mirror of
https://github.com/elephantrobotics/mycobot_ros.git
synced 2026-07-05 19:47:04 +00:00
update
This commit is contained in:
wuchangji
parent
0690b71843
commit
b2199c0710
38 changed files with 1044 additions and 539 deletions
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@ -9,6 +9,7 @@ project(mechArm_270)
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## is used, also find other catkin packages
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find_package(catkin REQUIRED COMPONENTS
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mecharm_pi
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mecharm
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)
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## System dependencies are found with CMake's conventions
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27
mycobot_ai/mechArm_270/launch/vision_m5.launch
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27
mycobot_ai/mechArm_270/launch/vision_m5.launch
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@ -0,0 +1,27 @@
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<launch>
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<arg name="port" default="/dev/ttyUSB1" />
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<arg name="baud" default="115200" />
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<arg name="model" default="$(find mycobot_description)/urdf/260_urdf/mypal_260_aikit.urdf"/>
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<arg name="rvizconfig" default="$(find mypalletizer_260)/config/mypal_260.rviz" />
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<!-- <arg name="gui" default="false" /> -->
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<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
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<!-- Combinejoin values to TF -->
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<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
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<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
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</node>
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<!-- mypalletizer-topics -->
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<include file="$(find mypalletizer_communication)/launch/communication_topic.launch">
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<arg name="port" value="$(arg port)" />
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<arg name="baud" value="$(arg baud)" />
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</include>
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<!-- listen and pub the real angles -->
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<node name="real_listener" pkg="mypalletizer_260" type="listen_real_of_topic.py" />
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<!-- Show in Rviz -->
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<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
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</launch>
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@ -2,8 +2,8 @@
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<arg name="port" default="/dev/ttyAMA0" />
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<arg name="baud" default="1000000" />
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<arg name="model" default="$(find mycobot_description)/urdf/mycobot/mycobot_with_vision.urdf"/>
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<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />
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<arg name="model" default="$(find mycobot_description)/urdf/mecharm_pi/mecharm_pi.urdf"/>
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<arg name="rvizconfig" default="$(find mecharm_pi)/config/mecharm_pi.rviz" />
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<!-- <arg name="gui" default="false" /> -->
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<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
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@ -13,14 +13,14 @@
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<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
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</node>
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<!-- mycobot-topics -->
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<include file="$(find mycobot_communication)/launch/communication_topic.launch">
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<!-- mecharm-topics -->
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<include file="$(find mecharm_communication)/launch/communication_topic_pi.launch">
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<arg name="port" value="$(arg port)" />
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<arg name="baud" value="$(arg baud)" />
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</include>
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<!-- listen and pub the real angles -->
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<node name="real_listener" pkg="mycobot_280" type="listen_real_of_topic.py" />
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<node name="real_listener" pkg="mecharm_pi" type="listen_real_of_topic.py" />
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<!-- Show in Rviz -->
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<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
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@ -3,7 +3,7 @@
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<arg name="baud" default="115200" />
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<arg name="model" default="$(find mycobot_description)/urdf/mycobot/mycobot_with_vision.urdf"/>
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<arg name="rvizconfig" default="$(find mycobot_280)/config/mycobot.rviz" />
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<arg name="rvizconfig" default="$(find mypalletizer_260)/config/mycobot.rviz" />
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<!-- <arg name="gui" default="false" /> -->
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<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
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@ -20,7 +20,7 @@
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</include>
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<!-- listen and pub the real angles -->
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<node name="real_listener" pkg="mycobot_280" type="listen_real_of_topic.py" />
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<node name="real_listener" pkg="mypalletizer_260" type="listen_real_of_topic.py" />
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<!-- Show in Rviz -->
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<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
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@ -42,7 +42,8 @@
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<!-- <build_export_depend>message_generation</build_export_depend> -->
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<!-- Use buildtool_depend for build tool packages: -->
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<!-- <buildtool_depend>catkin</buildtool_depend> -->
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<!-- Use exec_depend for packages you need at runtime: -->
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<!-- Use exec_depend for packages you need at runtimeshaodengroscore
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-->
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<!-- <exec_depend>message_runtime</exec_depend> -->
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<!-- Use test_depend for packages you need only for testing: -->
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<!-- <test_depend>gtest</test_depend> -->
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@ -53,6 +54,9 @@
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<build_export_depend>mecharm_pi</build_export_depend>
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<exec_depend>mecharm_pi</exec_depend>
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<build_depend>mecharm</build_depend>
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<build_export_depend>mecharm</build_export_depend>
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<exec_depend>mecharm</exec_depend>
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<!-- The export tag contains other, unspecified, tags -->
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<export>
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BIN
mycobot_ai/mechArm_270/res/blue/goal3.jpeg
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mycobot_ai/mechArm_270/res/blue/goal3.jpeg
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mycobot_ai/mechArm_270/res/blue/goal4.jpeg
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mycobot_ai/mechArm_270/res/blue/goal5.jpeg
