0, 89.82, 0.08] -start_angles = [18.64, 0.52, -85.69, 0.0, 89.82, 0.08] -end_angles = [-18.56, 0.52, -85.69, 0.0, 89.82, 0.08] - -ang = [] - -def wait_time(t): - global ang - for i in range(t*10+1): - time.sleep(0.1) - ang1 = mc.get_angles() - ang.append(ang1) - coord = mc.get_coords() - # print('ange-------->', ang) - print('coord-------->', coord) - - -def get_ang(): - i = 0 - - print('55555555555') - ang_list = None - while True: - for j in range(i,len(ang)): - i+=1 - # print('1111111111111') - # if ang_list != ang: - # ang_list = ang - - print('----------', ang[j]) - -t = threading.Thread(target=get_ang) -t.setDaemon(True) -t.start() - -def move(): - try: - mc.send_angles(init_angles, 5) - time.sleep(0.1) - - # for _ in range(50): - - # mc.send_angles(start_angles, 5) - # wait_time(6) - # mc.send_angles(end_angles, 5) - # wait_time(6) - except Exception as e: - print(e) - -while True: - t = wait_time(1) - print('dddd', t) - move() - diff --git a/mycobot_ai/ai_mecharm_270/scripts/color_test.py b/mycobot_ai/ai_mecharm_270/scripts/color_test.py deleted file mode 100644 index a21e333..0000000 --- a/mycobot_ai/ai_mecharm_270/scripts/color_test.py +++ /dev/null @@ -1,164 +0,0 @@ -# ecoding=utf-8 -import cv2 -import numpy as np -from imutils import contours -import math - -'''HSV中的颜色空间 -https://blog.csdn.net/wsp_1138886114/article/details/80660014 -''' -color_dist = {'red': {'Lower': np.array([0, 120, 120]), 'Upper': np.array([6, 255, 255])}, - # 'blue': {'Lower': np.array([100, 80, 46]), 'Upper': np.array([124, 255, 255])}, - # 'blue':{'Lower': np.array([100,43,46]),'Upper': np.array([124,255,255])}, - 'blue':{'Lower': np.array([100,43,46]),'Upper': np.array([124,255,255])}, - "cyan": {'Lower': np.array([78, 43, 46]),'Upper': np.array([99, 255, 255])}, - 'green': {'Lower': np.array([35, 43, 35]), 'Upper': np.array([90, 255, 255])}, - 'yellow': {"Lower": np.array([22, 93, 0]), "Upper": np.array([45, 255, 255])}, - # 'orange': {"Lower": np.array([0, 100, 45]), "Upper":np.array([255, 250, 255])}, - 'orange': {"Lower": np.array([11, 43, 46]), "Upper":np.array([25, 255, 255])}, - } - -cap = cv2.VideoCapture(0) -# cap = cv2.VideoCapture("src/test_1_2.mp4") -cap.set(3,420) -cap.set(4,360) - -cv2.namedWindow('camera', cv2.WINDOW_AUTOSIZE) -# 内核 -kernel = np.ones((5, 5), np.uint8) - -while cap.isOpened(): - ret, frame = cap.read() - if ret: - if frame is not None: - - gs_frame = cv2.GaussianBlur(frame, (5, 5), 0)# 高斯模糊 - hsv = cv2.cvtColor(gs_frame, cv2.COLOR_BGR2HSV) # 转化成HSV图像 - erode_hsv = cv2.erode(hsv, None, iterations=2) # 腐蚀 作用是粗的变细 - for _color in color_dist: - _font_x_pos = 0 - _font_y_pos = 0 - ## 颜色阈值识别 - inRange_hsv = cv2.inRange(erode_hsv, color_dist[_color]['Lower'], color_dist[_color]['Upper']) - # 膨胀操作 - dilation = cv2.dilate(inRange_hsv, kernel, iterations=1) - # 闭操作 - closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel) - # 边缘检测 - edges = cv2.Canny(closing, 10, 20) - # 检测物体边框 - cnts, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) - - # 判断轮廓数量也就是判断是否寻找到轮廓，如果没有找到轮廓就不继续进行操作 - if len(cnts) > 0: - for cnt in cnts: - if cv2.contourArea(cnt) >1500: - peri = cv2.arcLength(cnt,True) - #print(peri) - # 用于获得轮廓的近似值，使用cv2.drawCountors进行画图操作 ， - # 参数说明：cnt为输入的轮廓值， epsilon为阈值T，通常使用轮廓的周长作为阈值，True表示的是轮廓是闭合的 - ''' - cv2.approxPolyDP - @:param - cnt: - epsilon :算法参数 - True：表示是否闭合 - ''' - approx = cv2.approxPolyDP(cnt,0.02*peri,True) - # print(len(approx)) - # 提取拐点 - ''' - 返回列表元素，列表中的元素代表一个边沿信息。 - ''' - objCor = len(approx) - - if objCor ==3: - '''https://blog.51cto.com/hiszm/5201991''' - objectType = "Triangle" - mm = cv2.moments(cnt) - cx = int(mm['m10']/mm['m00']) - cy = int(mm['m01']/mm['m00']) - _font_x_pos = cx - _font_y_pos = cy - cv2.circle(frame,(cx,cy),3,(0,0,255),-1) - cv2.drawContours(frame, [cnt], 0, (0, 0, 255), 3) - print("三角形的坐标",cx,cy) - - - # 检测出是矩形 - elif objCor == 4: - # 可旋转矩形，即最小的外包矩形 - rect= cv2.minAreaRect(cnt) - ''' - @:param - 函数 cv2.minAreaRect() 返回一个Box2D结构 rect：（最小外接矩形的中心（x，y），（宽度，高度），旋转角度）。 - 分别对应于返回值：(rect[0][0], rect[0][1]), (rect[1][0], rect[1][1]), rect[2] - ''' - # 中心点坐标 - pos_x = int(rect[0][0]) - pos_y = int(rect[0][1]) - #print("position",pos_x,pos_y) - # 旋转角度 - theta = np.round(cv2.minAreaRect(cnt)[2],2) - box = cv2.boxPoints(rect) - box = np.int0(box) - print("物体的坐标为",(pos_x,pos_y),"旋转角度为",theta) - # 判断长方形还是正方形 - _font_x_pos = box[0][0] - _font_y_pos = box[0][1] - _W = math.sqrt(math.pow((box[0][0] - box[1][0]), 2) + math.pow((box[0][1] - box[1][1]), 2)) - _H = math.sqrt(math.pow((box[0][0] - box[3][0]), 2) + math.pow((box[0][1] - box[3][1]), 2)) - # 长宽比 - aspRatio = _W/float(_H) - if aspRatio >0.98 and aspRatio <1.03: - - objectType= "Square"#正方形 - else: - objectType="Rectangle"#长方形 - _pos = (pos_x,pos_y) - cv2.circle(frame,_pos,1,(0,0,255),2)#绘制中心点 - #cv2.putText(frame, 'teheta = ' + str(theta), (int(_font_x_pos),int(_font_y_pos+20)), cv2.FONT_HERSHEY_COMPLEX_SMALL,0.8, (0, 255, 0) ) - cv2.drawContours(frame,[box],0,(0,0,255),2) - # 圆形 - elif objCor>4: - objectType= "Circles" - ''' - void minEnclosingCircle(InputArray points, Point2f& center, float& radius) - @:param - points：输入信息，可以为包含点的容器(vector)或是Mat。 - center：包覆圆形的圆心。 - radius：包覆圆形的半径。 - ''' - (x,y),radius = cv2.minEnclosingCircle(cnt) - center = (int(x),int(y)) - radius = int(radius) - _font_x_pos = center[0] - _font_y_pos = center[1] - print("物体的圆心为:",(_font_x_pos, _font_y_pos),"半径为",radius) - cv2.circle(frame,center,1,(255,0,0),2)#绘制中心点 - cv2.circle(frame,center,radius,(255,0,0),2) - - else: - objectType="None" - # objectType 物体形状 - print("颜色类别：",_color) - cv2.putText(frame, str(_color + objectType), (int(_font_x_pos),int(_font_y_pos)), cv2.FONT_HERSHEY_COMPLEX_SMALL,1, (0, 255, 0) ) - - cv2.imshow('camera', frame) - # 存储识别结果视频 - # out.write(frame) - - cv2.waitKey(1) - if cv2.waitKey(10) & 0xFF == 27: - break - else: - print("无画面") - break - else: - print("无法读取摄像头！") - break - -cap.release() -# out.release() -cv2.waitKey(0) -cv2.destroyAllWindows() diff --git a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py deleted file mode 100644 index da893b8..0000000 --- a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py +++ /dev/null @@ -1,480 +0,0 @@ -# encoding:utf-8 -#!/usr/bin/env python2 - -import cv2 -import numpy as np -import time -import os,sys -import rospy -from visualization_msgs.msg import Marker -from pymycobot.mycobot import MyCobot -from moving_utils import Movement - -IS_CV_4 = cv2.__version__[0] == '4' -__version__ = "1.0" -# Adaptive seeed - - -class Object_detect(Movement): - - def __init__(self, camera_x = 155, camera_y = 10): - # inherit the parent class - super(Object_detect, self).__init__() - # get path of file - dir_path = os.path.dirname(__file__) - self.mc = None - - # 移动角度 - self.move_angles = [ - [-7.11, -6.94, -55.01, -24.16, 0, -15], # init the point - [18.8, -7.91, -54.49, -23.02, -0.79, -14.76], # point to grab - ] - - # 移动坐标 - self.move_coords = [ - [132.2, -136.9, 200.8, -178.24, -3.72, -107.17], # above the red bucket - [238.8, -124.1, 204.3, -169.69, -5.52, -96.52], # green - [115.8, 177.3, 210.6, 178.06, -0.92, -6.11], # blue - [-6.9, 173.2, 201.5, 179.93, 0.63, 33.83], # gray - ] - # which robot: USB* is m5; ACM* is wio; AMA* is raspi - self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] - self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] - self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] - self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] - self.raspi = False - if "dev" in self.robot_m5: - self.Pin = [2, 5] - elif "dev" in self.robot_wio: - # self.Pin = [20, 21] - self.Pin = [2, 5] - - for i in self.move_coords: - i[2] -= 20 - elif "dev" in self.robot_raspi or "dev" in self.robot_jes: - import RPi.GPIO as GPIO - GPIO.setwarnings(False) - self.GPIO = GPIO - GPIO.setmode(GPIO.BCM) - GPIO.setup(20, GPIO.OUT) - GPIO.setup(21, GPIO.OUT) - GPIO.output(20, 1) - GPIO.output(21, 1) - self.raspi = True - if self.raspi: - self.gpio_status(False) - - # choose place to set cube - self.color = 0 - # parameters to calculate camera clipping parameters - self.x1 = self.x2 = self.y1 = self.y2 = 0 - # set cache of real coord - self.cache_x = self.cache_y = 0 - # set color HSV - self.HSV = { - "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])], - "red": [np.array([0, 43, 46]), np.array([8, 255, 255])], - "green": [np.array([35, 43, 35]), np.array([90, 255, 255])], # [77, 255, 255] - "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])], - "cyan": [np.array([89, 43, 46]), np.array([99, 255, 255])], # np.array([78, 43, 46]), np.array([99, 255, 255]) - } - # use to calculate coord between cube and mycobot - self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 - # The coordinates of the grab center point relative to the mycobot - self.camera_x, self.camera_y = camera_x, camera_y - # The coordinates of the cube relative to the mycobot - self.c_x, self.c_y = 0, 0 - # The ratio of pixels to actual values - self.ratio = 0 - # Get ArUco marker dict that can be detected. - self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) - # Get ArUco marker params. - self.aruco_params = cv2.aruco.DetectorParameters_create() - - # init a node and a publisher - rospy.init_node("marker", anonymous=True) - self.pub = rospy.Publisher('/cube', Marker, queue_size=1) - # init a Marker - self.marker = Marker() - self.marker.header.frame_id = "/joint1" - self.marker.ns = "cube" - self.marker.type = self.marker.CUBE - self.marker.action = self.marker.ADD - self.marker.scale.x = 0.04 - self.marker.scale.y = 0.04 - self.marker.scale.z = 0.04 - self.marker.color.a = 1.0 - self.marker.color.g = 1.0 - self.marker.color.r = 1.0 - - # marker position initial - self.marker.pose.position.x = 0 - self.marker.pose.position.y = 0 - self.marker.pose.position.z = 0.03 - self.marker.pose.orientation.x = 0 - self.marker.pose.orientation.y = 0 - self.marker.pose.orientation.z = 0 - self.marker.pose.orientation.w = 1.0 - - # publish marker - def pub_marker(self, x, y, z=0.03): - self.marker.header.stamp = rospy.Time.now() - self.marker.pose.position.x = x - self.marker.pose.position.y = y - self.marker.pose.position.z = z - self.marker.color.g = self.color - self.pub.publish(self.marker) - - def gpio_status(self, flag): - if flag: - # self.GPIO.output(20, 0) - self.GPIO.output(21, 0) - else: - # self.GPIO.output(20, 1) - self.GPIO.output(21, 1) - - # 开启吸泵 m5 - def pump_on(self): - # 让2号位工作 - # self.mc.set_basic_output(2, 0) - # 让5号位工作 - self.mc.set_basic_output(5, 0) - - # 停止吸泵 m5 - def pump_off(self): - # 让2号位停止工作 - # self.mc.set_basic_output(2, 1) - # 让5号位停止工作 - self.mc.set_basic_output(5, 1) - # Grasping motion - def move(self, x, y, color): - # send Angle to move mycobot - print (color) - self.mc.send_angles(self.move_angles[1], 