mirror of
https://github.com/elephantrobotics/mycobot_ros.git
synced 2026-07-05 19:47:04 +00:00
update mycobot_communication/scripts/mycobot_services.py
This commit is contained in:
weijian
parent
67b57bb96e
commit
282ecb34dd
6 changed files with 55 additions and 2006 deletions
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@ -1,164 +0,0 @@
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# ecoding=utf-8
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import cv2
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import numpy as np
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from imutils import contours
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import math
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'''HSV中的颜色空间
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https://blog.csdn.net/wsp_1138886114/article/details/80660014
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'''
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color_dist = {'red': {'Lower': np.array([0, 120, 120]), 'Upper': np.array([6, 255, 255])},
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# 'blue': {'Lower': np.array([100, 80, 46]), 'Upper': np.array([124, 255, 255])},
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# 'blue':{'Lower': np.array([100,43,46]),'Upper': np.array([124,255,255])},
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'blue':{'Lower': np.array([100,43,46]),'Upper': np.array([124,255,255])},
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"cyan": {'Lower': np.array([78, 43, 46]),'Upper': np.array([99, 255, 255])},
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'green': {'Lower': np.array([35, 43, 35]), 'Upper': np.array([90, 255, 255])},
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'yellow': {"Lower": np.array([22, 93, 0]), "Upper": np.array([45, 255, 255])},
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# 'orange': {"Lower": np.array([0, 100, 45]), "Upper":np.array([255, 250, 255])},
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'orange': {"Lower": np.array([11, 43, 46]), "Upper":np.array([25, 255, 255])},
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}
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cap = cv2.VideoCapture(0)
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# cap = cv2.VideoCapture("src/test_1_2.mp4")
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cap.set(3,420)
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cap.set(4,360)
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cv2.namedWindow('camera', cv2.WINDOW_AUTOSIZE)
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# 内核
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kernel = np.ones((5, 5), np.uint8)
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while cap.isOpened():
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ret, frame = cap.read()
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if ret:
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if frame is not None:
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gs_frame = cv2.GaussianBlur(frame, (5, 5), 0)# 高斯模糊
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hsv = cv2.cvtColor(gs_frame, cv2.COLOR_BGR2HSV) # 转化成HSV图像
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erode_hsv = cv2.erode(hsv, None, iterations=2) # 腐蚀 作用是粗的变细
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for _color in color_dist:
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_font_x_pos = 0
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_font_y_pos = 0
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## 颜色阈值识别
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inRange_hsv = cv2.inRange(erode_hsv, color_dist[_color]['Lower'], color_dist[_color]['Upper'])
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# 膨胀操作
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dilation = cv2.dilate(inRange_hsv, kernel, iterations=1)
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# 闭操作
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closing = cv2.morphologyEx(dilation, cv2.MORPH_CLOSE, kernel)
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# 边缘检测
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edges = cv2.Canny(closing, 10, 20)
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# 检测物体边框
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cnts, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
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# 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
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if len(cnts) > 0:
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for cnt in cnts:
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if cv2.contourArea(cnt) >1500:
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peri = cv2.arcLength(cnt,True)
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#print(peri)
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# 用于获得轮廓的近似值，使用cv2.drawCountors进行画图操作 ，
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# 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
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'''
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cv2.approxPolyDP
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@:param
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cnt:
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epsilon :算法参数
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True：表示是否闭合
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'''
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approx = cv2.approxPolyDP(cnt,0.02*peri,True)
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# print(len(approx))
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# 提取拐点
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'''
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返回列表元素，列表中的元素代表一个边沿信息。
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'''
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objCor = len(approx)
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if objCor ==3:
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'''https://blog.51cto.com/hiszm/5201991'''
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objectType = "Triangle"
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mm = cv2.moments(cnt)
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cx = int(mm['m10']/mm['m00'])
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cy = int(mm['m01']/mm['m00'])
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_font_x_pos = cx
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_font_y_pos = cy
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cv2.circle(frame,(cx,cy),3,(0,0,255),-1)
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cv2.drawContours(frame, [cnt], 0, (0, 0, 255), 3)
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print("三角形的坐标",cx,cy)
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# 检测出是矩形
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elif objCor == 4:
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# 可旋转矩形，即最小的外包矩形
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rect= cv2.minAreaRect(cnt)
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'''
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@:param
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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）。
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分别对应于返回值：(rect[0][0], rect[0][1]), (rect[1][0], rect[1][1]), rect[2]
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'''
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# 中心点坐标
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pos_x = int(rect[0][0])
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pos_y = int(rect[0][1])
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#print("position",pos_x,pos_y)
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# 旋转角度
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theta = np.round(cv2.minAreaRect(cnt)[2],2)
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box = cv2.boxPoints(rect)
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box = np.int0(box)
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print("物体的坐标为",(pos_x,pos_y),"旋转角度为",theta)
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# 判断长方形还是正方形
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_font_x_pos = box[0][0]
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_font_y_pos = box[0][1]
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_W = math.sqrt(math.pow((box[0][0] - box[1][0]), 2) + math.pow((box[0][1] - box[1][1]), 2))
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_H = math.sqrt(math.pow((box[0][0] - box[3][0]), 2) + math.pow((box[0][1] - box[3][1]), 2))
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# 长宽比
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aspRatio = _W/float(_H)
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if aspRatio >0.98 and aspRatio <1.03:
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objectType= "Square"#正方形
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else:
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objectType="Rectangle"#长方形
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_pos = (pos_x,pos_y)
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cv2.circle(frame,_pos,1,(0,0,255),2)#绘制中心点
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#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) )
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cv2.drawContours(frame,[box],0,(0,0,255),2)
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# 圆形