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mycobot_ai/mechArm_270/res/blue/goal5.jpeg
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mycobot_ai/mechArm_270/res/blue/goal6.jpeg
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mycobot_ai/mechArm_270/res/blue/goal6.jpeg
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mycobot_ai/mechArm_270/res/blue/goal7.jpeg
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mycobot_ai/mechArm_270/res/blue/goal7.jpeg
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mycobot_ai/mechArm_270/res/blue/goal8.jpeg
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mycobot_ai/mechArm_270/res/blue/goal8.jpeg
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mycobot_ai/mechArm_270/res/gray/goal3.jpeg
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mycobot_ai/mechArm_270/res/gray/goal3.jpeg
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mycobot_ai/mechArm_270/res/gray/goal4.jpeg
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mycobot_ai/mechArm_270/res/gray/goal5.jpeg
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mycobot_ai/mechArm_270/res/gray/goal6.jpeg
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mycobot_ai/mechArm_270/res/gray/goal6.jpeg
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mycobot_ai/mechArm_270/res/gray/goal7.jpeg
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mycobot_ai/mechArm_270/res/gray/goal7.jpeg
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mycobot_ai/mechArm_270/res/gray/goal8.jpeg
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mycobot_ai/mechArm_270/res/gray/goal8.jpeg
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mycobot_ai/mechArm_270/res/green/goal10.jpeg
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mycobot_ai/mechArm_270/res/green/goal10.jpeg
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mycobot_ai/mechArm_270/res/green/goal11.jpeg
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mycobot_ai/mechArm_270/res/green/goal11.jpeg
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mycobot_ai/mechArm_270/res/green/goal5.jpeg
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mycobot_ai/mechArm_270/res/green/goal5.jpeg
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mycobot_ai/mechArm_270/res/green/goal6.jpeg
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mycobot_ai/mechArm_270/res/green/goal6.jpeg
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mycobot_ai/mechArm_270/res/green/goal7.jpeg
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mycobot_ai/mechArm_270/res/green/goal7.jpeg
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mycobot_ai/mechArm_270/res/green/goal8.jpeg
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mycobot_ai/mechArm_270/res/green/goal8.jpeg
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mycobot_ai/mechArm_270/res/green/goal9.jpeg
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mycobot_ai/mechArm_270/res/green/goal9.jpeg
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mycobot_ai/mechArm_270/res/red/goal2.jpeg
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mycobot_ai/mechArm_270/res/red/goal2.jpeg
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mycobot_ai/mechArm_270/res/red/goal3.jpeg
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mycobot_ai/mechArm_270/res/red/goal3.jpeg
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mycobot_ai/mechArm_270/res/red/goal4.jpeg
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mycobot_ai/mechArm_270/res/red/goal4.jpeg
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mycobot_ai/mechArm_270/res/red/goal5.jpeg
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mycobot_ai/mechArm_270/res/red/goal5.jpeg
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mycobot_ai/mechArm_270/res/red/goal6.jpeg
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mycobot_ai/mechArm_270/res/red/goal6.jpeg
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mycobot_ai/mechArm_270/res/red/goal7.jpeg
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mycobot_ai/mechArm_270/res/red/goal7.jpeg
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@ -49,19 +49,19 @@ def take_photo():
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def cut_photo():
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path_red = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/red'
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path_red = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/red'
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for i, j, k in os.walk(path_red):
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file_len_red = len(k)
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path_gray = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/gray'
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path_gray = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/gray'
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for i, j, k in os.walk(path_gray):
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file_len_gray = len(k)
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path_green = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/green'
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path_green = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/green'
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for i, j, k in os.walk(path_green):
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file_len_green = len(k)
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path_blue = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/blue'
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path_blue = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/blue'
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for i, j, k in os.walk(path_blue):
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file_len_blue = len(k)
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print("请截取要识别的部分")
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@ -95,19 +95,19 @@ def cut_photo():
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cv2.imshow('crop', crop)
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# 选择红桶文件夹
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if kw == 'red':
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/red/goal{}.jpeg'.format(str(file_len_red + 1)),crop)
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/red/goal{}.jpeg'.format(str(file_len_red + 1)),crop)
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print('Saved')
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# 选择灰桶文件夹
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elif kw == 'gray':
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/gray/goal{}.jpeg'.format(str(file_len_gray+1)),crop)
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/gray/goal{}.jpeg'.format(str(file_len_gray+1)),crop)
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print('Saved')
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# 选择绿桶文件夹
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elif kw == 'green':
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/green/goal{}.jpeg'.format(str(file_len_green+1)),crop)
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/green/goal{}.jpeg'.format(str(file_len_green+1)),crop)
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print('Saved')
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# 选择蓝桶文件夹
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elif kw == 'blue':
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/res/blue/goal{}.jpeg'.format(str(file_len_blue+1)),crop)
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cv2.imwrite('/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/res/blue/goal{}.jpeg'.format(str(file_len_blue+1)),crop)
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print('Saved')
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# 退出
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444
mycobot_ai/mechArm_270/scripts/detect_obj_img.py → mycobot_ai/mechArm_270/scripts/combine_detect_obj_color.py
Executable file → Normal file
444
mycobot_ai/mechArm_270/scripts/detect_obj_img.py → mycobot_ai/mechArm_270/scripts/combine_detect_obj_color.py
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@ -1,49 +1,50 @@
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# encoding:utf-8
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# -*- coding:utf-8 -*-
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#!/usr/bin/env python2
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from operator import imod
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from tokenize import Pointfloat
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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 json
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import os
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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 PIL import Image
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from threading import Thread
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import tkFileDialog as filedialog