25) - time.sleep(3) - - # send coordinates to move mycobot - self.mc.send_coords([x, y, 190.6, 179.87, -3.78, -62.75], 25, 1) # usb :rx,ry,rz -173.3, -5.48, -57.9 - time.sleep(3) - - # self.mc.send_coords([x, y, 150, 179.87, -3.78, -62.75], 25, 0) - # time.sleep(3) - - self.mc.send_coords([x, y, 103, 179.87, -3.78, -62.75], 25, 0) - time.sleep(3) - - # open pump - if "dev" in self.robot_m5 or "dev" in self.robot_wio: - self.pump_on() - elif "dev" in self.robot_raspi or "dev" in self.robot_jes: - self.gpio_status(True) - time.sleep(1.5) - - tmp = [] - while True: - if not tmp: - tmp = self.mc.get_angles() - else: - break - time.sleep(0.5) - - # print(tmp) - self.mc.send_angles([tmp[0], -0.71, -54.49, -23.02, -0.79, tmp[5]],25) # [18.8, -7.91, -54.49, -23.02, -0.79, -14.76] - time.sleep(2.5) - - self.pub_marker( - self.move_coords[2][0]/1000.0, self.move_coords[2][1]/1000.0, self.move_coords[2][2]/1000.0) - - self.mc.send_coords(self.move_coords[color], 25, 1) - self.pub_marker(self.move_coords[color][0]/1000.0, self.move_coords[color] - [1]/1000.0, self.move_coords[color][2]/1000.0) - time.sleep(3) - - # close pump - if "dev" in self.robot_m5 or "dev" in self.robot_wio: - self.pump_off() - elif "dev" in self.robot_raspi or "dev" in self.robot_jes: - self.gpio_status(False) - time.sleep(4) - - if color == 1: - self.pub_marker( - self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02) - elif color == 0: - self.pub_marker( - self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0) - # self.pub_angles(self.move_angles[0], 20) - self.mc.send_angles(self.move_angles[0], 25) - time.sleep(3) - - # decide whether grab cube - def decide_move(self, x, y, color): - print(x, y, self.cache_x, self.cache_y) - # detect the cube status move or run - if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm - self.cache_x, self.cache_y = x, y - return - else: - self.cache_x = self.cache_y = 0 - # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 - self.move(x, y, color) - - # init mycobot - def run(self): - if "dev" in self.robot_wio : - self.mc = MyCobot(self.robot_wio, 115200) - elif "dev" in self.robot_m5: - self.mc = MyCobot(self.robot_m5, 115200) - elif "dev" in self.robot_raspi: - self.mc = MyCobot(self.robot_raspi, 1000000) - if not self.raspi: - self.pub_pump(False, self.Pin) - self.mc.send_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20) - time.sleep(3) - - # draw aruco - - def draw_marker(self, img, x, y): - # draw rectangle on img - cv2.rectangle( - img, - (x - 20, y - 20), - (x + 20, y + 20), - (0, 255, 0), - thickness=2, - lineType=cv2.FONT_HERSHEY_COMPLEX, - ) - # add text on rectangle - cv2.putText(img, "({},{})".format(x, y), (x, y), - cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,) - - # get points of two aruco - def get_calculate_params(self, img): - # Convert the image to a gray image - gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - # Detect ArUco marker. - corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( - gray, self.aruco_dict, parameters=self.aruco_params - ) - - """ - Two Arucos must be present in the picture and in the same order. - There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. - Determine the center of the aruco by the four corners of the aruco. - """ - if len(corners) > 0: - if ids is not None: - if len(corners) <= 1 or ids[0] == 1: - return None - x1 = x2 = y1 = y2 = 0 - point_11, point_21, point_31, point_41 = corners[0][0] - x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int( - (point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0) - point_1, point_2, point_3, point_4 = corners[1][0] - x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int( - (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0) - return x1, x2, y1, y2 - return None - - # set camera clipping parameters - def set_cut_params(self, x1, y1, x2, y2): - self.x1 = int(x1) - self.y1 = int(y1) - self.x2 = int(x2) - self.y2 = int(y2) - print(self.x1, self.y1, self.x2, self.y2) - - # set parameters to calculate the coords between cube and mycobot - def set_params(self, c_x, c_y, ratio): - self.c_x = c_x - self.c_y = c_y - self.ratio = 220.0/ratio - - # calculate the coords between cube and mycobot - def get_position(self, x, y): - return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y) - - """ - Calibrate the camera according to the calibration parameters. - Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. - If two ARuco values have been calculated, clip the video. - """ - - def transform_frame(self, frame): - # enlarge the image by 1.5 times - fx = 1.5 - fy = 1.5 - frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy, - interpolation=cv2.INTER_CUBIC) - if self.x1 != self.x2: - # the cutting ratio here is adjusted according to the actual situation - frame = frame[int(self.y2*0.78):int(self.y1*1.1), - int(self.x1*0.86):int(self.x2*1.08)] - return frame - - # detect cube color - def color_detect(self, img): - # set the arrangement of color'HSV - x = y = 0 - gs_img = cv2.GaussianBlur(img, (3, 3), 0) # 高斯模糊 - # transfrom the img to model of gray - hsv = cv2.cvtColor(gs_img, cv2.COLOR_BGR2HSV) - - for mycolor, item in self.HSV.items(): - redLower = np.array(item[0]) - redUpper = np.array(item[1]) - # wipe off all color expect color in range - mask = cv2.inRange(hsv, item[0], item[1]) - # a etching operation on a picture to remove edge roughness - erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2) - # the image for expansion operation, its role is to deepen the color depth in the picture - dilation = cv2.dilate(erosion, np.ones( - (1, 1), np.uint8), iterations=2) - - - # adds pixels to the image - target = cv2.bitwise_and(img, img, mask=dilation) - # the filtered image is transformed into a binary image and placed in binary - ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY) - # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected - contours, hierarchy = cv2.findContours( - dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) - - if len(contours) > 0: - # do something about misidentification - boxes = [ - box - for box in [cv2.boundingRect(c) for c in contours] - if min(img.shape[0], img.shape[1]) / 10 - < min(box[2], box[3]) - < min(img.shape[0], img.shape[1]) / 1 - ] - if boxes: - for box in boxes: - x, y, w, h = box - # find the largest object that fits the requirements - c = max(contours, key=cv2.contourArea) - # get the lower left and upper right points of the positioning object - x, y, w, h = cv2.boundingRect(c) - # locate the target by drawing rectangle - cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2) - # calculate the rectangle center - x, y = (x*2+w)/2, (y*2+h)/2 - # calculate the real coordinates of mycobot relative to the target - if mycolor == "red": - self.color = 0 - - elif mycolor == "green": - self.color = 1 - - elif mycolor == "cyan" or mycolor == "blue": - self.color = 2 - - else: - self.color = 3 - - - if abs(x) + abs(y) > 0: - return x, y - else: - return None - - -if __name__ == "__main__": - # open the camera - cap_num = 0 - cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) - - if not cap.isOpened(): - cap.open() - # init a class of Object_detect - detect = Object_detect() - # init mycobot - detect.run() - - _init_ = 20 # - init_num = 0 - nparams = 0 - num = 0 - real_sx = real_sy = 0 - while cv2.waitKey(1) < 0: - # read camera - _, frame = cap.read() - # deal img - frame = detect.transform_frame(frame) - if _init_ > 0: - _init_ -= 1 - continue - # calculate the parameters of camera clipping - if init_num < 20: - if detect.get_calculate_params(frame) is None: - cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - init_num += 1 - continue - elif init_num == 20: - detect.set_cut_params( - (detect.sum_x1)/20.0, - (detect.sum_y1)/20.0, - (detect.sum_x2)/20.0, - (detect.sum_y2)/20.0, - ) - detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 - init_num += 1 - continue - - # calculate params of the coords between cube and mycobot - if nparams < 10: - if detect.get_calculate_params(frame) is None: - cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - nparams += 1 - continue - elif nparams == 10: - nparams += 1 - # calculate and set params of calculating real coord between cube and mycobot - detect.set_params( - (detect.sum_x1+detect.sum_x2)/20.0, - (detect.sum_y1+detect.sum_y2)/20.0, - abs(detect.sum_x1-detect.sum_x2)/10.0 + - abs(detect.sum_y1-detect.sum_y2)/10.0 - ) - print ("ok") - continue - - # get detect result - detect_result = detect.color_detect(frame) - if detect_result is None: - cv2.imshow("figure", frame) - continue - else: - x, y = detect_result - # calculate real coord between cube and mycobot - real_x, real_y = detect.get_position(x, y) - if num == 20: - detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0) - detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color) - num = real_sx = real_sy = 0 - - else: - num += 1 - real_sy += real_y - real_sx += real_x - - cv2.imshow("figure", frame) diff --git a/mycobot_ai/ai_mycobot_280/scripts/aikit_img.py b/mycobot_ai/ai_mycobot_280/scripts/aikit_img.py deleted file mode 100644 index f071a8a..0000000 --- a/mycobot_ai/ai_mycobot_280/scripts/aikit_img.py +++ /dev/null @@ -1,555 +0,0 @@ -# encoding=utf-8 -from multiprocessing import Process, Pipe -from cgi import parse -from difflib import restore -# import queue -from sys import path -from tokenize import Pointfloat -from turtle import color -# from typing_extensions import Self -import cv2 -import numpy as np -import time -import json -import os,sys - -from PIL import Image -from threading import Thread -from pymycobot.mypalletizer import MyPalletizer - -IS_CV_4 = cv2.__version__[0] == '4' -__version__ = "1.0" # Adaptive seeed - - -class Object_detect(): - - def __init__(self, camera_x = 160, camera_y = 10): - # inherit the parent class - super(Object_detect, self).__init__() - - # declare mypal260 - self.mc = None - # 移动角度 - self.move_angles = [ - [0, 0, 0, 0], # init the point - [-29.0, 5.88, -4.92, -76.28], # point to grab - [17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab - ] - - # 移动坐标 - self.move_coords = [ - [132.6, -155.6, 211.8, -20.9], # above the red bucket - [232.5, -134.1, 197.7, -45.26], # above the green bucket - [111.6, 159, 221.5, -120], # above the blue bucket - [-15.9, 164.6, 217.5, -119.35], # above the gray bucket - ] - - # choose place to set cube - self.color = 0 - # parameters to calculate camera clipping parameters - self.x1 = self.x2 = self.y1 = self.y2 = 0 - # set cache of real coord - self.cache_x = self.cache_y = 0 - - # use to calculate coord between cube and mycobot - self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 - # The coordinates of the grab center point relative to the mycobot - self.camera_x, self.camera_y = camera_x, camera_y - # The coordinates of the cube relative to the mycobot - self.c_x, self.c_y = 0, 0 - # The ratio of pixels to actual values - self.ratio = 0 - # Get ArUco marker dict that can be detected. - self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) - # Get ArUco marker params. - self.aruco_params = cv2.aruco.DetectorParameters_create() - - # 开启吸泵 m5 - def pump_on(self): - # 让2号位工作 - # self.mc.set_basic_output(2, 0) - # 让5号位工作 - self.mc.set_basic_output(5, 0) - - # 停止吸泵 m5 - def pump_off(self): - # 让2号位停止工作 - # self.mc.set_basic_output(2, 1) - # 让5号位停止工作 - self.mc.set_basic_output(5, 1) - - # Grasping motion - def move(self, x, y, color): - # send Angle to move mypal260 - self.mc.send_angles(self.move_angles[0], 20) - time.sleep(3) - - # send coordinates to move mypal260 根据不同底板机械臂，调整吸泵高度 - self.mc.send_coords([x, y, 160, 0], 20, 0) - time.sleep(1.5) - self.mc.send_coords([x, y, 110, 0], 20, 0) - time.sleep(1.5) - - # open pump - self.pump_on() - time.sleep(1.5) - - self.mc.send_angle(2, 0, 20) - time.sleep(0.3) - self.mc.send_angle(3, -18, 20) - time.sleep(2) - - self.mc.send_coords(self.move_coords[color], 20, 1) - - time.sleep(3) - - # close pump - - self.pump_off() - time.sleep(6) - - self.mc.send_angles(self.move_angles[1], 20) - time.sleep(1.5) - self.mc.send_angles([-30, 0, 0, 0], 20) - time.sleep(1.5) - - # decide whether grab cube - def decide_move(self, x, y, color): - print(x, y, self.cache_x, self.cache_y) - # detect the cube status move or run - if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm - self.cache_x, self.cache_y = x, y - return - else: - self.cache_x = self.cache_y = 0 - # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 - print('start...') - self.move(x, y, color) - print('end....') - - # init mypal260 - def run(self): - - self.mc = MyPalletizer("COM9", 115200) - - self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) - time.sleep(3) - - # draw aruco - def draw_marker(self, img, x, y): - # draw rectangle on img - cv2.rectangle( - img, - (x - 20, y - 20), - (x + 20, y + 20), - (0, 255, 0), - thickness=2, - lineType=cv2.FONT_HERSHEY_COMPLEX, - ) - # add text on rectangle - cv2.putText( - img, - "({},{})".format(x, y), - (x, y), - cv2.FONT_HERSHEY_COMPLEX_SMALL, - 1, - (243, 0, 0), - 2, - ) - - # get points of two aruco - def get_calculate_params(self, img): - # Convert the image to a gray image - gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - # Detect ArUco marker. - corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( - gray, self.aruco_dict, parameters=self.aruco_params) - - """ - Two Arucos must be present in the picture and in the same order. - There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. - Determine the center of the aruco by the four corners of the aruco. - """ - if len(corners) > 0: - if ids is not None: - if len(corners) <= 1 or ids[0] == 1: - return None - x1 = x2 = y1 = y2 = 0 - point_11, point_21, point_31, point_41 = corners[0][0] - x1, y1 = int( - (point_11[0] + point_21[0] + point_31[0] + point_41[0]) / - 4.0), int( - (point_11[1] + point_21[1] + point_31[1] + point_41[1]) - / 4.0) - point_1, point_2, point_3, point_4 = corners[1][0] - x2, y2 = int( - (point_1[0] + point_2[0] + point_3[0] + point_4[0]) / - 4.0), int( - (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / - 4.0) - return x1, x2, y1, y2 - return None - - # set camera clipping parameters - def set_cut_params(self, x1, y1, x2, y2): - self.x1 = int(x1) - self.y1 = int(y1) - self.x2 = int(x2) - self.y2 = int(y2) - print(self.x1, self.y1, self.x2, self.y2) - - # set parameters to calculate the coords between cube and mycobot - def set_params(self, c_x, c_y, ratio): - self.c_x = c_x - self.c_y = c_y - self.ratio = 220.0 / ratio - - # calculate the coords between cube and mycobot - def get_position(self, x, y): - return ((y - self.c_y) * self.ratio + - self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y) - - """ - Calibrate the camera according to the calibration parameters. - Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. - If two ARuco values have been calculated, clip the video. - """ - - def transform_frame(self, frame): - # enlarge the image by 1.5 times - fx = 1.5 - fy = 1.5 - frame = cv2.resize(frame, (0, 0), - fx=fx, - fy=fy, - interpolation=cv2.INTER_CUBIC) - if self.x1 != self.x2: - # the cutting ratio here is adjusted according to the actual situation - frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15), - int(self.x1 * 0.7):int(self.x2 * 1.15)] - return frame - - # according the class_id to get object name - def id_class_name(self, class_id): - for key, value in self.labels.items(): - if class_id == int(key): - return value - - # detect object - def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection): - i = 0 - MIN_MATCH_COUNT = 5 - # sift = cv2.xfeatures2d.SIFT_create() - - # find the keypoints and descriptors with SIFT - # kp = [] - # des = [] - kp = kp_list - des = desc_list - - # for i in goal: - # kp0, des0 = sift.detectAndCompute(i, None) - # kp.append(kp0) - # des.append(des0) - - # kp1, des1 = sift.detectAndCompute(goal, None) - # kp2, des2 = sift.detectAndCompute(img, None) - kp2, des2 = kp_img, desc_img - - # FLANN parameters - FLANN_INDEX_KDTREE = 0 - index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) - search_params = dict(checks=50) # or pass empty dictionary - flann = cv2.FlannBasedMatcher(index_params, search_params) - - x, y = 0, 0 - try: - for i in range(len(des)): - matches = flann.knnMatch(des[i], des2, k=2) - # store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。 - good = [] - for m, n in matches: - if m.distance < 0.7 * n.distance: - good.append(m) - - # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时 - if len(good) > MIN_MATCH_COUNT: - - # extract corresponding point pairs from matching 从匹配中提取出对应点对 - # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引 - src_pts = np.float32([kp[i][m.queryIdx].pt - for m in good]).reshape(-1, 1, 2) - dst_pts = np.float32([kp2[m.trainIdx].pt - for m in good]).reshape(-1, 1, 2) - - # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵 - M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, - 5.0) - matchesMask = mask.ravel().tolist() - # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置 - h, w, d = goal[i].shape - pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1], - [w - 1, 0]]).reshape(-1, 1, 2) - dst = cv2.perspectiveTransform(pts, M) - coord = (dst[0][0] + dst[1][0] + dst[2][0] + - dst[3][0]) / 4.0 - connection.send((DRAW_COORDS, coord)) - # cv2.putText(img, "{}".format(coord), (50, 60), - # fontFace=None, fontScale=1, - # color=(0, 255, 0), lineType=1) - print(format(dst[0][0][0])) - x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] + - dst[3][0][0]) / 4.0 - y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] + - dst[3][0][1]) / 4.0 - - # bound box 绘制边框 - # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) - connection.send((DRAW_RECT, dst)) - # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA) - except Exception as e: - pass - - if x + y > 0: - return x, y - else: - return None - -# The path to save the image folder -def parse_folder(folder): - restore = [] - path1 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mypalletizer_260/' + folder - path2 = r'D:/BaiduSyncdisk/PythonProject/OpenCV' + folder - - # if os.path.exists(path1): - # path = path1 - # elif os.path.exists(path2): - path = path1 - - for i, j, k in os.walk(path): - for l in k: - restore.append(cv2.imread(folder + '/{}'.format(l))) - return restore - -def compute_keypoints_and_descriptors(sift, images_lists): - kp_list = [] - desc_list = [] - for images in images_lists: - kp_tmp = [] - desc_tmp = [] - for img in images: - kp, desc = sift.detectAndCompute(img, None) - kp_tmp.append(kp) - desc_tmp.append(desc) - kp_list.append(kp_tmp) - desc_list.append(desc_tmp) - - return kp_list, desc_list - -GET_FRAME = 1 -STOP_PROCESSING = 2 -DRAW_COORDS = 3 -DRAW_RECT = 4 -CLEAR_DRAW = 5 -CROP_FRAME = 6 - -def get_frame(connection): - connection.send(GET_FRAME) - frame = connection.recv() - return frame - -def process_transform_frame(frame, x1, y1, x2, y2): - # enlarge the image by 1.5 times - fx = 1.5 - fy = 1.5 - frame = cv2.resize(frame, (0, 0), - fx=fx, - fy=fy, - interpolation=cv2.INTER_CUBIC) -# if x1 != x2: - # the cutting ratio here is adjusted according to the actual situation -# frame = frame[int(y2 * 0.2):int(y1 * 1.15), -# int(x1 * 0.7):int(x2 * 1.15)] - return frame - -def process_display_frame(connection): - cap_num = 1 - coord = None - dst = None - x1 = 0 - y1 = 0 - x2 = 0 - y2 = 0 - cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) - if not cap.isOpened(): - cap.open(1) - while cv2.waitKey(1) < 0: - _, frame = cap.read() - frame = process_transform_frame(frame, x1, y1, x2, y2) - if connection.poll(): - request = connection.recv() - if request == GET_FRAME: - connection.send(frame) - elif request == CLEAR_DRAW: - coord = None - dst = None - elif type(request) is tuple: - if request[0] == DRAW_COORDS: - coord = request[1] - elif request[0] == DRAW_RECT: - dst = request[1] - elif request[0] == CROP_FRAME: - x1 = request[1] - y1 = request[2] - x2 = request[3] - y2 = request[4] - - if not coord is None: - cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None, - fontScale=1, color=(0, 255, 0), lineType=1) - if not dst is None: - frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) - cv2.imshow("figure", frame) - time.sleep(0.04) - connection.send(STOP_PROCESSING) - -def run(): - parent_conn, child_conn = Pipe() - child = Process(target = process_display_frame, args=(child_conn,)) - child.start() - - res_queue = [[], [], [], []] - res_queue[0] = parse_folder('res/red') - res_queue[1] = parse_folder('res/green') - res_queue[2] = parse_folder('res/blue') - res_queue[3] = parse_folder('res/gray') - - sift = cv2.xfeatures2d.SIFT_create() - kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue) - - # init a class of Object_detect - detect = Object_detect() - - # init mycobot - detect.run() - - # _init_ = 20 # - init_num = 0 - nparams = 0 - # num = 0 - # real_sx = real_sy = 0 - while True: - start_time = time.time() - if parent_conn.poll(): - data = parent_conn.recv() - if data == STOP_PROCESSING: - break - # read camera - frame = get_frame(parent_conn) - # deal img - #frame = detect.transform_frame(frame) - - # if _init_ > 0: - # _init_ -= 1 - # continue - # calculate the parameters of camera clipping - if init_num < 20: - if detect.get_calculate_params(frame) is None: - # cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - init_num += 1 - continue - elif init_num == 20: - detect.set_cut_params( - (detect.sum_x1) / 20.0, - (detect.sum_y1) / 20.0, - (detect.sum_x2) / 20.0, - (detect.sum_y2) / 20.0, - ) - parent_conn.send((CROP_FRAME, - (detect.sum_x1) / 20.0, - (detect.sum_y1) / 20.0, - (detect.sum_x2) / 20.0, - (detect.sum_y2) / 20.0)) - detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 - init_num += 1 - continue - - # calculate params of the coords between cube and mycobot - if nparams < 10: - if detect.get_calculate_params(frame) is None: - # cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - nparams += 1 - print ("ok") - continue - elif nparams == 10: - nparams += 1 - # calculate and set params of calculating real coord between cube and mycobot - detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0, - (detect.sum_y1 + detect.sum_y2) / 20.0, - abs(detect.sum_x1 - detect.sum_x2) / 10.0 + - abs(detect.sum_y1 - detect.sum_y2) / 10.0) - print("ok") - continue - - # get detect result - kp_img, desc_img = sift.detectAndCompute(frame, None) - frame = get_frame(parent_conn) - for i, v in enumerate(res_queue): - # HACK: to update frame every time - detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn) - if detect_result: - x, y = detect_result - # calculate real coord between cube and mycobot - real_x, real_y = detect.get_position(x, y) - detect.color = i - detect.pub_marker(real_x / 1000.0, real_y / 1000.0) - detect.decide_move(real_x, real_y, detect.color) - # if num == 5: - # detect.color = i - # detect.pub_marker(real_sx / 5.0 / 1000.0, - # real_sy / 5.0 / 1000.0) - # detect.decide_move(real_sx / 5.0, real_sy / 5.0, - # detect.color) - # num = real_sx = real_sy = 0 - # else: - # num += 1 - # real_sy += real_y - # real_sx += real_x - parent_conn.send(CLEAR_DRAW) - - # cv2.imshow("figure", frame) - time.sleep(0.05) - end_time = time.time() - # print("loop_time = ", end_time - start_time) - - # close the window - if cv2.waitKey(1) & 0xFF == ord('q'): - # cap.release() - cv2.destroyAllWindows() - sys.exit() - - child.join() - - -if __name__ == "__main__": - run() - # Object_detect().take_photo() - # Object_detect().cut_photo() \ No newline at end of file diff --git a/mycobot_ai/ai_mycobot_280/scripts/encode_test.py b/mycobot_ai/ai_mycobot_280/scripts/encode_test.py deleted file mode 100644 index dfd5c47..0000000 --- a/mycobot_ai/ai_mycobot_280/scripts/encode_test.py +++ /dev/null @@ -1,248 +0,0 @@ -# encoding: UTF-8 -#!/usr/bin/env python2 -import cv2 as cv -import os -import numpy as np -import time -import rospy -from visualization_msgs.msg import Marker -from moving_utils import Movement - -# y轴偏移量 -pump_y = -55 -# x轴偏移量 -pump_x = 15 - - -class Detect_marker(Movement): - def __init__(self): - super(Detect_marker, self).__init__() - # set cache of real coord - self.cache_x = self.cache_y = 0 - - # which robot - self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] - self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] - self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] - self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] - self.raspi = False - if "dev" in self.robot_m5: - self.Pin = [2, 5] - elif "dev" in self.robot_wio: - self.Pin = [20, 21] - # for i in self.move_coords: - # i[2] -= 20 - elif "dev" in self.robot_raspi or "dev" in self.robot_jes: - import RPi.GPIO as GPIO - self.GPIO = GPIO - GPIO.setwarnings(False) - GPIO.setmode(GPIO.BCM) - GPIO.setup(20, GPIO.OUT) - GPIO.setup(21, GPIO.OUT) - self.raspi = True - if self.raspi: - self.gpio_status(False) - else: - self.pub_pump(False, self.Pin) - # Creating a Camera Object - cap_num = 0 - self.cap = cv.VideoCapture(cap_num, cv.CAP_V4L) - # Get ArUco marker dict that can be detected. - self.aruco_dict = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_250) - # Get ArUco marker params. - self.aruco_params = cv.aruco.DetectorParameters_create() - self.calibrationParams = cv.FileStorage( - "calibrationFileName.xml", cv.FILE_STORAGE_READ) - # Get distance coefficient. - self.dist_coeffs = self.calibrationParams.getNode("distCoeffs").mat() - - height = self.cap.get(4) - focal_length = width = self.cap.get(3) - center = [width / 2, height / 2] - # Calculate the camera matrix. - self.camera_matrix = np.array( - [ - [focal_length, 0, center[0]], - [0, focal_length, center[1]], - [0, 0, 1], - ], - dtype=np.float32, - ) - # init a node and a publisher - rospy.init_node("encode_marker", anonymous=True) - self.pub = rospy.Publisher('/cube', Marker, queue_size=1) - - self.marker = Marker() - self.marker.header.frame_id = "/joint1" - self.marker.ns = "cube" - self.marker.type = self.marker.CUBE - self.marker.action = self.marker.ADD - self.marker.scale.x = 0.04 - self.marker.scale.y = 0.04 - self.marker.scale.z = 0.04 - self.marker.color.a = 1 - self.marker.color.r = 0.3 - self.marker.color.g = 0.3 - self.marker.color.b = 0.3 - - # marker position initial - self.marker.pose.position.x = 0 - self.marker.pose.position.y = 0 - self.marker.pose.position.z = 0.03 - self.marker.pose.orientation.x = 0 - self.marker.pose.orientation.y = 0 - self.marker.pose.orientation.z = 0 - self.marker.pose.orientation.w = 1.0 - - # Grasping motion - def move(self, x, y): - if self.raspi: - coords = [ - [145.6, -64.9, 285.2, 179.88, 7.67, 179], - [130.1, -155.6, 243.9, 178.99, 5.38, -179.9] - ] - else: - coords = [ - [135.0, -65.5, 280.1, 178.99, 5.38, -179.9], - [136.1, -141.6, 243.9, 178.99, 5.38, -179.9] - ] - - # publish marker - self.marker.header.stamp = rospy.Time.now() - self.marker.pose.position.x = (coords[0][0]-x)/1000.0 - self.marker.pose.position.y = (coords[0][1]-y)/1000.0 - self.pub.publish(self.marker) - - # send coordinates to move mycobot - self.pub_coords(coords[0], 30, 1) - time.sleep(2) - self.pub_coords([coords[0][0]-x, coords[0][1]-y, - 240, 178.99, 5.38, -179.9], 25, 1) - time.sleep(2) - self.pub_coords([coords[0][0]-x, coords[0][1]-y, - 200, 178.99, 5.38, -179.9], 25, 1) - time.sleep(2) - if "dev" in self.robot_m5 or self.raspi: - self.pub_coords([coords[0][0]-x, coords[0][1]-y, - 90, 178.99, 5.38, -179.9], 25, 1) - elif "dev" in self.robot_wio: - self.pub_coords([coords[0][0]-x+20, coords[0][1] - - y-10, 70, 178.99, 5.38, -179.9], 25, 1) - time.sleep(2) - if self.raspi: - self.gpio_status(True) - else: - self.pub_pump(True, self.Pin) - time.sleep(1) - self.pub_coords(coords[0], 30, 1) - time.sleep(3) - self.pub_coords(coords[1], 30, 1) - time.sleep(2) - if self.raspi: - self.gpio_status(False) - else: - self.pub_pump(False, self.Pin) - # publish marker - time.sleep(1) - self.marker.header.stamp = rospy.Time.now() - self.marker.pose.position.x = coords[1][0]/1000.0 - self.marker.pose.position.y = coords[1][1]/1000.0 - self.pub.publish(self.marker) - - self.pub_coords(coords[0], 30, 1) - time.sleep(2) - - def gpio_status(self, flag): - if flag: - self.GPIO.output(20, 0) - self.GPIO.output(21, 0) - else: - self.GPIO.output(20, 1) - self.GPIO.output(21, 1) - - # decide whether grab cube - def decide_move(self, x, y): - - print(x, y) - # detect the cube status move or run - if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm - self.cache_x, self.cache_y = x, y - return - else: - self.cache_x = self.cache_y = 0 - if "dev" in self.robot_jes: - if x > -20: - y += 10 - if y > -25: - x -= 5 - x += 10 - - self.move(x, y) - - # init mycobot - def init_mycobot(self): - - for _ in range(5): - print(_) - self.pub_coords([145.6, -64.9, 285.2, 179.88, 7.67, 179], 20, 1) - time.sleep(0.5) - - def run(self): - global pump_y, pump_x - self.init_mycobot() - num = sum_x = sum_y = 0 - while cv.waitKey(1) < 0: - success, img = self.cap.read() - if not success: - print("It seems that the image cannot be acquired correctly.") - break - - # transfrom the img to model of gray - gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) - # Detect ArUco marker. - corners, ids, rejectImaPoint = cv.aruco.detectMarkers( - gray, self.aruco_dict, parameters=self.aruco_params - ) - font = cv.FONT_HERSHEY_SIMPLEX - if len(corners) > 0: - if ids is not None: - # get informations of aruco - ret = cv.aruco.estimatePoseSingleMarkers( - corners, 0.03, self.camera_matrix, self.dist_coeffs - ) - # rvec:rotation offset,tvec:translation deviator - (rvec, tvec) = (ret[0], ret[1]) - (rvec - tvec).any() - xyz = tvec[0, 0, :] - # calculate the coordinates of the aruco relative to the pump - xyz = [round(xyz[0]*1000+pump_y, 2), round(xyz[1] - * 1000+pump_x, 2), round(xyz[2]*1000, 2)] - cv.putText(img, "Id: " + str(ids[0][0]), (0, 40), font, 0.6, (0, 255, 0), 2, cv.LINE_AA) - for i in range(rvec.shape[0]): - # draw the aruco on img - cv.aruco.drawDetectedMarkers(img, corners) - cv.aruco.drawAxis( - img, - self.camera_matrix, - self.dist_coeffs, - rvec[i, :, :], - tvec[i, :, :], - 0.03, - ) - - if num < 40: - if self.raspi: - sum_x -= 30 - sum_x += xyz[1] - sum_y += xyz[0] - num += 1 - elif num == 40: - self.decide_move(sum_x/40.0, sum_y/40.0) - num = sum_x = sum_y = 0 - - cv.imshow("encode_image", img) - - -if __name__ == "__main__": - detect = Detect_marker() - detect.run() diff --git a/mycobot_ai/ai_mypalletizer_260/scripts/aikit_img.py b/mycobot_ai/ai_mypalletizer_260/scripts/aikit_img.py deleted file mode 100644 index 770ee11..0000000 --- a/mycobot_ai/ai_mypalletizer_260/scripts/aikit_img.py +++ /dev/null @@ -1,557 +0,0 @@ -# encoding=utf-8 -#!/usr/bin/env python2 -from multiprocessing import Process, Pipe -from cgi import parse -from difflib import restore -# import queue -from sys import path -from tokenize import Pointfloat -from turtle import color -# from typing_extensions import Self -import cv2 -import numpy as np -import time -import json -import os,sys - -from PIL import Image -from threading import Thread -from pymycobot.mypalletizer import MyPalletizer - -IS_CV_4 = cv2.__version__[0] == '4' -__version__ = "1.0" # Adaptive seeed - -__metaclass__ = type - -class Object_detect(): - - def __init__(self, camera_x = 160, camera_y = 10): - # inherit the parent class - super(Object_detect, self).__init__() - - # declare mypal260 - self.mc = None - # 移动角度 - self.move_angles = [ - [0, 0, 0, 0], # init the point - [-29.0, 5.88, -4.92, -76.28], # point to grab - [17.4, -10.1, -87.27, 5.8, -2.02, 15], # point to grab - ] - - # 移动坐标 - self.move_coords = [ - [132.6, -155.6, 211.8, -20.9], # above the red bucket - [232.5, -134.1, 197.7, -45.26], # above the green bucket - [111.6, 159, 221.5, -120], # above the blue bucket - [-15.9, 164.6, 217.5, -119.35], # above the gray bucket - ] - - # choose place to set cube - self.color = 0 - # parameters to calculate camera clipping parameters - self.x1 = self.x2 = self.y1 = self.y2 = 0 - # set cache of real coord - self.cache_x = self.cache_y = 0 - - # use to calculate coord between cube and mycobot - self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0 - # The coordinates of the grab center point relative to the mycobot - self.camera_x, self.camera_y = camera_x, camera_y - # The coordinates of the cube relative to the mycobot - self.c_x, self.c_y = 0, 0 - # The ratio of pixels to actual values - self.ratio = 0 - # Get ArUco marker dict that can be detected. - self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250) - # Get ArUco marker params. - self.aruco_params = cv2.aruco.DetectorParameters_create() - - # 开启吸泵 m5 - def pump_on(self): - # 让2号位工作 - # self.mc.set_basic_output(2, 0) - # 让5号位工作 - self.mc.set_basic_output(5, 0) - - # 停止吸泵 m5 - def pump_off(self): - # 让2号位停止工作 - # self.mc.set_basic_output(2, 1) - # 让5号位停止工作 - self.mc.set_basic_output(5, 1) - - # Grasping motion - def move(self, x, y, color): - # send Angle to move mypal260 - self.mc.send_angles(self.move_angles[0], 20) - time.sleep(3) - - # send coordinates to move mypal260 根据不同底板机械臂，调整吸泵高度 - self.mc.send_coords([x, y, 160, 0], 20, 0) - time.sleep(1.5) - self.mc.send_coords([x, y, 110, 0], 20, 0) - time.sleep(1.5) - - # open pump - self.pump_on() - time.sleep(1.5) - - self.mc.send_angle(2, 0, 20) - time.sleep(0.3) - self.mc.send_angle(3, -18, 20) - time.sleep(2) - - self.mc.send_coords(self.move_coords[color], 20, 1) - - time.sleep(3) - - # close pump - - self.pump_off() - time.sleep(6) - - self.mc.send_angles(self.move_angles[1], 20) - time.sleep(1.5) - self.mc.send_angles([-30, 0, 0, 0], 20) - time.sleep(1.5) - - # decide whether grab cube - def decide_move(self, x, y, color): - print(x, y, self.cache_x, self.cache_y) - # detect the cube status move or run - if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm - self.cache_x, self.cache_y = x, y - return - else: - self.cache_x = self.cache_y = 0 - # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动 - print('start...') - self.move(x, y, color) - print('end....') - - # init mypal260 - def run(self): - - self.mc = MyPalletizer("/dev/ttyUSB0", 115200) - - self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) - time.sleep(3) - - # draw aruco - def draw_marker(self, img, x, y): - # draw rectangle on img - cv2.rectangle( - img, - (x - 20, y - 20), - (x + 20, y + 20), - (0, 255, 0), - thickness=2, - lineType=cv2.FONT_HERSHEY_COMPLEX, - ) - # add text on rectangle - cv2.putText( - img, - "({},{})".format(x, y), - (x, y), - cv2.FONT_HERSHEY_COMPLEX_SMALL, - 1, - (243, 0, 0), - 2, - ) - - # get points of two aruco - def get_calculate_params(self, img): - # Convert the image to a gray image - gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - # Detect ArUco marker. - corners, ids, rejectImaPoint = cv2.aruco.detectMarkers( - gray, self.aruco_dict, parameters=self.aruco_params) - - """ - Two Arucos must be present in the picture and in the same order. - There are two Arucos in the Corners, and each aruco contains the pixels of its four corners. - Determine the center of the aruco by the four corners of the aruco. - """ - if len(corners) > 0: - if ids is not None: - if len(corners) <= 1 or ids[0] == 1: - return None - x1 = x2 = y1 = y2 = 0 - point_11, point_21, point_31, point_41 = corners[0][0] - x1, y1 = int( - (point_11[0] + point_21[0] + point_31[0] + point_41[0]) / - 4.0), int( - (point_11[1] + point_21[1] + point_31[1] + point_41[1]) - / 4.0) - point_1, point_2, point_3, point_4 = corners[1][0] - x2, y2 = int( - (point_1[0] + point_2[0] + point_3[0] + point_4[0]) / - 4.0), int( - (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / - 4.0) - return x1, x2, y1, y2 - return None - - # set camera clipping parameters - def set_cut_params(self, x1, y1, x2, y2): - self.x1 = int(x1) - self.y1 = int(y1) - self.x2 = int(x2) - self.y2 = int(y2) - print(self.x1, self.y1, self.x2, self.y2) - - # set parameters to calculate the coords between cube and mycobot - def set_params(self, c_x, c_y, ratio): - self.c_x = c_x - self.c_y = c_y - self.ratio = 220.0 / ratio - - # calculate the coords between cube and mycobot - def get_position(self, x, y): - return ((y - self.c_y) * self.ratio + - self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y) - - """ - Calibrate the camera according to the calibration parameters. - Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times. - If two ARuco values have been calculated, clip the video. - """ - - def transform_frame(self, frame): - # enlarge the image by 1.5 times - fx = 1.5 - fy = 1.5 - frame = cv2.resize(frame, (0, 0), - fx=fx, - fy=fy, - interpolation=cv2.INTER_CUBIC) - if self.x1 != self.x2: - # the cutting ratio here is adjusted according to the actual situation - frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15), - int(self.x1 * 0.7):int(self.x2 * 1.15)] - return frame - - # according the class_id to get object name - def id_class_name(self, class_id): - for key, value in self.labels.items(): - if class_id == int(key): - return value - - # detect object - def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection): - i = 0 - MIN_MATCH_COUNT = 5 - # sift = cv2.xfeatures2d.SIFT_create() - - # find the keypoints and descriptors with SIFT - # kp = [] - # des = [] - kp = kp_list - des = desc_list - - # for i in goal: - # kp0, des0 = sift.detectAndCompute(i, None) - # kp.append(kp0) - # des.append(des0) - - # kp1, des1 = sift.detectAndCompute(goal, None) - # kp2, des2 = sift.detectAndCompute(img, None) - kp2, des2 = kp_img, desc_img - - # FLANN parameters - FLANN_INDEX_KDTREE = 0 - index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5) - search_params = dict(checks=50) # or pass empty dictionary - flann = cv2.FlannBasedMatcher(index_params, search_params) - - x, y = 0, 0 - try: - for i in range(len(des)): - matches = flann.knnMatch(des[i], des2, k=2) - # store all the good matches as per Lowe's ratio test. 根据Lowe比率测试存储所有良好匹配项。 - good = [] - for m, n in matches: - if m.distance < 0.7 * n.distance: - good.append(m) - - # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时 - if len(good) > MIN_MATCH_COUNT: - - # extract corresponding point pairs from matching 从匹配中提取出对应点对 - # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引 - src_pts = np.float32([kp[i][m.queryIdx].pt - for m in good]).reshape(-1, 1, 2) - dst_pts = np.float32([kp2[m.trainIdx].pt - for m in good]).reshape(-1, 1, 2) - - # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵 - M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, - 5.0) - matchesMask = mask.ravel().tolist() - # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置 - h, w, d = goal[i].shape - pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1], - [w - 1, 0]]).reshape(-1, 1, 2) - dst = cv2.perspectiveTransform(pts, M) - coord = (dst[0][0] + dst[1][0] + dst[2][0] + - dst[3][0]) / 4.0 - connection.send((DRAW_COORDS, coord)) - # cv2.putText(img, "{}".format(coord), (50, 60), - # fontFace=None, fontScale=1, - # color=(0, 255, 0), lineType=1) - print(format(dst[0][0][0])) - x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] + - dst[3][0][0]) / 4.0 - y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] + - dst[3][0][1]) / 4.0 - - # bound box 绘制边框 - # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) - connection.send((DRAW_RECT, dst)) - # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA) - except Exception as e: - pass - - if x + y > 0: - return x, y - else: - return None - -# The path to save the image folder -def parse_folder(folder): - restore = [] - path1 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mypalletizer_260/' + folder - path2 = r'D:/BaiduSyncdisk/PythonProject/OpenCV' + folder - - # if os.path.exists(path1): - # path = path1 - # elif os.path.exists(path2): - path = path1 - - for i, j, k in os.walk(path): - for l in k: - restore.append(cv2.imread(folder + '/{}'.format(l))) - return restore - -def compute_keypoints_and_descriptors(sift, images_lists): - kp_list = [] - desc_list = [] - for images in images_lists: - kp_tmp = [] - desc_tmp = [] - for img in images: - kp, desc = sift.detectAndCompute(img, None) - kp_tmp.append(kp) - desc_tmp.append(desc) - kp_list.append(kp_tmp) - desc_list.append(desc_tmp) - - return kp_list, desc_list - -GET_FRAME = 1 -STOP_PROCESSING = 2 -DRAW_COORDS = 3 -DRAW_RECT = 4 -CLEAR_DRAW = 5 -CROP_FRAME = 6 - -def get_frame(connection): - connection.send(GET_FRAME) - frame = connection.recv() - return frame - -def process_transform_frame(frame, x1, y1, x2, y2): - # enlarge the image by 1.5 times - fx = 1.5 - fy = 1.5 - frame = cv2.resize(frame, (0, 0), - fx=fx, - fy=fy, - interpolation=cv2.INTER_CUBIC) -# if x1 != x2: - # the cutting ratio here is adjusted according to the actual situation -# frame = frame[int(y2 * 0.2):int(y1 * 1.15), -# int(x1 * 0.7):int(x2 * 1.15)] - return frame - -def process_display_frame(connection): - cap_num = 0 - coord = None - dst = None - x1 = 0 - y1 = 0 - x2 = 0 - y2 = 0 - cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L) - if not cap.isOpened(): - cap.open() - while cv2.waitKey(1) < 0: - _, frame = cap.read() - frame = process_transform_frame(frame, x1, y1, x2, y2) - if connection.poll(): - request = connection.recv() - if request == GET_FRAME: - connection.send(frame) - elif request == CLEAR_DRAW: - coord = None - dst = None - elif type(request) is tuple: - if request[0] == DRAW_COORDS: - coord = request[1] - elif request[0] == DRAW_RECT: - dst = request[1] - elif request[0] == CROP_FRAME: - x1 = request[1] - y1 = request[2] - x2 = request[3] - y2 = request[4] - - if not coord is None: - cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None, - fontScale=1, color=(0, 255, 0), lineType=1) - if not dst is None: - frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA) - cv2.imshow("figure", frame) - time.sleep(0.04) - connection.send(STOP_PROCESSING) - -def run(): - parent_conn, child_conn = Pipe() - child = Process(target = process_display_frame, args=(child_conn,)) - child.start() - - res_queue = [[], [], [], []] - res_queue[0] = parse_folder('res/red') - res_queue[1] = parse_folder('res/green') - res_queue[2] = parse_folder('res/blue') - res_queue[3] = parse_folder('res/gray') - - sift = cv2.xfeatures2d.SIFT_create() - kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue) - - # init a class of Object_detect - detect = Object_detect() - - # init mycobot - detect.run() - - # _init_ = 20 # - init_num = 0 - nparams = 0 - # num = 0 - # real_sx = real_sy = 0 - while True: - start_time = time.time() - if parent_conn.poll(): - data = parent_conn.recv() - if data == STOP_PROCESSING: - break - # read camera - frame = get_frame(parent_conn) - # deal img - #frame = detect.transform_frame(frame) - - # if _init_ > 0: - # _init_ -= 1 - # continue - # calculate the parameters of camera clipping - if init_num < 20: - if detect.get_calculate_params(frame) is None: - # cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - init_num += 1 - continue - elif init_num == 20: - detect.set_cut_params( - (detect.sum_x1) / 20.0, - (detect.sum_y1) / 20.0, - (detect.sum_x2) / 20.0, - (detect.sum_y2) / 20.0, - ) - parent_conn.send((CROP_FRAME, - (detect.sum_x1) / 20.0, - (detect.sum_y1) / 20.0, - (detect.sum_x2) / 20.0, - (detect.sum_y2) / 20.0)) - detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0 - init_num += 1 - continue - - # calculate params of the coords between cube and mycobot - if nparams < 10: - if detect.get_calculate_params(frame) is None: - # cv2.imshow("figure", frame) - continue - else: - x1, x2, y1, y2 = detect.get_calculate_params(frame) - detect.draw_marker(frame, x1, y1) - detect.draw_marker(frame, x2, y2) - detect.sum_x1 += x1 - detect.sum_x2 += x2 - detect.sum_y1 += y1 - detect.sum_y2 += y2 - nparams += 1 - print ("ok") - continue - elif nparams == 10: - nparams += 1 - # calculate and set params of calculating real coord between cube and mycobot - detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0, - (detect.sum_y1 + detect.sum_y2) / 20.0, - abs(detect.sum_x1 - detect.sum_x2) / 10.0 + - abs(detect.sum_y1 - detect.sum_y2) / 10.0) - print("ok") - continue - - # get detect result - kp_img, desc_img = sift.detectAndCompute(frame, None) - frame = get_frame(parent_conn) - for i, v in enumerate(res_queue): - # HACK: to update frame every time - detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn) - if detect_result: - x, y = detect_result - # calculate real coord between cube and mycobot - real_x, real_y = detect.get_position(x, y) - detect.color = i - # detect.pub_marker(real_x / 1000.0, real_y / 1000.0) - detect.decide_move(real_x, real_y, detect.color) - # if num == 5: - # detect.color = i - # detect.pub_marker(real_sx / 5.0 / 1000.0, - # real_sy / 5.0 / 1000.0) - # detect.decide_move(real_sx / 5.0, real_sy / 5.0, - # detect.color) - # num = real_sx = real_sy = 0 - # else: - # num += 1 - # real_sy += real_y - # real_sx += real_x - parent_conn.send(CLEAR_DRAW) - - # cv2.imshow("figure", frame) - time.sleep(0.05) - end_time = time.time() - # print("loop_time = ", end_time - start_time) - - # close the window - if cv2.waitKey(1) & 0xFF == ord('q'): - # cap.release() - cv2.destroyAllWindows() - sys.exit() - - child.join() - - -if __name__ == "__main__": - run() - # Object_detect().take_photo() - # Object_detect().cut_photo() \ No newline at end of file From c682b6a9428969acdb6e97ecf1dba15d803ed6ae Mon Sep 17 00:00:00 2001 From: weijian Date: Wed, 7 Dec 2022 10:23:06 +0800 Subject: [PATCH 06/12] update mecharm_270 M5 point --- .../scripts/combine_detect_obj_color.py | 18 ++++++++----- .../combine_detect_obj_img_folder_opt.py | 26 +++++++++---------- 2 files changed, 24 insertions(+), 20 deletions(-) diff --git a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py index 3a8e940..1cf478a 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py +++ b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py @@ -40,8 +40,8 @@ class Object_detect(Movement): self.move_coords = [ [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket - [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket - [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + [84.3, 123.8, 205.0, 153.45, -3.67, 142.01], # above the blue bucket + [-15, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket ] # which robot: USB* is m5; ACM* is wio; AMA* is raspi @@ -54,7 +54,9 @@ class Object_detect(Movement): self.Pin = [2, 5] # self.Pin = [5] elif "dev" in self.robot_wio: - self.Pin = [20, 21] + # self.Pin = [20, 21] + self.Pin = [2, 5] + # self.Pin = [5] for i in self.move_coords: i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: @@ -173,7 +175,7 @@ class Object_detect(Movement): # open pump - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.pump_on() elif "dev" in self.robot_raspi or "dev" in self.robot_jes: self.gpio_status(True) @@ -188,7 +190,7 @@ class Object_detect(Movement): time.sleep(0.5) # print(tmp) - self.mc.send_angles([tmp[0], 17.22, -32.51, tmp[3], 97, tmp[5]],30) + self.mc.send_angles([tmp[0], 17.22, -45, tmp[3], 97, tmp[5]],30) time.sleep(3) @@ -200,7 +202,7 @@ class Object_detect(Movement): time.sleep(3) # close pump - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.pump_off() elif "dev" in self.robot_raspi or "dev" in self.robot_jes: self.gpio_status(False) @@ -231,7 +233,9 @@ class Object_detect(Movement): # init 270 def run(self): if "dev" in self.robot_m5: - self.mc = MyCobot(self.robot_m5, 115200) + self.mc = MyCobot(self.robot_m5, 115200) + elif "dev" in self.robot_wio: + self.mc = MyCobot(self.robot_wio, 115200) elif "dev" in self.robot_raspi: self.mc = MyCobot(self.robot_raspi, 1000000) if not self.raspi: diff --git a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py index d0f7873..d9dc686 100755 --- a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py +++ b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py @@ -46,8 +46,8 @@ class Object_detect(Movement): self.move_coords = [ [92.3, -104.9, 211.4, -179.6, 28.91, 131.29], # above the red bucket [165.0, -93.6, 201.4, -173.43, 46.23, 160.65], # above the green bucket - [88.1, 126.3, 193.4, 162.15, 2.23, 156.02], # above the blue bucket - [-5.4, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket + [84.3, 123.8, 205.0, 153.45, -3.67, 142.01], # above the blue bucket + [-15, 120.6, 204.6, 162.66, -6.96, 159.93], # above the gray bucket ] # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed @@ -59,7 +59,8 @@ class Object_detect(Movement): if "dev" in self.robot_m5: self.Pin = [2, 5] elif "dev" in self.robot_wio: - self.Pin = [20, 21] + # self.Pin = [20, 21] + self.Pin = [2, 5] for i in self.move_coords: i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: @@ -158,21 +159,20 @@ class Object_detect(Movement): def move(self, x, y, color): # send Angle to move 270 self.mc.send_angles(self.move_angles[0], 30) - time.sleep(7) + time.sleep(4) print("x %s ,y %s" % (x,y)) # send coordinates to move 270 根据不同底板机械臂，调整吸泵高度 self.mc.send_coords([x, y, 140, 179.12, -0.18, 179.46], 30, 0) - time.sleep(7) - print("ntm") + time.sleep(3) self.mc.send_coords([x, y, 95, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 m5 # self.mc.send_coords([x, y, 90, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 pi # self.mc.send_coords([x, y, 92, 179.12, -0.18, 179.46], 30, 0) # -178.77, -2.69, 40.15 - time.sleep(6) + time.sleep(3) # open pump - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.pump_on() elif "dev" in self.robot_raspi or "dev" in self.robot_jes: self.gpio_status(True) @@ -187,25 +187,25 @@ class Object_detect(Movement): time.sleep(0.5) # print(tmp) - self.mc.send_angles([tmp[0], 17.22, -32.51, tmp[3], 97, tmp[5]],30) - time.sleep(6) + self.mc.send_angles([tmp[0], 17.22, -45, tmp[3], 97, tmp[5]],30) + time.sleep(3) self.mc.send_coords(self.move_coords[color], 30, 1) self.pub_marker(self.move_coords[color][0] / 1000.0, self.move_coords[color][1] / 1000.0, self.move_coords[color][2] / 1000.0) - time.sleep(6) + time.sleep(3) # close pump - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.pump_off() elif "dev" in self.robot_raspi or "dev" in self.robot_jes: self.gpio_status(False) time.sleep(6) self.mc.send_angles(self.move_angles[1], 30) - time.sleep(6) + time.sleep(2) # decide whether grab cube def decide_move(self, x, y, color): From d4b80b82fc1101486f536d2a76eeae71d062d67d Mon Sep 17 00:00:00 2001 From: weijian Date: Wed, 7 Dec 2022 11:10:08 +0800 Subject: [PATCH 07/12] update mecharm_270 M5 point --- .../ai_mecharm_270/scripts/combine_detect_obj_color.py | 6 ++---- .../scripts/combine_detect_obj_img_folder_opt.py | 5 ++--- 2 files changed, 4 insertions(+), 7 deletions(-) diff --git a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py index 1cf478a..92d39af 100644 --- a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py +++ b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_color.py @@ -50,13 +50,11 @@ class Object_detect(Movement): self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] self.raspi = False - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.Pin = [2, 5] # self.Pin = [5] elif "dev" in self.robot_wio: - # self.Pin = [20, 21] - self.Pin = [2, 5] - # self.Pin = [5] + self.Pin = [20, 21] for i in self.move_coords: i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: diff --git a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py index d9dc686..5d891dd 100755 --- a/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py +++ b/mycobot_ai/ai_mecharm_270/scripts/combine_detect_obj_img_folder_opt.py @@ -56,11 +56,10 @@ class Object_detect(Movement): self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] - if "dev" in self.robot_m5: + if "dev" in self.robot_m5 or "dev" in self.robot_wio: self.Pin = [2, 5] elif "dev" in self.robot_wio: - # self.Pin = [20, 21] - self.Pin = [2, 5] + self.Pin = [20, 21] for i in self.move_coords: i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: From d0ce79bc80dce4c1e05ac5bc71ddd2293fabc90e Mon Sep 17 00:00:00 2001 From: weijian Date: Wed, 7 Dec 2022 17:04:33 +0800 Subject: [PATCH 08/12] fix 280pi and mecharm_pi ubuntu20.04 ros1 from python3 --- mecharm/mecharm/scripts/simple_gui.py | 2 +- mecharm/mecharm/scripts/teleop_keyboard.py | 2 +- .../scripts/mecharm_services.py | 67 +++++++++++++++++-- mecharm/mecharm_pi/scripts/simple_gui.py | 7 +- mecharm/mecharm_pi/scripts/teleop_keyboard.py | 4 +- .../mycobot_280pi/scripts/simple_gui.py | 7 +- .../mycobot_280pi/scripts/teleop_keyboard.py | 2 +- .../scripts/mycobot_services.py | 61 +++++++++++++++-- 8 files changed, 129 insertions(+), 23 deletions(-) diff --git a/mecharm/mecharm/scripts/simple_gui.py b/mecharm/mecharm/scripts/simple_gui.py index 67784ec..387718d 100755 --- a/mecharm/mecharm/scripts/simple_gui.py +++ b/mecharm/mecharm/scripts/simple_gui.py @@ -33,7 +33,7 @@ class Window: # 计算 Tk 根窗口的 x 和 y 坐标 x = (self.ws / 2) - 190 y = (self.hs / 2) - 250 - self.win.geometry("430x400+{}+{}".format(x, y)) + self.win.geometry("430x400+{}+{}".format(int(x), int(y))) # layout,布局 self.set_layout() # input section,输入部分 diff --git a/mecharm/mecharm/scripts/teleop_keyboard.py b/mecharm/mecharm/scripts/teleop_keyboard.py index 3d2b971..b7d1033 100755 --- a/mecharm/mecharm/scripts/teleop_keyboard.py +++ b/mecharm/mecharm/scripts/teleop_keyboard.py @@ -84,7 +84,7 @@ def teleop_keyboard(): init_pose = [0, 0, 0, 0, 0, 0, speed] - home_pose = [0, 8, -127, 40, 0, 0, speed] + home_pose = [0, 30, 30, 0, 30, 0, speed] # rsp = set_angles(*init_pose) diff --git a/mecharm/mecharm_communication/scripts/mecharm_services.py b/mecharm/mecharm_communication/scripts/mecharm_services.py index 322127c..aa1e026 100755 --- a/mecharm/mecharm_communication/scripts/mecharm_services.py +++ b/mecharm/mecharm_communication/scripts/mecharm_services.py @@ -1,17 +1,55 @@ -#!/usr/bin/env python2 - # -*- coding: UTF-8 -*- +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- import time import rospy +import os +import fcntl from mycobot_communication.srv import * from pymycobot.mycobot import MyCobot mc = None +# Avoid serial port conflicts and need to be locked +def acquire(lock_file): + open_mode = os.O_RDWR | os.O_CREAT | os.O_TRUNC + fd = os.open(lock_file, open_mode) + + pid = os.getpid() + lock_file_fd = None + + timeout = 50.0 + start_time = current_time = time.time() + while current_time < start_time + timeout: + try: + # The LOCK_EX means that only one process can hold the lock + # The LOCK_NB means that the fcntl.flock() is not blocking + # and we are able to implement termination of while loop, + # when timeout is reached. + fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB) + except (IOError, OSError): + pass + else: + lock_file_fd = fd + break + # print('pid waiting for lock:%d'% pid) + time.sleep(1.0) + current_time = time.time() + if lock_file_fd is None: + os.close(fd) + return lock_file_fd + + +def release(lock_file_fd): + # Do not remove the lockfile: + fcntl.flock(lock_file_fd, fcntl.LOCK_UN) + os.close(lock_file_fd) + return None + def create_handle(): global mc - rospy.init_node("mecharm_services") + rospy.init_node("mycobot_services") rospy.loginfo("start ...") port = rospy.get_param("~port") baud = rospy.get_param("~baud") @@ -43,7 +81,9 @@ def set_angles(req): sp = req.speed if mc: + lock = acquire("/tmp/mycobot_lock") mc.send_angles(angles, sp) + release(lock) return SetAnglesResponse(True) @@ -51,7 +91,9 @@ def set_angles(req): def get_angles(req): """get angles,获取角度""" if mc: + lock = acquire("/tmp/mycobot_lock") angles = mc.get_angles() + release(lock) return GetAnglesResponse(*angles) @@ -68,14 +110,18 @@ def set_coords(req): mod = req.model if mc: + lock = acquire("/tmp/mycobot_lock") mc.send_coords(coords, sp, mod) + release(lock) return SetCoordsResponse(True) def get_coords(req): if mc: + lock = acquire("/tmp/mycobot_lock") coords = mc.get_coords() + release(lock) return GetCoordsResponse(*coords) @@ -83,23 +129,26 @@ def switch_status(req): """Gripper switch status""" """夹爪开关状态""" if mc: + lock = acquire("/tmp/mycobot_lock") if req.Status: mc.set_gripper_state(0, 80) else: mc.set_gripper_state(1, 80) + release(lock) return GripperStatusResponse(True) def toggle_pump(req): if mc: + lock = acquire("/tmp/mycobot_lock") if req.Status: mc.set_basic_output(req.Pin1, 0) mc.set_basic_output(req.Pin2, 0) else: mc.set_basic_output(req.Pin1, 1) mc.set_basic_output(req.Pin2, 1) - + release(lock) return PumpStatusResponse(True) @@ -107,12 +156,12 @@ robot_msg = """ MyCobot Status -------------------------------- Joint Limit: - joint 1: -160 ~ +160 - joint 2: -90 ~ +90 + joint 1: -160 ~ +170 + joint 2: -85 ~ +90 joint 3: -180 ~ +45 joint 4: -160 ~ +160 joint 5: -100 ~ +100 - joint 6: -180 ~ +180 + joint 6: -∞ ~ +∞ Connect Status: %s @@ -131,11 +180,15 @@ def output_robot_message(): atom_version = "unknown" if mc: + lock = acquire("/tmp/mycobot_lock") cn = mc.is_controller_connected() + release(lock) if cn == 1: connect_status = True time.sleep(0.1) + lock = acquire("/tmp/mycobot_lock") si = mc.is_all_servo_enable() + release(lock) if si == 1: servo_infomation = "all connected" diff --git a/mecharm/mecharm_pi/scripts/simple_gui.py b/mecharm/mecharm_pi/scripts/simple_gui.py index 67784ec..c7e76cf 100644 --- a/mecharm/mecharm_pi/scripts/simple_gui.py +++ b/mecharm/mecharm_pi/scripts/simple_gui.py @@ -1,6 +1,7 @@ -#!/usr/bin/env python +#!/usr/bin/env python3 # -*- coding: utf-8 -*- -import Tkinter as tk +# import Tkinter as tk # python2 +import tkinter as tk from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus import rospy import time @@ -33,7 +34,7 @@ class Window: # 计算 Tk 根窗口的 x 和 y 坐标 x = (self.ws / 2) - 190 y = (self.hs / 2) - 250 - self.win.geometry("430x400+{}+{}".format(x, y)) + self.win.geometry("430x400+{}+{}".format(int(x), int(y))) # layout,布局 self.set_layout() # input section,输入部分 diff --git a/mecharm/mecharm_pi/scripts/teleop_keyboard.py b/mecharm/mecharm_pi/scripts/teleop_keyboard.py index 3d2b971..6cfa0f3 100644 --- a/mecharm/mecharm_pi/scripts/teleop_keyboard.py +++ b/mecharm/mecharm_pi/scripts/teleop_keyboard.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python +#!/usr/bin/env python3 # -*- coding:utf-8 -*- from __future__ import print_function from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus @@ -84,7 +84,7 @@ def teleop_keyboard(): init_pose = [0, 0, 0, 0, 0, 0, speed] - home_pose = [0, 8, -127, 40, 0, 0, speed] + home_pose = [0, 30, 30, 0, 30, 0, speed] # rsp = set_angles(*init_pose) diff --git a/mycobot_280/mycobot_280pi/scripts/simple_gui.py b/mycobot_280/mycobot_280pi/scripts/simple_gui.py index d2757cb..41f9258 100755 --- a/mycobot_280/mycobot_280pi/scripts/simple_gui.py +++ b/mycobot_280/mycobot_280pi/scripts/simple_gui.py @@ -1,6 +1,7 @@ -#!/usr/bin/env python +#!/usr/bin/env python3 # -*- coding: utf-8 -*- -import Tkinter as tk +# import Tkinter as tk +import tkinter as tk from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus import rospy import time @@ -33,7 +34,7 @@ class Window: # 计算 Tk 根窗口的 x 和 y 坐标 x = (self.ws / 2) - 190 y = (self.hs / 2) - 250 - self.win.geometry("430x400+{}+{}".format(x, y)) + self.win.geometry("430x400+{}+{}".format(int(x), int(y))) # layout,布局 self.set_layout() # input section,输入部分 diff --git a/mycobot_280/mycobot_280pi/scripts/teleop_keyboard.py b/mycobot_280/mycobot_280pi/scripts/teleop_keyboard.py index e5ee716..110f8a4 100755 --- a/mycobot_280/mycobot_280pi/scripts/teleop_keyboard.py +++ b/mycobot_280/mycobot_280pi/scripts/teleop_keyboard.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python +#!/usr/bin/env python3 # encoding=utf-8 from __future__ import print_function from mycobot_communication.srv import GetCoords, SetCoords, GetAngles, SetAngles, GripperStatus diff --git a/mycobot_communication/scripts/mycobot_services.py b/mycobot_communication/scripts/mycobot_services.py index 0f105a8..cbf1b75 100755 --- a/mycobot_communication/scripts/mycobot_services.py +++ b/mycobot_communication/scripts/mycobot_services.py @@ -1,13 +1,51 @@ #!/usr/bin/env python2 -# -*- coding: utf-8 -* +# -*- coding: utf-8 -*- import time import rospy +import os +import fcntl from mycobot_communication.srv import * from pymycobot.mycobot import MyCobot mc = None +# Avoid serial port conflicts and need to be locked +def acquire(lock_file): + open_mode = os.O_RDWR | os.O_CREAT | os.O_TRUNC + fd = os.open(lock_file, open_mode) + + pid = os.getpid() + lock_file_fd = None + + timeout = 50.0 + start_time = current_time = time.time() + while current_time < start_time + timeout: + try: + # The LOCK_EX means that only one process can hold the lock + # The LOCK_NB means that the fcntl.flock() is not blocking + # and we are able to implement termination of while loop, + # when timeout is reached. + fcntl.flock(fd, fcntl.LOCK_EX | fcntl.LOCK_NB) + except (IOError, OSError): + pass + else: + lock_file_fd = fd + break + # print('pid waiting for lock:%d'% pid) + time.sleep(1.0) + current_time = time.time() + if lock_file_fd is None: + os.close(fd) + return lock_file_fd + + +def release(lock_file_fd): + # Do not remove the lockfile: + fcntl.flock(lock_file_fd, fcntl.LOCK_UN) + os.close(lock_file_fd) + return None + def create_handle(): global mc @@ -41,9 +79,11 @@ def set_angles(req): req.joint_6, ] sp = req.speed - print('angles1:',angles) + if mc: + lock = acquire("/tmp/mycobot_lock") mc.send_angles(angles, sp) + release(lock) return SetAnglesResponse(True) @@ -51,8 +91,9 @@ def set_angles(req): def get_angles(req): """get angles,获取角度""" if mc: + lock = acquire("/tmp/mycobot_lock") angles = mc.get_angles() - print('angles2:',angles) + release(lock) return GetAnglesResponse(*angles) @@ -69,15 +110,18 @@ def set_coords(req): mod = req.model if mc: + lock = acquire("/tmp/mycobot_lock") mc.send_coords(coords, sp, mod) + release(lock) return SetCoordsResponse(True) def get_coords(req): if mc: + lock = acquire("/tmp/mycobot_lock") coords = mc.get_coords() - print('coords:',coords) + release(lock) return GetCoordsResponse(*coords) @@ -85,23 +129,26 @@ def switch_status(req): """Gripper switch status""" """夹爪开关状态""" if mc: + lock = acquire("/tmp/mycobot_lock") if req.Status: mc.set_gripper_state(0, 80) else: mc.set_gripper_state(1, 80) + release(lock) return GripperStatusResponse(True) def toggle_pump(req): if mc: + lock = acquire("/tmp/mycobot_lock") if req.Status: mc.set_basic_output(req.Pin1, 0) mc.set_basic_output(req.Pin2, 0) else: mc.set_basic_output(req.Pin1, 1) mc.set_basic_output(req.Pin2, 1) - + release(lock) return PumpStatusResponse(True) @@ -133,11 +180,15 @@ def output_robot_message(): atom_version = "unknown" if mc: + lock = acquire("/tmp/mycobot_lock") cn = mc.is_controller_connected() + release(lock) if cn == 1: connect_status = True time.sleep(0.1) + lock = acquire("/tmp/mycobot_lock") si = mc.is_all_servo_enable() + release(lock) if si == 1: servo_infomation = "all connected" From e11e0ac141fbd37b98011629875378f938e29424 Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Thu, 8 Dec 2022 11:21:56 +0800 Subject: [PATCH 09/12] update aikit280 m5 --- mycobot_280/mycobot_280/config/mycobot.rviz | 9 +++++++++ .../ai_mycobot_280/scripts/combine_detect_obj_color.py | 4 ++-- .../scripts/combine_detect_obj_img_folder_opt.py | 4 ++-- 3 files changed, 13 insertions(+), 4 deletions(-) diff --git a/mycobot_280/mycobot_280/config/mycobot.rviz b/mycobot_280/mycobot_280/config/mycobot.rviz index 68ab389..6fe1018 100644 --- a/mycobot_280/mycobot_280/config/mycobot.rviz +++ b/mycobot_280/mycobot_280/config/mycobot.rviz @@ -8,6 +8,7 @@ Panels: - /Status1 - /RobotModel1 - /TF1 + - /Marker1 Splitter Ratio: 0.5 Tree Height: 607 - Class: rviz/Selection @@ -147,6 +148,14 @@ Visualization Manager: {} Update Interval: 0 Value: true + - Class: rviz/Marker + Enabled: true + Marker Topic: /cube + Name: Marker + Namespaces: + {} + Queue Size: 100 + Value: true Enabled: true Global Options: Background Color: 48; 48; 48 diff --git a/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_color.py b/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_color.py index f29c73f..389a29a 100755 --- a/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_color.py +++ b/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_color.py @@ -51,8 +51,8 @@ class Object_detect(Movement): # self.Pin = [20, 21] self.Pin = [2, 5] - for i in self.move_coords: - i[2] -= 20 + # for i in self.move_coords: + # i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: import RPi.GPIO as GPIO GPIO.setwarnings(False) diff --git a/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py index ee5ca7d..de5ca4a 100644 --- a/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py +++ b/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py @@ -61,8 +61,8 @@ class Object_detect(Movement): self.Pin = [2, 5] elif "dev" in self.robot_wio: self.Pin = [2, 5] - for i in self.move_coords: - i[2] -= 20 + # for i in self.move_coords: + # i[2] -= 20 elif "dev" in self.robot_raspi or "dev" in self.robot_jes: import RPi.GPIO as GPIO GPIO.setwarnings(False) From db466ddafba0cd81a652e5a8d1be71b27709411a Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Thu, 8 Dec 2022 11:30:41 +0800 Subject: [PATCH 10/12] add aikit280 one touch start --- .../ai_mycobot_280/scripts/ai_windows.py | 191 ++++++++++++++++++ 1 file changed, 191 insertions(+) create mode 100644 mycobot_ai/ai_mycobot_280/scripts/ai_windows.py diff --git a/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py b/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py new file mode 100644 index 0000000..09ad47f --- /dev/null +++ b/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py @@ -0,0 +1,191 @@ +#!