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elif objCor>4:
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objectType= "Circles"
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'''
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void minEnclosingCircle(InputArray points, Point2f& center, float& radius)
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@:param
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points：输入信息，可以为包含点的容器(vector)或是Mat。
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center：包覆圆形的圆心。
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radius：包覆圆形的半径。
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'''
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(x,y),radius = cv2.minEnclosingCircle(cnt)
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center = (int(x),int(y))
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radius = int(radius)
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_font_x_pos = center[0]
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_font_y_pos = center[1]
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print("物体的圆心为:",(_font_x_pos, _font_y_pos),"半径为",radius)
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cv2.circle(frame,center,1,(255,0,0),2)#绘制中心点
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cv2.circle(frame,center,radius,(255,0,0),2)
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else:
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objectType="None"
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# objectType 物体形状
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print("颜色类别：",_color)
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cv2.putText(frame, str(_color + objectType), (int(_font_x_pos),int(_font_y_pos)), cv2.FONT_HERSHEY_COMPLEX_SMALL,1, (0, 255, 0) )
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cv2.imshow('camera', frame)
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# 存储识别结果视频
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# out.write(frame)
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cv2.waitKey(1)
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if cv2.waitKey(10) & 0xFF == 27:
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break
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else:
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print("无画面")
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break
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else:
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print("无法读取摄像头！")
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break
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cap.release()
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# out.release()
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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@ -1,480 +0,0 @@
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# encoding:utf-8
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#!/usr/bin/env python2
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import cv2
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import numpy as np
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import time
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import os,sys
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import rospy
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from visualization_msgs.msg import Marker
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from pymycobot.mycobot import MyCobot
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from moving_utils import Movement
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IS_CV_4 = cv2.__version__[0] == '4'
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__version__ = "1.0"
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# Adaptive seeed
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class Object_detect(Movement):
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def __init__(self, camera_x = 155, camera_y = 10):
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# inherit the parent class
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super(Object_detect, self).__init__()
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# get path of file
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dir_path = os.path.dirname(__file__)
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self.mc = None
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# 移动角度
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self.move_angles = [
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[-7.11, -6.94, -55.01, -24.16, 0, -15], # init the point
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[18.8, -7.91, -54.49, -23.02, -0.79, -14.76], # point to grab
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]
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# 移动坐标
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self.move_coords = [
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[132.2, -136.9, 200.8, -178.24, -3.72, -107.17], # above the red bucket
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[238.8, -124.1, 204.3, -169.69, -5.52, -96.52], # green
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[115.8, 177.3, 210.6, 178.06, -0.92, -6.11], # blue
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[-6.9, 173.2, 201.5, 179.93, 0.63, 33.83], # gray
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]
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# which robot: USB* is m5; ACM* is wio; AMA* is raspi
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self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
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self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
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self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
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self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
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self.raspi = False
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if "dev" in self.robot_m5:
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self.Pin = [2, 5]
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elif "dev" in self.robot_wio:
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# self.Pin = [20, 21]
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self.Pin = [2, 5]
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for i in self.move_coords:
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i[2] -= 20
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elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
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import RPi.GPIO as GPIO
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GPIO.setwarnings(False)
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self.GPIO = GPIO
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GPIO.setmode(GPIO.BCM)
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GPIO.setup(20, GPIO.OUT)
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GPIO.setup(21, GPIO.OUT)
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GPIO.output(20, 1)
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GPIO.output(21, 1)
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self.raspi = True
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if self.raspi:
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self.gpio_status(False)
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# choose place to set cube
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self.color = 0
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# parameters to calculate camera clipping parameters
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self.x1 = self.x2 = self.y1 = self.y2 = 0
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# set cache of real coord
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self.cache_x = self.cache_y = 0
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# set color HSV
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self.HSV = {
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"yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])],
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"red": [np.array([0, 43, 46]), np.array([8, 255, 255])],
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"green": [np.array([35, 43, 35]), np.array([90, 255, 255])], # [77, 255, 255]
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"blue": [np.array([100, 43, 46]), np.array([124, 255, 255])],
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"cyan": [np.array([89, 43, 46]), np.array([99, 255, 255])], # np.array([78, 43, 46]), np.array([99, 255, 255])
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}
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# use to calculate coord between cube and mycobot
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self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
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# The coordinates of the grab center point relative to the mycobot
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self.camera_x, self.camera_y = camera_x, camera_y
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# The coordinates of the cube relative to the mycobot
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self.c_x, self.c_y = 0, 0
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# The ratio of pixels to actual values
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self.ratio = 0
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# Get ArUco marker dict that can be detected.