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import Tkinter as tk
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from visualization_msgs.msg import Marker
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from pymycobot.mypalletizer import MyPalletizer
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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" # Adaptive seeed
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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=150, camera_y=-10):
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def __init__(self, camera_x = 160, 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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# declare mypal260
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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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[-1.14, -10.63, -87.8, 9.05, -3.07, 15], # point to grab
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[0, 0, 0, 0], # init the point
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[-29.0, 5.88, -4.92, -76.28], # point to grab
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[17.4, -10.1, -87.27, 5.8, -2.02, 15], # 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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[120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
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# above the yello bucket
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#[208.2, -127.8, 260.9, -157.51, -17.5, -71.18],
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[205.6, -130.5, 263.0, -150.99, -0.07, -107.35],
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[209.7, -18.6, 230.4, -168.48, -9.86, -39.38],
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[196.9, -64.7, 232.6, -166.66, -9.44, -52.47],
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[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
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[141.2, -142.0, 210, -26.8], # above the red bucket
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[234.3, -120, 210, -48.77], # above the green bucket
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[100.9, 159.3, 248.6, -124.27], # above the blue bucket
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[-17.6, 161.6, 238.4, -152.31], # above the gray bucket
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]
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# 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
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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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@ -57,37 +58,35 @@ class Object_detect(Movement):
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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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self.GPIO = 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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self.Pin = [2, 5]
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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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# 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
|
||||
# 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 mypal260
|
||||
self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
|
||||
# The coordinates of the grab center point relative to the mycobot
|
||||
# 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 mycobot
|
||||
# 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
|
||||
|
|
@ -96,11 +95,6 @@ class Object_detect(Movement):
|
|||
# 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)
|
||||
|
|
@ -126,11 +120,7 @@ class Object_detect(Movement):
|
|||
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
|
||||
|
|
@ -139,6 +129,7 @@ class Object_detect(Movement):
|
|||
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)
|
||||
|
|
@ -146,80 +137,69 @@ class Object_detect(Movement):
|
|||
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
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_angles(self.move_angles[1], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
time.sleep(1.5)
|
||||
# send coordinates to move mycobot
|
||||
self.pub_coords([x, y, 165, -178.9, -1.57, -66], 20, 1)
|
||||
time.sleep(1.5)
|
||||
# 根据不同底板机械臂，调整吸泵高度
|
||||
if "dev" in self.robot_m5:
|
||||
# m5 and jetson nano
|
||||
self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
|
||||
elif "dev" in self.robot_wio:
|
||||
h = 0
|
||||
if 165 < x < 180:
|
||||
h = 10
|
||||
elif x > 180:
|
||||
h = 20
|
||||
elif x < 135:
|
||||
h = -20
|
||||
self.pub_coords([x, y, 31.9+h, -178.9, -1, -66], 20, 1)
|
||||
elif "dev" in self.robot_jes:
|
||||
h = 0
|
||||
if x<130:
|
||||
h=15
|
||||
self.pub_coords([x, y, 90-h, -178.9, -1.57, -66], 25, 1)
|
||||
time.sleep(1.5)
|
||||
# open pump
|
||||
if self.raspi:
|
||||
self.gpio_status(True)
|
||||
else:
|
||||
self.pub_pump(True, self.Pin)
|
||||
time.sleep(0.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
# send Angle to move mypal260
|
||||
print(color)
|
||||
self.mc.send_angles(self.move_angles[0], 20)
|
||||
time.sleep(3)
|
||||
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.pub_angles(self.move_angles[1], 20)
|
||||
# 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, 90, 0], 20, 0)
|
||||
time.sleep(1.5)
|
||||
self.pub_marker(
|
||||
self.move_coords[3][0]/1000.0, self.move_coords[3][1]/1000.0, self.move_coords[3][2]/1000.0)
|
||||
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
# open pump
|
||||
if "dev" in self.robot_m5:
|
||||
self.pump_on()
|
||||
elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
|
||||
self.gpio_status(True)
|
||||
time.sleep(1.5)
|
||||
self.pub_marker(
|
||||
self.move_coords[4][0]/1000.0, self.move_coords[4][1]/1000.0, self.move_coords[4][2]/1000.0)
|
||||
print self.move_coords[color]
|
||||
self.pub_coords(self.move_coords[color], 20, 1)
|
||||
|
||||
self.mc.send_angle(2, 0, 20)
|
||||
time.sleep(0.3)
|
||||
self.mc.send_angle(3, -15, 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(2)
|
||||
time.sleep(3)
|
||||
|
||||
# close pump
|
||||
if self.raspi:
|
||||
if "dev" in self.robot_m5:
|
||||
self.pump_off()
|
||||
elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
|
||||
self.gpio_status(False)
|
||||
else:
|
||||
self.pub_pump(False, self.Pin)
|
||||
time.sleep(1)
|
||||
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.pub_angles(self.move_angles[0], 20)
|
||||
time.sleep(3)
|
||||
|
||||
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
|
||||
|
|
@ -229,43 +209,23 @@ class Object_detect(Movement):
|
|||
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
|
||||
if "dev" in self.robot_wio:
|
||||
if (y < -30 and x > 140) or (x > 150 and y < -10):
|
||||
x -= 10
|
||||
y += 10
|
||||
elif y > -10:
|
||||
y += 10
|
||||
elif x > 170:
|
||||
x -= 10
|
||||
y += 10
|
||||
elif "dev" in self.robot_m5:
|
||||
y += 10
|
||||
x -= 15
|
||||
if y < -20:
|
||||
y += 5
|
||||
# print x,y
|
||||
elif "dev" in self.robot_jes:
|
||||
if y<0:
|
||||
x+=5
|
||||
y+=3
|
||||
y+=10
|
||||
print x,y
|
||||
self.move(x, y, color)
|
||||
|
||||
# init mycobot
|
||||
# init mypal260
|
||||
def run(self):
|
||||
if "dev" in self.robot_m5:
|
||||
self.mc = MyPalletizer(self.robot_m5, 115200)
|
||||
elif "dev" in self.robot_raspi:
|
||||
self.mc = MyPalletizer(self.robot_raspi, 1000000)
|
||||
if not self.raspi:
|
||||
self.pub_pump(False, self.Pin)
|
||||
for _ in range(5):
|
||||
self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20)
|
||||
print(_)
|
||||
time.sleep(0.5)
|
||||
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(
|
||||
cv2.rectangle(
|
||||
img,
|
||||
(x - 20, y - 20),
|
||||
(x + 20, y + 20),
|
||||
|
|
@ -313,13 +273,13 @@ class Object_detect(Movement):
|
|||
self.y2 = int(y2)
|
||||
print(self.x1, self.y1, self.x2, self.y2)
|
||||
|
||||
# set parameters to calculate the coords between cube and mycobot
|
||||
# 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 mycobot
|
||||
# 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)
|
||||
|
||||
|
|
@ -328,7 +288,6 @@ class Object_detect(Movement):
|
|||
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
|
||||
|
|
@ -341,160 +300,88 @@ class Object_detect(Movement):
|
|||
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
|
||||
# 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])
|
||||
|
||||
def obj_detect(self, img, goal):
|
||||
# rows, cols = frame.shape[:-1]
|
||||
# Resize image and swap BGR to RGB.
|
||||
# blob = cv2.dnn.blobFromImage(
|
||||
# frame,
|
||||
# size=(300, 300),
|
||||
# mean=(0, 0, 0),
|
||||
# swapRB=True,
|
||||
# crop=False,
|
||||
# )
|
||||
# transfrom the img to model of gray
|
||||
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
|
||||
# print("hsv",hsv)
|
||||
|
||||
# Detecting.
|
||||
# self.net.setInput(blob)
|
||||
# out = self.net.forward()
|
||||
# x, y = 0, 0
|
||||
# wipe off all color expect color in range
|
||||
mask = cv2.inRange(hsv, item[0], item[1])
|
||||
|
||||
# Processing result.
|
||||
# for detection in out[0, 0, :, :]:
|
||||
# score = float(detection[2])
|
||||
# if score > 0.3:
|
||||
# class_id = detection[1]
|
||||
# left = detection[3] * cols
|
||||
# top = detection[4] * rows
|
||||
# right = detection[5] * cols
|
||||
# bottom = detection[6] * rows
|
||||
# if abs(right + bottom - left - top) > 380:
|
||||
# continue
|
||||
# x, y = (left + right) / 2.0, (top + bottom) / 2.0
|
||||
# cv2.rectangle(
|
||||
# frame,
|
||||
# (int(left), int(top)),
|
||||
# (int(right), int(bottom)),
|
||||
# (0, 230, 0),
|
||||
# thickness=2,
|
||||
# )
|
||||
# cv2.putText(
|
||||
# frame,
|
||||
# "{}: {}%".format(self.id_class_name(class_id),round(score * 100, 2)),
|
||||
# (int(left), int(top) - 10),
|
||||
# cv2.FONT_HERSHEY_COMPLEX_SMALL,
|
||||
# 1,
|
||||
# (243, 0, 0),
|
||||
# 2,
|
||||
# )
|
||||
i = 0
|
||||
MIN_MATCH_COUNT = 10
|
||||
sift = cv2.xfeatures2d.SIFT_create()
|
||||
# a etching operation on a picture to remove edge roughness
|
||||
erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2)
|
||||
|
||||
# find the keypoints and descriptors with SIFT
|
||||
kp = []
|
||||
des = []
|
||||
# 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)
|
||||
|
||||
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)
|
||||
# adds pixels to the image
|
||||
target = cv2.bitwise_and(img, img, mask=dilation)
|
||||
|
||||
# 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)
|
||||
# the filtered image is transformed into a binary image and placed in binary
|
||||
ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY)
|
||||
|
||||
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)
|
||||
# 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)
|
||||
|
||||
# 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:
|
||||
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
|
||||
elif mycolor == "green":
|
||||
self.color = 1
|
||||
elif mycolor == "cyan":
|
||||
self.color = 2
|
||||
else:
|
||||
self.color = 3
|
||||
|
||||
# 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)
|
||||
ccoord = (dst[0][0]+dst[1][0]+dst[2][0]+dst[3][0])/4.0
|
||||
cv2.putText(img, "{}".format(ccoord), (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)
|
||||
# cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA)
|
||||
except Exception as e:
|
||||
pass
|
||||
|
||||
# else:
|
||||
# if(len(good) < MIN_MATCH_COUNT):
|
||||
|
||||
# i += 1
|
||||
# if(i % 10 == 0):
|
||||
# print("Not enough matches are found - %d/%d" %
|
||||
# (len(good), MIN_MATCH_COUNT))
|
||||
|
||||
# matchesMask = None
|
||||
if x+y > 0:
|
||||
if abs(x) + abs(y) > 0:
|
||||
return x, y
|
||||
else:
|
||||
return None
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
def run():
|
||||
|
||||
# Object_detect().take_photo()
|
||||
# Object_detect().cut_photo()
|
||||
# goal = Object_detect().distinguist()
|
||||
goal = []
|
||||
path = os.getcwd()+'/local_photo/img'
|
||||
|
||||
for i, j, k in os.walk(path):
|
||||
for l in k:
|
||||
goal.append(cv2.imread('local_photo/img/{}'.format(l)))
|
||||
|
||||
# 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
|
||||
# init mypal260
|
||||
detect.run()
|
||||
|
||||
_init_ = 20 #
|
||||
_init_ = 20
|
||||
init_num = 0
|
||||
nparams = 0
|
||||
num = 0
|
||||
|
|
@ -504,10 +391,10 @@ def run():
|
|||
_, 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:
|
||||
|
|
@ -534,7 +421,7 @@ def run():
|
|||
init_num += 1
|
||||
continue
|
||||
|
||||
# calculate params of the coords between cube and mycobot
|
||||
# calculate params of the coords between cube and mypal260
|
||||
if nparams < 10:
|
||||
if detect.get_calculate_params(frame) is None:
|
||||
cv2.imshow("figure", frame)
|
||||
|
|
@ -551,27 +438,28 @@ def run():
|
|||
continue
|
||||
elif nparams == 10:
|
||||
nparams += 1
|
||||
# calculate and set params of calculating real coord between cube and mycobot
|
||||
# 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"
|
||||
print("ok")
|
||||
continue
|
||||
|
||||
# get detect result
|
||||
detect_result = detect.obj_detect(frame, goal)
|
||||
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
|
||||
# calculate real coord between cube and mypal260
|
||||
real_x, real_y = detect.get_position(x, y)
|
||||
if num == 5:
|
||||
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)
|
||||
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:
|
||||
|
|
@ -581,8 +469,8 @@ def run():
|
|||
|
||||
cv2.imshow("figure", frame)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run()
|
||||
# Object_detect().take_photo()
|
||||
# Object_detect().cut_photo()
|
||||
# close the window
|
||||
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||||
cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
sys.exit()
|
||||
667
mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py
Executable file
667
mycobot_ai/mechArm_270/scripts/combine_detect_obj_img_folder_opt.py
Executable file
|
|
@ -0,0 +1,667 @@
|
|||
#!/usr/bin/env python2
|
||||
# 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
|
||||
import rospy
|
||||
from visualization_msgs.msg import Marker
|
||||
from PIL import Image
|
||||
from threading import Thread
|
||||
import tkFileDialog as filedialog
|
||||
import Tkinter as tk
|
||||
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 = [
|
||||
[141.2, -142.0, 210, -26.8], # above the red bucket
|
||||
[234.3, -120, 210, -48.77], # above the green bucket
|
||||
[100.9, 159.3, 248.6, -124.27], # above the blue bucket
|
||||
[-17.6, 161.6, 238.4, -152.31], # above the gray bucket
|
||||
]
|
||||
|
||||
# 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
|
||||
self.raspi = False
|
||||
# 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.gpio_status(False)
|
||||
# self.Pin = [2, 5]
|
||||
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]
|
||||
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)
|
||||
# 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
|
||||
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, 90, 0], 20, 0)
|
||||
time.sleep(1.5)
|
||||
|
||||
# open pump
|
||||
if "dev" in self.robot_m5:
|
||||
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, -15, 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:
|
||||
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_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/myPalletizer_260/' + folder
|
||||
path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_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()
|
||||
|
||||
# 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()
|
||||
|
|
@ -24,8 +24,8 @@ class Movement(object):
|
|||
self.coords.y = item[1]
|
||||
self.coords.z = item[2]
|
||||
self.coords.rx = item[3]
|
||||
self.coords.ry = item[4]
|
||||
self.coords.rz = item[5]
|
||||
# self.coords.ry = item[4]
|
||||
# self.coords.rz = item[5]
|
||||
self.coords.speed = sp
|
||||
self.coords.model = m
|
||||
self.coord_pub.publish(self.coords)
|
||||
|
|
@ -36,8 +36,8 @@ class Movement(object):
|
|||
self.angles.joint_2 = item[1]
|
||||
self.angles.joint_3 = item[2]
|
||||
self.angles.joint_4 = item[3]
|
||||
self.angles.joint_5 = item[4]
|
||||
self.angles.joint_6 = item[5]
|
||||
# self.angles.joint_5 = item[4]
|
||||
# self.angles.joint_6 = item[5]
|
||||
self.angles.speed = sp
|
||||
self.angle_pub.publish(self.angles)
|
||||
|
||||
|
|
|
|||
157
mycobot_ai/mechArm_270/scripts/detect_obj_color.py → mycobot_ai/mechArm_270/scripts/pi_detect_obj_color.py
Executable file → Normal file
157
mycobot_ai/mechArm_270/scripts/detect_obj_color.py → mycobot_ai/mechArm_270/scripts/pi_detect_obj_color.py
Executable file → Normal file
|
|
@ -1,17 +1,18 @@
|
|||
# encoding:utf-8
|
||||
# -*- coding:utf-8 -*-
|
||||
#!/usr/bin/env python2
|
||||
|
||||
from operator import imod
|
||||
from tokenize import Pointfloat
|
||||
import cv2
|
||||
import numpy as np
|
||||
import time
|
||||
import json
|
||||
import os
|
||||
import os,sys
|
||||
import rospy
|
||||
from visualization_msgs.msg import Marker
|
||||
|
||||
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
|
||||
|
|
@ -19,27 +20,30 @@ __version__ = "1.0"
|
|||
|
||||
class Object_detect(Movement):
|
||||
|
||||
def __init__(self, camera_x=150, camera_y=-10):
|
||||
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 = [
|
||||
[-7.11, -6.94, -55.01, -24.16, 0, 15], # init the point
|
||||
[5, -10.63, -87.8, 9.05, -3.07, 15], # point to grab
|
||||
[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 = [
|
||||
[120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
|
||||
# above the yello bucket
|
||||
#[215.2, -127.8, 260.9, -157.51, -17.5, -71.18],
|
||||
[210.6, -130.5, 263.0, -150.99, -0.07, -107.35],
|
||||
[209.7, -18.6, 230.4, -168.48, -9.86, -39.38],
|
||||
[196.9, -64.7, 232.6, -166.66, -9.44, -52.47],
|
||||
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
|
||||
[141.2, -142.0, 210, -26.8], # above the red bucket
|
||||
[234.3, -120, 210, -48.77], # above the green bucket
|
||||
[100.9, 159.3, 248.6, -124.27], # above the blue bucket
|
||||
[-17.6, 161.6, 238.4, -152.31], # 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]
|
||||
|
|
@ -80,11 +84,11 @@ class Object_detect(Movement):
|
|||
"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 mycobot
|
||||
# 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 mycobot
|
||||
# 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 mycobot
|
||||
# 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
|
||||
|
|
@ -137,65 +141,54 @@ class Object_detect(Movement):
|
|||
|
||||
# Grasping motion
|
||||
def move(self, x, y, color):
|
||||
# send Angle to move mycobot
|
||||
print color
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
# 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.pub_angles(self.move_angles[1], 20)
|
||||
self.mc.send_coords([x, y, 90, 0], 20, 0)
|
||||
time.sleep(1.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
time.sleep(1.5)
|
||||
# send coordinates to move mycobot
|
||||
self.pub_coords([x, y, 165, -178.9, -1.57, -25.95], 20, 1)
|
||||
time.sleep(1.5)
|
||||
|
||||
self.pub_coords([x, y, 80, -178.9, -1.57, -25.95], 20, 1)
|
||||
|
||||
time.sleep(1)
|
||||
|
||||
# open pump
|
||||
if self.raspi:
|
||||
self.gpio_status(True)
|
||||
else:
|
||||
self.pub_pump(True, self.Pin)
|
||||
time.sleep(0.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
time.sleep(3)
|
||||
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.pub_angles(self.move_angles[1], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_marker(
|
||||
self.move_coords[3][0]/1000.0, self.move_coords[3][1]/1000.0, self.move_coords[3][2]/1000.0)
|
||||
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
self.mc.send_angle(2, 0, 20)
|
||||
time.sleep(0.3)
|
||||
self.mc.send_angle(3, -15, 20)
|
||||
time.sleep(2)
|
||||
self.pub_marker(
|
||||
self.move_coords[4][0]/1000.0, self.move_coords[4][1]/1000.0, self.move_coords[4][2]/1000.0)
|
||||
|
||||
self.pub_coords(self.move_coords[color], 20, 1)
|
||||
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(2)
|
||||
time.sleep(3)
|
||||
|
||||
# close pump
|
||||
if self.raspi:
|
||||
self.gpio_status(False)
|
||||
else:
|
||||
self.pub_pump(False, self.Pin)
|
||||
time.sleep(1)
|
||||
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.pub_angles(self.move_angles[0], 20)
|
||||
time.sleep(3)
|
||||
|
||||
# self.pub_angles(self.move_angles[0], 20)
|
||||
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
|
||||
|
|
@ -204,24 +197,20 @@ class Object_detect(Movement):
|
|||
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
|
||||
# init mypal260
|
||||
def run(self):
|
||||
self.mc = MyPalletizer("/dev/ttyAMA0",1000000) # ok
|
||||
if not self.raspi:
|
||||
self.pub_pump(False, self.Pin)
|
||||
for _ in range(5):
|
||||
self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20)
|
||||
print(_)
|
||||
time.sleep(0.5)
|
||||
self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) # ok
|
||||
time.sleep(3)
|
||||
|
||||
# draw aruco
|
||||
|
||||
def draw_marker(self, img, x, y):
|
||||
# draw rectangle on img
|
||||
cv2.rectangle(
|
||||
cv2.rectangle(
|
||||
img,
|
||||
(x - 20, y - 20),
|
||||
(x + 20, y + 20),
|
||||
|
|
@ -269,13 +258,13 @@ class Object_detect(Movement):
|
|||
self.y2 = int(y2)
|
||||
print(self.x1, self.y1, self.x2, self.y2)
|
||||
|
||||
# set parameters to calculate the coords between cube and mycobot
|
||||
# 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 mycobot
|
||||
# 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)
|
||||
|
||||
|
|
@ -284,7 +273,6 @@ class Object_detect(Movement):
|
|||
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
|
||||
|
|
@ -302,21 +290,30 @@ class Object_detect(Movement):
|
|||
# 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)
|
||||
|
|
@ -341,33 +338,35 @@ class Object_detect(Movement):
|
|||
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 == "yellow":
|
||||
self.color = 1
|
||||
elif mycolor == "red":
|
||||
# calculate the real coordinates of mypal260 relative to the target
|
||||
|
||||
if mycolor == "red":
|
||||
self.color = 0
|
||||
else:
|
||||
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
|
||||
# init mypal260
|
||||
detect.run()
|
||||
|
||||
_init_ = 20 #
|
||||
_init_ = 20
|
||||
init_num = 0
|
||||
nparams = 0
|
||||
num = 0
|
||||
|
|
@ -377,10 +376,10 @@ if __name__ == "__main__":
|
|||
_, 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:
|
||||
|
|
@ -407,7 +406,7 @@ if __name__ == "__main__":
|
|||
init_num += 1
|
||||
continue
|
||||
|
||||
# calculate params of the coords between cube and mycobot
|
||||
# calculate params of the coords between cube and mypal260
|
||||
if nparams < 10:
|
||||
if detect.get_calculate_params(frame) is None:
|
||||
cv2.imshow("figure", frame)
|
||||
|
|
@ -424,14 +423,14 @@ if __name__ == "__main__":
|
|||
continue
|
||||
elif nparams == 10:
|
||||
nparams += 1
|
||||
# calculate and set params of calculating real coord between cube and mycobot
|
||||
# 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"
|
||||
print("ok")
|
||||
continue
|
||||
|
||||
# get detect result
|
||||
|
|
@ -441,7 +440,7 @@ if __name__ == "__main__":
|
|||
continue
|
||||
else:
|
||||
x, y = detect_result
|
||||
# calculate real coord between cube and mycobot
|
||||
# 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)
|
||||
|
|
@ -454,3 +453,9 @@ if __name__ == "__main__":
|
|||
real_sx += real_x
|
||||
|
||||
cv2.imshow("figure", frame)
|
||||
|
||||
# close the window
|
||||
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||||
cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
sys.exit()
|
||||
|
|
@ -22,6 +22,7 @@ from threading import Thread
|
|||
import tkFileDialog as filedialog
|
||||
import Tkinter as tk
|
||||
from moving_utils import Movement
|
||||
from pymycobot.mypalletizer import MyPalletizer
|
||||
|
||||
IS_CV_4 = cv2.__version__[0] == '4'
|
||||
__version__ = "1.0" # Adaptive seeed
|
||||
|
|
@ -29,28 +30,27 @@ __version__ = "1.0" # Adaptive seeed
|
|||
|
||||
class Object_detect(Movement):
|
||||
|
||||
def __init__(self, camera_x=150, camera_y=-10):
|
||||
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 = [
|
||||
[-26.11, -6.94, -55.01, -24.16, 0, 15], # init the point
|
||||
[-1.14, 0.63, -87.8, 9.05, -3.07, 15], # point to grab
|
||||
[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 = [
|
||||
[120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
|
||||
# above the yello bucket
|
||||
#[208.2, -127.8, 260.9, -157.51, -17.5, -71.18],
|
||||
[205.6, -130.5, 263.0, -150.99, -0.07, -107.35], # above the green bucket
|
||||
[-20.0, 176.7, 242.6, -166.66, -9.44, -52.47], # above the gray bucket
|
||||
[104.9, 176.7, 242.6, -166.66, -9.44, -52.47], # above the blue bucket
|
||||
[126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
|
||||
[141.2, -142.0, 210, -26.8], # above the red bucket
|
||||
[234.3, -120, 210, -48.77], # above the green bucket
|
||||
[100.9, 159.3, 248.6, -124.27], # above the blue bucket
|
||||
[-17.6, 161.6, 238.4, -152.31], # above the gray bucket
|
||||
]
|
||||
|
||||
# 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
|
||||
|
|
@ -97,6 +97,7 @@ class Object_detect(Movement):
|
|||
# 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)
|
||||
|
|
@ -125,7 +126,6 @@ class Object_detect(Movement):
|
|||
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
|
||||
|
|
@ -144,56 +144,40 @@ class Object_detect(Movement):
|
|||
|
||||
# Grasping motion
|
||||
def move(self, x, y, color):
|
||||
# send Angle to move mycobot
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
# 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.pub_angles(self.move_angles[1], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
time.sleep(1.5)
|
||||
# send coordinates to move mycobot
|
||||
self.pub_coords([x, y, 165, -178.9, -1.57, -66], 20, 1)
|
||||
time.sleep(1.5)
|
||||
# 根据不同底板机械臂，调整吸泵高度
|
||||
self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
|
||||
self.mc.send_coords([x, y, 90, 0], 20, 0)
|
||||
time.sleep(1.5)
|
||||
|
||||
# open pump
|
||||
self.gpio_status(True)
|
||||
|
||||
time.sleep(0.5)
|
||||
self.pub_angles(self.move_angles[2], 20)
|
||||
time.sleep(3)
|
||||
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.pub_angles(self.move_angles[1], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_marker(self.move_coords[3][0] / 1000.0,
|
||||
self.move_coords[3][1] / 1000.0,
|
||||
self.move_coords[3][2] / 1000.0)
|
||||
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
time.sleep(1.5)
|
||||
self.pub_marker(self.move_coords[4][0] / 1000.0,
|
||||
self.move_coords[4][1] / 1000.0,
|
||||
self.move_coords[4][2] / 1000.0)
|
||||
self.mc.send_angle(2, 0, 20)
|
||||
time.sleep(0.3)
|
||||
self.mc.send_angle(3, -15, 20)
|
||||
time.sleep(2)
|
||||
|
||||
print(self.move_coords[color])
|
||||
self.pub_coords(self.move_coords[color], 20, 1)
|
||||
|
||||
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(4)
|
||||
time.sleep(3)
|
||||
|
||||
# close pump
|
||||
self.gpio_status(False)
|
||||
|
||||
time.sleep(1)
|
||||
self.pub_marker(self.move_coords[color][0] / 1000.0 + 0.04,
|
||||
self.move_coords[color][1] / 1000.0 - 0.02)
|
||||
self.pub_angles(self.move_angles[0], 20)
|
||||
time.sleep(3)
|
||||
|
||||
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)
|
||||
|
|
@ -209,13 +193,14 @@ class Object_detect(Movement):
|
|||
|
||||
# init mycobot
|
||||
def run(self):
|
||||
for _ in range(5):
|
||||
self.pub_angles([-26.11, -6.94, -55.01, -24.16, 0, -15], 20)
|
||||
print(_)
|
||||
time.sleep(0.5)
|
||||
self.mc = MyPalletizer("/dev/ttyAMA0",1000000) # ok
|
||||
if not self.raspi:
|
||||
self.pub_pump(False, self.Pin)
|
||||
|
||||
self.mc.send_angles([-29.0, 5.88, -4.92, -76.28], 20) # ok
|
||||
time.sleep(3)
|
||||
|
||||
# draw aruco
|
||||
|
||||
def draw_marker(self, img, x, y):
|
||||
# draw rectangle on img
|
||||
cv2.rectangle(
|
||||
|
|
@ -244,6 +229,7 @@ class Object_detect(Movement):
|
|||
# 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.
|
||||
|
|
@ -389,15 +375,6 @@ class Object_detect(Movement):
|
|||
except Exception as e:
|
||||
pass
|
||||
|
||||
# else:
|
||||
# if(len(good) < MIN_MATCH_COUNT):
|
||||
|
||||
# i += 1
|
||||
# if(i % 10 == 0):
|
||||
# print("Not enough matches are found - %d/%d" %
|
||||
# (len(good), MIN_MATCH_COUNT))
|
||||
|
||||
# matchesMask = None
|
||||
if x + y > 0:
|
||||
return x, y
|
||||
else:
|
||||
|
|
@ -406,13 +383,12 @@ class Object_detect(Movement):
|
|||
# The path to save the image folder
|
||||
def parse_folder(folder):
|
||||
restore = []
|
||||
path = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/' + folder
|
||||
path = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/myPalletizer_260/' + folder
|
||||
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 = []
|
||||
|
|
@ -428,7 +404,6 @@ def compute_keypoints_and_descriptors(sift, images_lists):
|
|||
|
||||
return kp_list, desc_list
|
||||
|
||||
|
||||
GET_FRAME = 1
|
||||
STOP_PROCESSING = 2
|
||||
DRAW_COORDS = 3
|
||||
|
|
@ -436,13 +411,11 @@ 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
|
||||
|
|
@ -457,7 +430,6 @@ def process_transform_frame(frame, x1, y1, x2, y2):
|
|||
# int(x1 * 0.7):int(x2 * 1.15)]
|
||||
return frame
|
||||
|
||||
|
||||
def process_display_frame(connection):
|
||||
cap_num = 0
|
||||
coord = None
|
||||
|
|
@ -502,8 +474,7 @@ def process_display_frame(connection):
|
|||
|
||||
def run():
|
||||
parent_conn, child_conn = Pipe()
|
||||
|
||||
child = Process(target=process_display_frame, args=(child_conn,))
|
||||
child = Process(target = process_display_frame, args=(child_conn,))
|
||||
child.start()
|
||||
|
||||
# Object_detect().take_photo()
|
||||
|
|
@ -513,8 +484,8 @@ def run():
|
|||
res_queue = [[], [], [], []]
|
||||
res_queue[0] = parse_folder('res/red')
|
||||
res_queue[1] = parse_folder('res/green')
|
||||
res_queue[2] = parse_folder('res/gray')
|
||||
res_queue[3] = parse_folder('res/blue')
|
||||
res_queue[2] = parse_folder('res/blue')
|
||||
res_queue[3] = parse_folder('res/gray')
|
||||
|
||||
# res_queue = []
|
||||
# res_queue.extend(parse_folder('res/red'))
|
||||
|
|
@ -527,6 +498,7 @@ def run():
|
|||
|
||||
# init a class of Object_detect
|
||||
detect = Object_detect()
|
||||
|
||||
# init mycobot
|
||||
detect.run()
|
||||
|
||||
|
|
@ -607,9 +579,7 @@ def run():
|
|||
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
|
||||
|
|
@ -639,8 +609,14 @@ def run():
|
|||
end_time = time.time()
|
||||
print("loop_time = ", end_time - start_time)
|
||||
|
||||
child.join()
|
||||
# close the window
|
||||
if cv2.waitKey(1) & 0xFF == ord('q'):
|
||||
cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
sys.exit()
|
||||
|
||||
child.join()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run()
|
||||
|
|
@ -1,104 +1,41 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
|
||||
# from fileinput import filename
|
||||
# from genericpath import isfile
|
||||
# import os
|
||||
# from sys import path
|
||||
# import cv2
|
||||
# from PIL import Image
|
||||
|
||||
|
||||
# # #count=0
|
||||
# for file in dirs:
|
||||
# pic_dir=os.path.join(path,file) # res中子文件夹的路径
|
||||
# print(pic_dir)
|
||||
# for i in os.listdir(pic_dir):
|
||||
# imgdir=os.path.join(pic_dir,i)
|
||||
# print(imgdir)
|
||||
# for i in os.listdir(pic_dir):
|
||||
# image_dir=os.path.join(pic_dir,i) #res中每个子文件夹中图片的路径
|
||||
# img1 = cv2.imread(image_dir) # 读取res中每个子文件夹中的图片
|
||||
# #count+=1
|
||||
# print(image_dir)#输出图片的路径
|
||||
#print(img1)#输出图片
|
||||
#print(count)#图片个数
|
||||
# dir_path = os.path.dirname(__file__)
|
||||
# print(dir_path)
|
||||
# # path1 = os.path.split(os.path.realpath(__file__))[0]
|
||||
# # print(path1)
|
||||
# path3=os.path.join(os.path.split(dir_path)[0]+'/res/')
|
||||
|
||||
# print(path3)
|
||||
# #for file in os.listdir(path3):
|
||||
# pic_dir=os.path.join(path3+'red')
|
||||
# # print(pic_dir)
|
||||
# for i in os.listdir(pic_dir):
|
||||
# img=os.path.join(pic_dir,i)
|
||||
# print(img)
|
||||
# print(os.getcwd()+'/mycobot_ai/res/red')
|
||||
|
||||
# list1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]
|
||||
# print(list1[0][0])
|
||||
# for i, v in enumerate(list1):
|
||||
# print(i)
|
||||
|
||||
# res = []
|
||||
# for i in list1:
|
||||
# res.append(i)
|
||||
# print(res)
|
||||
|
||||
# # for i in list1:
|
||||
# # print(i)
|
||||
|
||||
# color=i
|
||||
# print(color)
|
||||
# for color in range(0,4):
|
||||
# print(color)
|
||||
|
||||
from pymycobot.mycobot import MyCobot
|
||||
from pymycobot.mypalletizer import MyPalletizer
|
||||
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
|
||||
import time,os
|
||||
|
||||
# mc = MyCobot("/dev/ttyACM0", 115200)
|
||||
mc = MyPalletizer(os.popen("ls /dev/ttyUSB*").readline()[:-1], 115200)
|
||||
|
||||
mc = MyCobot("/dev/ttyAMA0", 1000000)
|
||||
# mc.send_angles([0,0,0,0,0,0], 20)
|
||||
# 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]
|
||||
# time.sleep(1.5)
|
||||
|
||||
# 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)
|
||||
# move_coords = [
|
||||
# [120.1, -141.6, 240.9, -173.34, -8.15, -110.11], # above the red bucket
|
||||
# # above the green bucket
|
||||
# #[208.2, -127.8, 260.9, -157.51, -17.5, -71.18],
|
||||
# [205.6, -130.5, 263.0, -150.99, -0.07, -107.35],
|
||||
# [209.7, -18.6, 230.4, -168.48, -9.86, -39.38],
|
||||
# [196.9, -64.7, 232.6, -166.66, -9.44, -52.47],
|
||||
# [126.6, -118.1, 305.0, -157.57, -13.72, -75.3],
|
||||
# ]
|
||||
|
||||
# mc.send_coords([126.6, -118.1, 305.0, -157.57, -13.72, -75.3],20,1)
|
||||
# mc.send_coords([141.2, -142.0, 206.2, -26.8],25,1) # above the red bucket
|
||||
# time.sleep(2)
|
||||
# mc.send_coords([104.9, 176.7, 242.6, -166.66, -9.44, -52.47],20,1) # above the blue bucket
|
||||
# mc.send_coords([234.3, -120, 210, -48.77],25,1) # above the green bucket
|
||||
# time.sleep(2)
|
||||
# mc.send_coords([-20.0, 176.7, 242.6, -166.66, -9.44, -52.47],20,1) # abobe the gray bucket
|
||||
# time.sleep(2)
|
||||
# mc.send_coords([120.1,151.6,250.0,-173.34,-8.15,-110.11],20,1)
|
||||
# time.sleep(2)
|
||||
# mc.send_coords([104.9, 176.7, 242.6, -166.66, -9.44, -52.47],20,1)
|
||||
# mc.send_coords([100.9, 159.3, 248.6, -124.27],20,1) # above the blue bucket
|
||||
# time.sleep(3)
|
||||
# mc.send_coords([-17.6, 161.6, 238.4, -152.31],20,1) # above the gray bucket
|
||||
# time.sleep(3)
|
||||
|
||||
# mc.send_angle(3,0,25)
|
||||
# print(mc.get_angles())
|
||||
# print(mc.get_coords())
|
||||
|
||||
# while True:
|
||||
# print("angles:%s"%mc.get_angles())
|
||||
# print("coords:%s"%mc.get_coords())
|
||||
# print("\n")
|
||||
|
||||
mc.send_angles([-26.11, -6.94, -55.01, -24.16, 0, 15],20)
|
||||
# mc.release_all_servos()
|
||||
time.sleep(3)
|
||||
print(mc.get_angles())
|
||||
# mc.send_angles([-1.14, 3.63, -87.8, 9.05, -3.07, 15],20)
|
||||
time.sleep(2)
|
||||
# print(mc.get_angles())
|
||||
# mc.send_angles([17.4, -10.1, -87.27, 5.8, -2.02, 15],20)
|
||||
# time.sleep(2)
|
||||
# print(mc.get_angles())
|
||||
|
||||
# mc.release_servo(6)
|
||||
mc.release_all_servos()
|
||||
# mc.set_servo_calibration(6)
|
||||
# if os.listdir(path,filename='blue'):
|
||||
# pass
|
||||
# mc.set_servo_calibration(1)
|
||||
# mc.set_servo_calibration(2)
|
||||
# mc.set_servo_calibration(3)
|
||||
# mc.set_servo_calibration(4)
|
||||
Loading…
Add table
Reference in a new issue