/usr/bin/env python3 +# encoding:utf-8 + +from tkinter import ttk +from tkinter import * +import os,sys +import time +import subprocess + +import threading +from multiprocessing import Process + + +class Application(object): + def __init__(self): + self.win = Tk() + # 窗口置顶 + self.win.wm_attributes('-topmost', 1) + self.ros = False + # 运行的文件 + self.run_py = "" + # 判断通信口并给权限 + try: + self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1] + self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1] + self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1] + self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1] + if "dev" in self.robot_wio: + self.set_file(self.robot_wio) + elif "dev" in self.robot_m5: + self.set_file(self.robot_m5) + elif "dev" in self.robot_raspi: + self.change_file(self.robot_raspi) + elif "dev" in self.robot_jes: + self.change_file(self.robot_jes) + except Exception as e: + pass + + # 设置标题 + self.win.title("aikit启动工具") + self.win.geometry( + "600x400+100+100") # 290 160为窗口大小，+10 +10 定义窗口弹出时的默认展示位置 + # 打开ros按钮 + self.btn = Button(self.win, text="open ROS", command=self.open_ros) + self.btn.grid(row=0) + + self.chanse_code = Label(self.win, text="选择程序:", width=10) + self.chanse_code.grid(row=1) + + self.myComboList = [u"颜色识别", u"物体识别", u"二维码识别"] + self.myCombox = ttk.Combobox(self.win, values=self.myComboList) + self.myCombox.grid(row=1, column=1) + + self.add_btn = Button(self.win, text="添加新的物体图像", command=self.add_img) + self.add_btn.grid(row=1, column=2) + + self.tips = "1、首先打开ros,大概需要等待5s\n2、选择所要运行的程序点击运行即可,开启大概需要10秒,可以通过查看终端查看开启情况。\n\n添加新的图像：\n1、点击按钮，等待开启摄像头\n2、选中图像框，按z键拍照\n3、使用鼠标框出需要识别的图像区域\n4、按Enter键提取图像\n5、根据终端提示，输入数字(1~4)保存到相对应图像的文件夹，按下Enter键即可保存至对应文件夹。" + + self.btn = Button(self.win, text="运行", command=self.start_run) + self.btn.grid(row=5) + + self.close = Button(self.win, text="close", command=self.close_py) + self.close.grid(row=5, column=1) + + self.t2 = None + self.log_data = Text(self.win, width=74, height=20) + self.log_data.grid(row=16, column=0, columnspan=10) + self.log_data.insert(END, self.tips) + + # self.open_ros() + self.win.protocol('WM_DELETE_WINDOW', self.close_rviz) + + def close_rviz(self): + os.system( + "ps -ef | grep -E mycobot.rviz | grep -v 'grep' | awk '{print $2}' | xargs kill -9") + sys.exit(0) + + def set_file(self,port): + self.command = ''.format( + port) + # 根据通信口修改ros启动文件 + os.system( + "sed -i '2c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/launch/vision_wio.launch" + .format(self.command)) + + def change_file(self, port): + command1 = ''.format(port) + command2 = ''.format(1000000) + # 根据通信口修改ros启动文件 + os.system( + "sed -i '2c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch".format(command1)) + os.system( + "sed -i '3c {}' ~/catkin_ws/src/mycobot_ros/mycobot_ai/launch/vision.launch".format(command2)) + + def start_run(self): + try: + print(u"开始运行") + one = self.myCombox.get() + if one == u"颜色识别": + self.run_py = "combine_detect_obj_color.py" + t2 = threading.Thread(target=self.open_py1) + t2.setDaemon(True) + t2.start() + elif one == u"物体识别": + self.run_py = "combine_detect_obj_img_folder_opt.py" + t3 = threading.Thread(target=self.open_py) + t3.setDaemon(True) + t3.start() + elif one == u"二维码识别": + self.run_py = "detect_encode.py" + t3 = threading.Thread(target=self.open_py2) + t3.setDaemon(True) + t3.start() + except Exception as e: + self.tips = str(e) + self.log_data.insert(END, self.tips) + + def open_py(self): + os.system( + "cd /home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280 && python scripts/combine_detect_obj_img_folder_opt.py" + ) + + def open_py1(self): + os.system( + "python ~/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_color.py" + ) + + def open_py2(self): + os.system( + "python ~/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/scripts/detect_encode.py" + ) + + def add_img(self): + os.system( + "python ~/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/scripts/add_img.py" + ) + + def open_ros(self): + if self.ros: + print("ros is opened") + return + # t1 = threading.Thread(target=self.ross) + # t1.setDaemon(True) + # t1.start() + self.ross() + self.ros = True + + def ross(self): + # os.system( + # "roslaunch ~/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/launch/vision_wio.launch" + # ) + p = subprocess.Popen(["roslaunch", "/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_mycobot_280/launch/vision_wio.launch"],shell=False, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + def close_py(self): + t1 = threading.Thread(target=self.close_p) + t1.setDaemon(True) + t1.start() + + def close_p(self): + # 关闭ai程序 + os.system("ps -ef | grep -E " + self.run_py + + " | grep -v 'grep' | awk '{print $2}' | xargs kill -9") + + def get_current_time(self): + # 日志时间 + """Get current time with format.""" + current_time = time.strftime("%Y-%m-%d %H:%M:%S", + time.localtime(time.time())) + return current_time + + def write_log_to_Text(self, logmsg): + # 设置日志函数 + global LOG_NUM + current_time = self.get_current_time() + logmsg_in = str(current_time) + " " + str(logmsg) + "\n" # 换行 + + if LOG_NUM <= 18: + self.log_data_Text.insert(END, logmsg_in) + LOG_NUM += len(logmsg_in.split("\n")) + # print(LOG_NUM) + else: + self.log_data_Text.insert(END, logmsg_in) + self.log_data_Text.yview("end") + + def run(self): + self.win.mainloop() + + +if __name__ == "__main__": + mc = Application() + mc.run() From cdb76b5ce903b545a1e060c0febccbfbc0bb4f11 Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Thu, 8 Dec 2022 12:41:01 +0800 Subject: [PATCH 11/12] update ai_window.py font --- mycobot_ai/ai_mycobot_280/scripts/ai_windows.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py b/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py index 09ad47f..a0ebfe9 100644 --- a/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py +++ b/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py @@ -39,31 +39,31 @@ class Application(object): # 设置标题 self.win.title("aikit启动工具") self.win.geometry( - "600x400+100+100") # 290 160为窗口大小，+10 +10 定义窗口弹出时的默认展示位置 + "800x600+100+100") # 290 160为窗口大小，+10 +10 定义窗口弹出时的默认展示位置 # 打开ros按钮 - self.btn = Button(self.win, text="open ROS", command=self.open_ros) + self.btn = Button(self.win, text="open ROS", font=("Helvetica","13"), command=self.open_ros) self.btn.grid(row=0) - self.chanse_code = Label(self.win, text="选择程序:", width=10) + self.chanse_code = Label(self.win, text="选择程序:", font=("Helvetica","13"), width=10) self.chanse_code.grid(row=1) self.myComboList = [u"颜色识别", u"物体识别", u"二维码识别"] - self.myCombox = ttk.Combobox(self.win, values=self.myComboList) + self.myCombox = ttk.Combobox(self.win, font=("Helvetica","13"), values=self.myComboList) self.myCombox.grid(row=1, column=1) - self.add_btn = Button(self.win, text="添加新的物体图像", command=self.add_img) + self.add_btn = Button(self.win, text="添加新的物体图像", font=("Helvetica","13"), command=self.add_img) self.add_btn.grid(row=1, column=2) self.tips = "1、首先打开ros,大概需要等待5s\n2、选择所要运行的程序点击运行即可,开启大概需要10秒,可以通过查看终端查看开启情况。\n\n添加新的图像：\n1、点击按钮，等待开启摄像头\n2、选中图像框，按z键拍照\n3、使用鼠标框出需要识别的图像区域\n4、按Enter键提取图像\n5、根据终端提示，输入数字(1~4)保存到相对应图像的文件夹，按下Enter键即可保存至对应文件夹。" - self.btn = Button(self.win, text="运行", command=self.start_run) + self.btn = Button(self.win, text="运行", font=("Helvetica","13"), command=self.start_run) self.btn.grid(row=5) - self.close = Button(self.win, text="close", command=self.close_py) + self.close = Button(self.win, text="close", font=("Helvetica","13"), command=self.close_py) self.close.grid(row=5, column=1) self.t2 = None - self.log_data = Text(self.win, width=74, height=20) + self.log_data = Text(self.win, width=74, height=20, font=("Helvetica","13")) self.log_data.grid(row=16, column=0, columnspan=10) self.log_data.insert(END, self.tips) From 4688aab02be73f38b76d6d95fac550b32014213d Mon Sep 17 00:00:00 2001 From: wangWking <842749351@qq.com> Date: Mon, 12 Dec 2022 10:48:20 +0800 Subject: [PATCH 12/12] update chmod +x --- mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py | 0 .../ai_mycobot_280/scripts/advance_detect_obj_img_folder.py | 0 mycobot_ai/ai_mycobot_280/scripts/ai_windows.py | 0 .../ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py | 0 mycobot_ai/ai_mycobot_280/scripts/detect_obj_img_folder_opt.py | 0 5 files changed, 0 insertions(+), 0 deletions(-) mode change 100644 => 100755 mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py mode change 100644 => 100755 mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py mode change 100644 => 100755 mycobot_ai/ai_mycobot_280/scripts/ai_windows.py mode change 100644 => 100755 mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py mode change 100644 => 100755 mycobot_ai/ai_mycobot_280/scripts/detect_obj_img_folder_opt.py diff --git a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_color.py old mode 100644 new mode 100755 diff --git a/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py b/mycobot_ai/ai_mycobot_280/scripts/advance_detect_obj_img_folder.py old mode 100644 new mode 100755 diff --git a/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py b/mycobot_ai/ai_mycobot_280/scripts/ai_windows.py old mode 100644 new mode 100755 diff --git a/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/ai_mycobot_280/scripts/combine_detect_obj_img_folder_opt.py old mode 100644 new mode 100755 diff --git a/mycobot_ai/ai_mycobot_280/scripts/detect_obj_img_folder_opt.py b/mycobot_ai/ai_mycobot_280/scripts/detect_obj_img_folder_opt.py old mode 100644 new mode 100755