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self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
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# Get ArUco marker params.
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self.aruco_params = cv2.aruco.DetectorParameters_create()
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# init a node and a publisher
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rospy.init_node("marker", anonymous=True)
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self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
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# init a Marker
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self.marker = Marker()
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self.marker.header.frame_id = "/joint1"
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self.marker.ns = "cube"
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self.marker.type = self.marker.CUBE
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self.marker.action = self.marker.ADD
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self.marker.scale.x = 0.04
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self.marker.scale.y = 0.04
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self.marker.scale.z = 0.04
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self.marker.color.a = 1.0
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self.marker.color.g = 1.0
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self.marker.color.r = 1.0
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# marker position initial
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self.marker.pose.position.x = 0
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self.marker.pose.position.y = 0
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self.marker.pose.position.z = 0.03
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self.marker.pose.orientation.x = 0
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self.marker.pose.orientation.y = 0
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self.marker.pose.orientation.z = 0
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self.marker.pose.orientation.w = 1.0
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# publish marker
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def pub_marker(self, x, y, z=0.03):
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self.marker.header.stamp = rospy.Time.now()
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self.marker.pose.position.x = x
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self.marker.pose.position.y = y
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self.marker.pose.position.z = z
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self.marker.color.g = self.color
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self.pub.publish(self.marker)
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def gpio_status(self, flag):
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if flag:
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# self.GPIO.output(20, 0)
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self.GPIO.output(21, 0)
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else:
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# self.GPIO.output(20, 1)
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self.GPIO.output(21, 1)
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# 开启吸泵 m5
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def pump_on(self):
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# 让2号位工作
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# self.mc.set_basic_output(2, 0)
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# 让5号位工作
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self.mc.set_basic_output(5, 0)
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# 停止吸泵 m5
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def pump_off(self):
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# 让2号位停止工作
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# self.mc.set_basic_output(2, 1)
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# 让5号位停止工作
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self.mc.set_basic_output(5, 1)
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# Grasping motion
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def move(self, x, y, color):
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# send Angle to move mycobot
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print (color)
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self.mc.send_angles(self.move_angles[1], 25)
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time.sleep(3)
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# send coordinates to move mycobot
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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
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time.sleep(3)
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# self.mc.send_coords([x, y, 150, 179.87, -3.78, -62.75], 25, 0)
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# time.sleep(3)
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self.mc.send_coords([x, y, 103, 179.87, -3.78, -62.75], 25, 0)
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time.sleep(3)
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# open pump
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if "dev" in self.robot_m5 or "dev" in self.robot_wio:
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self.pump_on()
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elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
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self.gpio_status(True)
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time.sleep(1.5)
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tmp = []
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while True:
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if not tmp:
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tmp = self.mc.get_angles()
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else:
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break
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time.sleep(0.5)
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# print(tmp)
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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]
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time.sleep(2.5)
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self.pub_marker(
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self.move_coords[2][0]/1000.0, self.move_coords[2][1]/1000.0, self.move_coords[2][2]/1000.0)
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self.mc.send_coords(self.move_coords[color], 25, 1)
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self.pub_marker(self.move_coords[color][0]/1000.0, self.move_coords[color]
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[1]/1000.0, self.move_coords[color][2]/1000.0)
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time.sleep(3)
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# close pump
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if "dev" in self.robot_m5 or "dev" in self.robot_wio:
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self.pump_off()
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elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
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self.gpio_status(False)
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time.sleep(4)
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if color == 1:
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self.pub_marker(
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self.move_coords[color][0]/1000.0+0.04, self.move_coords[color][1]/1000.0-0.02)
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elif color == 0:
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self.pub_marker(
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self.move_coords[color][0]/1000.0+0.03, self.move_coords[color][1]/1000.0)
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# self.pub_angles(self.move_angles[0], 20)
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self.mc.send_angles(self.move_angles[0], 25)
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time.sleep(3)
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# decide whether grab cube
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def decide_move(self, x, y, color):
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print(x, y, self.cache_x, self.cache_y)
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# detect the cube status move or run
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if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
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self.cache_x, self.cache_y = x, y
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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)
|
||||
|
|
@ -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()
|
||||
|
|
@ -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()
|
||||
|
|
@ -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()
|
||||
|
|
@ -2,12 +2,51 @@
|
|||
# -*- 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
|
||||
|
|
@ -43,7 +82,9 @@ def set_angles(req):
|
|||
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 +92,9 @@ 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 +111,18 @@ 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)
|
||||
|
||||
|
||||
|
|
@ -85,22 +130,26 @@ 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 +182,15 @@ 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"
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue