diff --git a/mycobot_ai/ai_ultraarm/CMakeLists.txt b/mycobot_ai/ai_ultraarm/CMakeLists.txt
deleted file mode 100644
index b866e09..0000000
--- a/mycobot_ai/ai_ultraarm/CMakeLists.txt
+++ /dev/null
@@ -1,204 +0,0 @@
-cmake_minimum_required(VERSION 3.0.2)
-project(ai_ultraarm)
-
-## Compile as C++11, supported in ROS Kinetic and newer
-# add_compile_options(-std=c++11)
-
-## Find catkin macros and libraries
-## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
-## is used, also find other catkin packages
-find_package(catkin REQUIRED COMPONENTS
-  ultraarm
-)
-
-## System dependencies are found with CMake's conventions
-# find_package(Boost REQUIRED COMPONENTS system)
-
-
-## Uncomment this if the package has a setup.py. This macro ensures
-## modules and global scripts declared therein get installed
-## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
-# catkin_python_setup()
-
-################################################
-## Declare ROS messages, services and actions ##
-################################################
-
-## To declare and build messages, services or actions from within this
-## package, follow these steps:
-## * Let MSG_DEP_SET be the set of packages whose message types you use in
-##   your messages/services/actions (e.g. std_msgs, actionlib_msgs, ...).
-## * In the file package.xml:
-##   * add a build_depend tag for "message_generation"
-##   * add a build_depend and a exec_depend tag for each package in MSG_DEP_SET
-##   * If MSG_DEP_SET isn't empty the following dependency has been pulled in
-##     but can be declared for certainty nonetheless:
-##     * add a exec_depend tag for "message_runtime"
-## * In this file (CMakeLists.txt):
-##   * add "message_generation" and every package in MSG_DEP_SET to
-##     find_package(catkin REQUIRED COMPONENTS ...)
-##   * add "message_runtime" and every package in MSG_DEP_SET to
-##     catkin_package(CATKIN_DEPENDS ...)
-##   * uncomment the add_*_files sections below as needed
-##     and list every .msg/.srv/.action file to be processed
-##   * uncomment the generate_messages entry below
-##   * add every package in MSG_DEP_SET to generate_messages(DEPENDENCIES ...)
-
-## Generate messages in the 'msg' folder
-# add_message_files(
-#   FILES
-#   Message1.msg
-#   Message2.msg
-# )
-
-## Generate services in the 'srv' folder
-# add_service_files(
-#   FILES
-#   Service1.srv
-#   Service2.srv
-# )
-
-## Generate actions in the 'action' folder
-# add_action_files(
-#   FILES
-#   Action1.action
-#   Action2.action
-# )
-
-## Generate added messages and services with any dependencies listed here
-# generate_messages(
-#   DEPENDENCIES
-#   std_msgs  # Or other packages containing msgs
-# )
-
-################################################
-## Declare ROS dynamic reconfigure parameters ##
-################################################
-
-## To declare and build dynamic reconfigure parameters within this
-## package, follow these steps:
-## * In the file package.xml:
-##   * add a build_depend and a exec_depend tag for "dynamic_reconfigure"
-## * In this file (CMakeLists.txt):
-##   * add "dynamic_reconfigure" to
-##     find_package(catkin REQUIRED COMPONENTS ...)
-##   * uncomment the "generate_dynamic_reconfigure_options" section below
-##     and list every .cfg file to be processed
-
-## Generate dynamic reconfigure parameters in the 'cfg' folder
-# generate_dynamic_reconfigure_options(
-#   cfg/DynReconf1.cfg
-#   cfg/DynReconf2.cfg
-# )
-
-###################################
-## catkin specific configuration ##
-###################################
-## The catkin_package macro generates cmake config files for your package
-## Declare things to be passed to dependent projects
-## INCLUDE_DIRS: uncomment this if your package contains header files
-## LIBRARIES: libraries you create in this project that dependent projects also need
-## CATKIN_DEPENDS: catkin_packages dependent projects also need
-## DEPENDS: system dependencies of this project that dependent projects also need
-catkin_package(
-#  INCLUDE_DIRS include
-#  LIBRARIES mycobot_ai
-#  CATKIN_DEPENDS mycobot_280
-#  DEPENDS system_lib
-)
-
-###########
-## Build ##
-###########
-
-## Specify additional locations of header files
-## Your package locations should be listed before other locations
-include_directories(
-# include
-  ${catkin_INCLUDE_DIRS}
-)
-
-## Declare a C++ library
-# add_library(${PROJECT_NAME}
-#   src/${PROJECT_NAME}/mycobot_ai.cpp
-# )
-
-## Add cmake target dependencies of the library
-## as an example, code may need to be generated before libraries
-## either from message generation or dynamic reconfigure
-# add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
-
-## Declare a C++ executable
-## With catkin_make all packages are built within a single CMake context
-## The recommended prefix ensures that target names across packages don't collide
-# add_executable(${PROJECT_NAME}_node src/mycobot_ai_node.cpp)
-
-## Rename C++ executable without prefix
-## The above recommended prefix causes long target names, the following renames the
-## target back to the shorter version for ease of user use
-## e.g. "rosrun someones_pkg node" instead of "rosrun someones_pkg someones_pkg_node"
-# set_target_properties(${PROJECT_NAME}_node PROPERTIES OUTPUT_NAME node PREFIX "")
-
-## Add cmake target dependencies of the executable
-## same as for the library above
-# add_dependencies(${PROJECT_NAME}_node ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS})
-
-## Specify libraries to link a library or executable target against
-# target_link_libraries(${PROJECT_NAME}_node
-#   ${catkin_LIBRARIES}
-# )
-
-#############
-## Install ##
-#############
-
-# all install targets should use catkin DESTINATION variables
-# See http://ros.org/doc/api/catkin/html/adv_user_guide/variables.html
-
-## Mark executable scripts (Python etc.) for installation
-## in contrast to setup.py, you can choose the destination
-# catkin_install_python(PROGRAMS
-#   scripts/my_python_script
-#   DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
-# )
-
-## Mark executables for installation
-## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_executables.html
-# install(TARGETS ${PROJECT_NAME}_node
-#   RUNTIME DESTINATION ${CATKIN_PACKAGE_BIN_DESTINATION}
-# )
-
-## Mark libraries for installation
-## See http://docs.ros.org/melodic/api/catkin/html/howto/format1/building_libraries.html
-# install(TARGETS ${PROJECT_NAME}
-#   ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
-#   LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION}
-#   RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}
-# )
-
-## Mark cpp header files for installation
-# install(DIRECTORY include/${PROJECT_NAME}/
-#   DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION}
-#   FILES_MATCHING PATTERN "*.h"
-#   PATTERN ".svn" EXCLUDE
-# )
-
-## Mark other files for installation (e.g. launch and bag files, etc.)
-# install(FILES
-#   # myfile1
-#   # myfile2
-#   DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}
-# )
-
-#############
-## Testing ##
-#############
-
-## Add gtest based cpp test target and link libraries
-# catkin_add_gtest(${PROJECT_NAME}-test test/test_mycobot_ai.cpp)
-# if(TARGET ${PROJECT_NAME}-test)
-#   target_link_libraries(${PROJECT_NAME}-test ${PROJECT_NAME})
-# endif()
-
-## Add folders to be run by python nosetests
-# catkin_add_nosetests(test)
diff --git a/mycobot_ai/ai_ultraarm/launch/vision_m5.launch b/mycobot_ai/ai_ultraarm/launch/vision_m5.launch
deleted file mode 100644
index 7928868..0000000
--- a/mycobot_ai/ai_ultraarm/launch/vision_m5.launch
+++ /dev/null
@@ -1,27 +0,0 @@
-<launch>
-	<arg name="port" default="/dev/ttyUSB0" />
-	<arg name="baud" default="115200" />
-
-	<arg name="model" default="$(find mycobot_description)/urdf/ultraArm_urdf/ultraArm_aikit.urdf"/>
-	<arg name="rvizconfig" default="$(find ultraarm)/config/ultraArm.rviz" />
-	<!-- <arg name="gui" default="false" /> -->
-
-	<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
-
-	<!-- Combinejoin values to TF -->
-	<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
-		<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
-	</node>
-
-	<!-- mypalletizer-topics -->
-    <include file="$(find ultraarm_communication)/launch/communication_topic.launch">
-		<arg name="port" value="$(arg port)" />	
-		<arg name="baud" value="$(arg baud)" />	
-    </include>
-
-    <!-- listen and pub the real angles -->
-	<node name="real_listener" pkg="ultraarm" type="listen_real_of_topic.py" />
-
-	<!-- Show in Rviz -->
-	<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
-</launch>
diff --git a/mycobot_ai/ai_ultraarm/launch/vision_pi.launch b/mycobot_ai/ai_ultraarm/launch/vision_pi.launch
deleted file mode 100644
index 95333de..0000000
--- a/mycobot_ai/ai_ultraarm/launch/vision_pi.launch
+++ /dev/null
@@ -1,27 +0,0 @@
-<launch>
-<arg name="port" default="/dev/ttyAMA0" />
-	<arg name="baud" default="1000000" />
-
-	<arg name="model" default="$(find mycobot_description)/urdf/260_pi/mypal_260_pi_aikit.urdf"/>
-	<arg name="rvizconfig" default="$(find mypalletizer_260_pi)/config/mypal_260_pi.rviz" />
-	<!-- <arg name="gui" default="false" /> -->
-
-	<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
-
-	<!-- Combinejoin values to TF -->
-	<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
-		<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
-	</node>
-
-	<!-- mypalletizer-topics -->
-    <include file="$(find mypalletizer_communication)/launch/communication_topic_pi.launch">
-		<arg name="port" value="$(arg port)" />	
-		<arg name="baud" value="$(arg baud)" />	
-    </include>
-
-    <!-- listen and pub the real angles -->
-	<node name="real_listener" pkg="mypalletizer_260_pi" type="listen_real_of_topic.py" />
-
-	<!-- Show in Rviz -->
-	<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
-</launch>
diff --git a/mycobot_ai/ai_ultraarm/launch/vision_wio.launch b/mycobot_ai/ai_ultraarm/launch/vision_wio.launch
deleted file mode 100644
index 51eb78b..0000000
--- a/mycobot_ai/ai_ultraarm/launch/vision_wio.launch
+++ /dev/null
@@ -1,27 +0,0 @@
-<launch>
-	<arg name="port" default="/dev/ttyACM0" />
-	<arg name="baud" default="115200" />
-
-	<arg name="model" default="$(find mycobot_description)/urdf/mycobot/mycobot_with_vision.urdf"/>
-	<arg name="rvizconfig" default="$(find mypalletizer_260)/config/mycobot.rviz" />
-	<!-- <arg name="gui" default="false" /> -->
-
-	<param name="robot_description" command="$(find xacro)/xacro --inorder $(arg model)" />
-
-	<!-- Combinejoin values to TF -->
-	<node name="robot_state_publisher" pkg="robot_state_publisher" type="state_publisher" >
-		<rosparam param="source_list" subst_value="true">["joint_states"]</rosparam>
-	</node>
-
-	<!-- mycobot-topics -->
-    <include file="$(find mycobot_communication)/launch/communication_topic.launch">
-		<arg name="port" value="$(arg port)" />	
-		<arg name="baud" value="$(arg baud)" />	
-    </include>
-
-    <!-- listen and pub the real angles -->
-	<node name="real_listener" pkg="mypalletizer_260" type="listen_real_of_topic.py" />
-
-	<!-- Show in Rviz -->
-	<node name="rviz" pkg="rviz" type="rviz" args="-d $(arg rvizconfig)" required="true" />
-</launch>
diff --git a/mycobot_ai/ai_ultraarm/local_photo/goal5.jpeg b/mycobot_ai/ai_ultraarm/local_photo/goal5.jpeg
deleted file mode 100644
index 42767ce..0000000
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diff --git a/mycobot_ai/ai_ultraarm/local_photo/img/goal01.jpeg b/mycobot_ai/ai_ultraarm/local_photo/img/goal01.jpeg
deleted file mode 100644
index 1c5b153..0000000
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diff --git a/mycobot_ai/ai_ultraarm/local_photo/img/goal03.jpeg b/mycobot_ai/ai_ultraarm/local_photo/img/goal03.jpeg
deleted file mode 100644
index a6566fb..0000000
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diff --git a/mycobot_ai/ai_ultraarm/local_photo/img/goal2.jpeg b/mycobot_ai/ai_ultraarm/local_photo/img/goal2.jpeg
deleted file mode 100644
index cdb50bf..0000000
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diff --git a/mycobot_ai/ai_ultraarm/local_photo/takephoto.jpeg b/mycobot_ai/ai_ultraarm/local_photo/takephoto.jpeg
deleted file mode 100644
index 9968701..0000000
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diff --git a/mycobot_ai/ai_ultraarm/package.xml b/mycobot_ai/ai_ultraarm/package.xml
deleted file mode 100644
index e18f968..0000000
--- a/mycobot_ai/ai_ultraarm/package.xml
+++ /dev/null
@@ -1,62 +0,0 @@
-<?xml version="1.0"?>
-<package format="2">
-  <name>ai_ultraarm</name>
-  <version>0.0.0</version>
-  <description>The ai_ultraarm package</description>
-
-  <!-- One maintainer tag required, multiple allowed, one person per tag -->
-  <!-- Example:  -->
-  <!-- <maintainer email="jane.doe@example.com">Jane Doe</maintainer> -->
-  <maintainer email="huang@todo.todo">huang</maintainer>
-
-
-  <!-- One license tag required, multiple allowed, one license per tag -->
-  <!-- Commonly used license strings: -->
-  <!--   BSD, MIT, Boost Software License, GPLv2, GPLv3, LGPLv2.1, LGPLv3 -->
-  <license>TODO</license>
-
-
-  <!-- Url tags are optional, but multiple are allowed, one per tag -->
-  <!-- Optional attribute type can be: website, bugtracker, or repository -->
-  <!-- Example: -->
-  <!-- <url type="website">http://wiki.ros.org/mycobot_ai</url> -->
-
-
-  <!-- Author tags are optional, multiple are allowed, one per tag -->
-  <!-- Authors do not have to be maintainers, but could be -->
-  <!-- Example: -->
-  <!-- <author email="jane.doe@example.com">Jane Doe</author> -->
-
-
-  <!-- The *depend tags are used to specify dependencies -->
-  <!-- Dependencies can be catkin packages or system dependencies -->
-  <!-- Examples: -->
-  <!-- Use depend as a shortcut for packages that are both build and exec dependencies -->
-  <!--   <depend>roscpp</depend> -->
-  <!--   Note that this is equivalent to the following: -->
-  <!--   <build_depend>roscpp</build_depend> -->
-  <!--   <exec_depend>roscpp</exec_depend> -->
-  <!-- Use build_depend for packages you need at compile time: -->
-  <!--   <build_depend>message_generation</build_depend> -->
-  <!-- Use build_export_depend for packages you need in order to build against this package: -->
-  <!--   <build_export_depend>message_generation</build_export_depend> -->
-  <!-- Use buildtool_depend for build tool packages: -->
-  <!--   <buildtool_depend>catkin</buildtool_depend> -->
-  <!-- Use exec_depend for packages you need at runtime: -->
-  <!--   <exec_depend>message_runtime</exec_depend> -->
-  <!-- Use test_depend for packages you need only for testing: -->
-  <!--   <test_depend>gtest</test_depend> -->
-  <!-- Use doc_depend for packages you need only for building documentation: -->
-  <!--   <doc_depend>doxygen</doc_depend> -->
-  <buildtool_depend>catkin</buildtool_depend>
-  <build_depend>ultraarm</build_depend>
-  <build_export_depend>ultraarm</build_export_depend>
-  <exec_depend>ultraarm</exec_depend>
-
-
-  <!-- The export tag contains other, unspecified, tags -->
-  <export>
-    <!-- Other tools can request additional information be placed here -->
-
-  </export>
-</package>
diff --git a/mycobot_ai/ai_ultraarm/prof.calltree b/mycobot_ai/ai_ultraarm/prof.calltree
deleted file mode 100644
index adace80..0000000
--- a/mycobot_ai/ai_ultraarm/prof.calltree
+++ /dev/null
@@ -1,21703 +0,0 @@
-event: ns : Nanoseconds
-events: ns
-summary: 302460620000
-fl=/build/python2.7-MQK6UF/python2.7-2.7.17/Modules/pyexpat.c
-fn=CharacterData
-443 65999
-cfl=/usr/lib/python2.7/xmlrpclib.py
-cfn=data
-calls=67 822
-443 101000
-
-fl=/build/python2.7-MQK6UF/python2.7-2.7.17/Modules/pyexpat.c
-fn=StartElement
-571 70999
-cfl=/usr/lib/python2.7/xmlrpclib.py
-cfn=start
-calls=64 813
-571 218999
-
-fl=/build/python2.7-MQK6UF/python2.7-2.7.17/Modules/pyexpat.c
-fn=EndElement
-623 107000
-cfl=/usr/lib/python2.7/xmlrpclib.py
-cfn=end
-calls=64 825
-623 624000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/__init__.py
-fn=<module>
-1 1000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotAngles.py
-fn=<module>
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-cfn=MycobotAngles
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-2 6000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotAngles.py
-fn=MycobotAngles
-10 6000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotCoords.py
-fn=<module>
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-cfn=MycobotCoords
-calls=1 10
-2 5000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotCoords.py
-fn=MycobotCoords
-10 5000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotGripperStatus.py
-fn=<module>
-2 96000
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-cfn=MycobotGripperStatus
-calls=1 10
-2 6000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotGripperStatus.py
-fn=MycobotGripperStatus
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-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotPumpStatus.py
-fn=<module>
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-cfl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotPumpStatus.py
-cfn=MycobotPumpStatus
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-2 4000
-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotPumpStatus.py
-fn=MycobotPumpStatus
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-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotPumpStatus.py
-fn=__init__
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-
-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetAngles.py
-fn=<module>
-2 88000
-cfl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetAngles.py
-cfn=MycobotSetAngles
-calls=1 10
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetAngles.py
-fn=MycobotSetAngles
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetAngles.py
-fn=__init__
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetCoords.py
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-cfn=MycobotSetCoords
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetCoords.py
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/_MycobotSetCoords.py
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-fl=/home/ubuntu/catkin_ws/devel/lib/python2.7/dist-packages/mycobot_communication/msg/__init__.py
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-fl=/opt/ros/melodic/lib/python2.7/dist-packages/catkin/find_in_workspaces.py
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diff --git a/mycobot_ai/ai_ultraarm/scripts/add_img.py b/mycobot_ai/ai_ultraarm/scripts/add_img.py
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index bc6dddc..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/add_img.py
+++ /dev/null
@@ -1,139 +0,0 @@
-# coding:utf-8
-from fileinput import filename
-import os, cv2, sys
-
-
-def take_photo():
-    # 提醒用户操作字典
-    print("*********************************************")
-    print("*  热键(请在摄像头的窗口使用)：             *")
-    print("*  z: 拍摄图片                              *")
-    print("*  q: 退出                                  *")
-    print("*********************************************")
-
-    # 创建/使用local_photo文件夹
-    class_name = "res"
-    if (os.path.exists("res")):
-        pass
-    else:
-        os.mkdir(class_name)
-
-    # 设置特定值
-
-    index = 'takephoto'
-    cap = cv2.VideoCapture(0)
-
-    while True:
-        # 读入每一帧
-        ret, frame = cap.read()
-
-        cv2.imshow("capture", frame)
-
-        # 存储
-        input = cv2.waitKey(1) & 0xFF
-        # 拍照
-        if input == ord('z'):
-            cv2.imwrite(
-                "%s/%s.jpeg" % (class_name, index),
-                cv2.resize(frame, (600, 480), interpolation=cv2.INTER_AREA))
-            break
-
-        # 退出
-        if input == ord('q'):
-
-            # 关闭窗口
-            cap.release()
-            cv2.destroyAllWindows()
-            sys.exit()
-
-
-def cut_photo():
-    
-    path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/ai_ultraarm/'    # pi
-    path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_ultraarm/'         # m5
-
-    if os.path.exists(path1):
-        path = path1
-    elif os.path.exists(path2):
-        path = path2
-    else:
-        print("invalid file path! Please check whether the file path exists or modify it!")
-
-
-    path_red = path + '/res/red'
-    for i, j, k in os.walk(path_red):
-        file_len_red = len(k)
-
-    path_gray = path + '/res/gray'
-    for i, j, k in os.walk(path_gray):
-        file_len_gray = len(k)
-
-    path_green = path + '/res/green'
-    for i, j, k in os.walk(path_green):
-        file_len_green = len(k)
-
-    path_blue = path + '/res/blue'
-    for i, j, k in os.walk(path_blue):
-        file_len_blue = len(k)
-    print("请截取要识别的部分")
-    # root = tk.Tk()
-    # root.withdraw()
-    # temp1=filedialog.askopenfilename(parent=root)   #rgb
-    # temp2=Image.open(temp1,mode='r')
-    # temp2= cv.cvtColor(np.asarray(temp2),cv.COLOR_RGB2BGR)
-    # cut = np.array(temp2)
-
-    cut = cv2.imread(r"res/takephoto.jpeg")
-
-    cv2.imshow('original', cut)
-    # C:\Users\Elephant\Desktop\pymycobot+opencv\local_photo/takephoto.jpeg
-
-    # 选择ROI
-    roi = cv2.selectROI(windowName="original",
-                        img=cut,
-                        showCrosshair=False,
-                        fromCenter=False)
-    x, y, w, h = roi
-    print(roi)
-
-    msg = """\
-    Image save location:
-        1 - Save to red folder
-        2 - Save to gray folder
-        3 - Save to green folder
-        4 - Save to blue folder
-        """
-    print(msg)
-    kw = int(input("请输入保存图片文件夹数字编号:"))
-    # print(kw)
-
-    # 显示ROI并保存图片
-    if roi != (0, 0, 0, 0):
-        
-        crop = cut[y:y + h, x:x + w]
-        cv2.imshow('crop', crop)
-        # 选择红桶文件夹
-        if kw == 1:
-            cv2.imwrite(path + '/res/red/goal{}.jpeg'.format(str(file_len_red + 1)),crop)
-            print('Saved')
-        # 选择灰桶文件夹
-        elif kw == 2:
-            cv2.imwrite(path + '/res/gray/goal{}.jpeg'.format(str(file_len_gray+1)),crop)
-            print('Saved')
-        # 选择绿桶文件夹
-        elif kw == 3:
-            cv2.imwrite(path + '/res/green/goal{}.jpeg'.format(str(file_len_green+1)),crop)
-            print('Saved')
-        # 选择蓝桶文件夹
-        elif kw == 4:
-            cv2.imwrite(path + '/res/blue/goal{}.jpeg'.format(str(file_len_blue+1)),crop)
-            print('Saved')
-
-    # 退出
-    cv2.waitKey(0)
-    cv2.destroyAllWindows()
-
-
-if __name__ == "__main__":
-    take_photo()
-    cut_photo()
diff --git a/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_color.py b/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_color.py
deleted file mode 100755
index 7ca841a..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_color.py
+++ /dev/null
@@ -1,441 +0,0 @@
-#!/usr/bin/env python2
-# -*- coding:utf-8 -*- 
-from operator import imod
-from tokenize import Pointfloat
-import cv2
-import numpy as np
-import time
-import json
-import os,sys
-import rospy
-from visualization_msgs.msg import Marker   
-from pymycobot.ultraArm import ultraArm
-from moving_utils import Movement
-
-IS_CV_4 = cv2.__version__[0] == '4'
-__version__ = "1.0"
-# Adaptive seeed
-
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x = 148, camera_y = 10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-
-        # declare ultraArm
-        self.ua = None
-
-        # 移动角度
-        self.move_angles = [
-            [0.0, 0.0, 0.0],  # init the point
-            [19.48, 0.0, 0.0],  # point to grab
-            # [17.4, -10.1, -87.27, 5.8, -2.02, 15],  # point to grab
-        ]
-
-        # 移动坐标
-        self.move_coords = [
-            [121.35, 127.48, 120.0],  # above the red bucket
-            [217.09, 113.01, 98.36], # above the green bucket
-            [107.54, -171.23, 117.11], # above the blue bucket
-            [-6.91, -175.86, 120.0], # above the gray bucket         
-        ]
-
-        # which robot: USB* is m5; ACM* is wio; AMA* is raspi
-        self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
-        self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
-        self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
-        self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
-      
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # set color HSV
-        self.HSV = {
-            "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])],
-            # "yellow": [np.array([26, 43, 46]), np.array([34, 255, 255])],
-            "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 ultraArm
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the ultraArm
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the ultraArm
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-    # publish marker
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-    # pump_control pi
-    def gpio_status(self, flag):
-        if flag:
-            self.GPIO.output(20, 0)
-            self.GPIO.output(21, 0)
-        else:
-            self.GPIO.output(20, 1)
-            self.GPIO.output(21, 1)
-    
-    # 开启吸泵 m5
-    def pump_on(self):
-        self.ua.set_gpio_state(0)
-
-    # 停止吸泵 m5
-    def pump_off(self):
-        self.ua.set_gpio_state(1)
-
-    # Grasping motion
-    def move(self, x, y, color):
-        # send Angle to move ultraArm
-        print('color-->', color)
-        self.ua.set_angles(self.move_angles[0], 20)
-        time.sleep(3)
-
-        # send coordinates to move ultraArm
-        self.ua.set_coords([x, -y, 58.84], 20)
-        time.sleep(1.5)
-        self.ua.set_coords([x, -y, 21.8], 20)
-        time.sleep(2)
-
-        # open pump
-        self.pump_on()
-        time.sleep(1.5)
-
-        self.ua.set_angle(2, 0, 30)
-        time.sleep(0.3)
-        self.ua.set_angle(3, 0, 30)
-        time.sleep(1)
-
-        self.ua.set_coords(self.move_coords[color], 30)
-        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(7)
-       
-        # close pump
-        
-        self.pump_off()
-        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.ua.set_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 ultraArm
-    def run(self):
-        self.ua = ultraArm(self.robot_m5, 115200)
-        self.ua.go_zero()
-        self.ua.set_angles([19.48, 0.0, 0.0], 40)
-        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 ultraArm
-    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 ultraArm
-    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
-
-    # detect cube color
-    def color_detect(self, img):
-        # set the arrangement of color'HSV
-        x = y = 0
-        for mycolor, item in self.HSV.items():
-            # print("mycolor:",mycolor)
-            redLower = np.array(item[0])
-            redUpper = np.array(item[1])
-
-            # transfrom the img to model of gray
-            hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-            # print("hsv",hsv)
-
-            # wipe off all color expect color in range
-            mask = cv2.inRange(hsv, item[0], item[1])
-
-            # a etching operation on a picture to remove edge roughness
-            erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2)
-
-            # the image for expansion operation, its role is to deepen the color depth in the picture
-            dilation = cv2.dilate(erosion, np.ones(
-                (1, 1), np.uint8), iterations=2)
-
-            # adds pixels to the image
-            target = cv2.bitwise_and(img, img, mask=dilation)
-
-            # the filtered image is transformed into a binary image and placed in binary
-            ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY)
-
-            # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected
-            contours, hierarchy = cv2.findContours(
-                dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-            if len(contours) > 0:
-                # do something about misidentification
-                boxes = [
-                    box
-                    for box in [cv2.boundingRect(c) for c in contours]
-                    if min(img.shape[0], img.shape[1]) / 10
-                    < min(box[2], box[3])
-                    < min(img.shape[0], img.shape[1]) / 1
-                ]
-                if boxes:
-                    for box in boxes:
-                        x, y, w, h = box
-                    # find the largest object that fits the requirements
-                    c = max(contours, key=cv2.contourArea)
-                    # get the lower left and upper right points of the positioning object
-                    x, y, w, h = cv2.boundingRect(c)
-                    # locate the target by drawing rectangle
-                    cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2)
-                    # calculate the rectangle center
-                    x, y = (x*2+w)/2, (y*2+h)/2
-                    # calculate the real coordinates of ultraArm relative to the target
-                    if mycolor == "red":
-                        self.color = 0
-                    elif mycolor == "green":
-                        self.color = 1
-                    elif mycolor == "cyan":
-                        self.color = 2
-                    else:
-                        self.color = 3
-
-        if abs(x) + abs(y) > 0:
-            return x, y
-        else:
-            return None
-
-if __name__ == "__main__":
-
-    # open the camera
-    cap_num = 0
-    cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
-    if not cap.isOpened():
-        cap.open()
-    # init a class of Object_detect
-    detect = Object_detect()
-    # init ultraArm
-    detect.run()
-
-    _init_ = 20  
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-       # read camera
-        _, frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-        if _init_ > 0:
-            _init_ -= 1
-            continue
-
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1)/20.0,
-                (detect.sum_y1)/20.0,
-                (detect.sum_x2)/20.0,
-                (detect.sum_y2)/20.0,
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and ultraArm
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                continue
-        elif nparams == 10:
-            nparams += 1
-            # calculate and set params of calculating real coord between cube and ultraArm
-            detect.set_params(
-                (detect.sum_x1+detect.sum_x2)/20.0,
-                (detect.sum_y1+detect.sum_y2)/20.0,
-                abs(detect.sum_x1-detect.sum_x2)/10.0 +
-                abs(detect.sum_y1-detect.sum_y2)/10.0
-            )
-            print("ok")
-            continue
-
-        # get detect result
-        detect_result = detect.color_detect(frame)
-        if detect_result is None:
-            cv2.imshow("figure", frame)
-            continue
-        else:
-            x, y = detect_result
-            # calculate real coord between cube and ultraArm
-            real_x, real_y = detect.get_position(x, y)
-            if num == 20:
-                detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0)
-                detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color)
-                num = real_sx = real_sy = 0
-
-            else:
-                num += 1
-                real_sy += real_y
-                real_sx += real_x
-
-        cv2.imshow("figure", frame)
-
-        # close the window
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            cap.release()
-            cv2.destroyAllWindows()
-            sys.exit()
\ No newline at end of file
diff --git a/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_img_folder_opt.py b/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_img_folder_opt.py
deleted file mode 100755
index ecef81d..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/combine_detect_obj_img_folder_opt.py
+++ /dev/null
@@ -1,595 +0,0 @@
-#!/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.ultraArm import ultraArm
-
-IS_CV_4 = cv2.__version__[0] == '4'
-__version__ = "1.0"  # Adaptive seeed
-
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x = 148, 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.ua = None
-        # 移动角度
-        self.move_angles = [
-            [0.0, 0.0, 0.0],  # init the point
-            [19.48, 0.0, 0.0],  # point to grab
-        ]
-
-        # 移动坐标
-        self.move_coords = [
-            [121.35, 127.48, 120.0],  # above the red bucket
-            [217.09, 113.01, 98.36], # above the green bucket
-            [107.54, -171.23, 117.11], # above the blue bucket
-            [-6.91, -175.86, 120.0], # above the gray bucket     
-        ]
-
-        # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed       
-        self.raspi = False
-        self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
-        self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
-        self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
-        self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
-    
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-
-        # use to calculate coord between cube and mycobot
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the mycobot
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mycobot
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-        self.cache_x = self.cache_y = 0
-
-    # publish marker
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-    
-    # 开启吸泵 m5
-    def pump_on(self):
-        self.ua.set_gpio_state(0)
-
-    # 停止吸泵 m5
-    def pump_off(self):
-        self.ua.set_gpio_state(1)
-
-    # Grasping motion
-    def move(self, x, y, color):
-        # send Angle to move mypal260
-        self.ua.set_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.ua.set_coords([x, -y, 58.84], 20)
-        time.sleep(1.5)
-        self.ua.set_coords([x, -y, 21.8], 20)
-        time.sleep(2)
-
-        # open pump
-        self.pump_on()
-        time.sleep(1.5)
-
-        self.ua.set_angle(2, 0, 30)
-        time.sleep(0.3)
-        self.ua.set_angle(3, 0, 30)
-        time.sleep(2)
-
-        self.ua.set_coords(self.move_coords[color], 30)
-        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(7)
-
-        # close pump
-        self.pump_off()
-        time.sleep(6)
-
-        self.ua.set_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):
-        self.ua = ultraArm(self.robot_m5, 115200) 
-        self.ua.go_zero()
-        self.ua.set_angles([19.48, 0.0, 0.0], 40)
-        time.sleep(3)
-
-    # draw aruco
-    def draw_marker(self, img, x, y):
-        # draw rectangle on img
-        cv2.rectangle(
-            img,
-            (x - 20, y - 20),
-            (x + 20, y + 20),
-            (0, 255, 0),
-            thickness=2,
-            lineType=cv2.FONT_HERSHEY_COMPLEX,
-        )
-        # add text on rectangle
-        cv2.putText(
-            img,
-            "({},{})".format(x, y),
-            (x, y),
-            cv2.FONT_HERSHEY_COMPLEX_SMALL,
-            1,
-            (243, 0, 0),
-            2,
-        )
-
-    # get points of two aruco
-    def get_calculate_params(self, img):
-        # Convert the image to a gray image
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        # Detect ArUco marker.
-        corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
-            gray, self.aruco_dict, parameters=self.aruco_params)
-
-        """
-        Two Arucos must be present in the picture and in the same order.
-        There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
-        Determine the center of the aruco by the four corners of the aruco.
-        """
-        if len(corners) > 0:
-            if ids is not None:
-                if len(corners) <= 1 or ids[0] == 1:
-                    return None
-                x1 = x2 = y1 = y2 = 0
-                point_11, point_21, point_31, point_41 = corners[0][0]
-                x1, y1 = int(
-                    (point_11[0] + point_21[0] + point_31[0] + point_41[0]) /
-                    4.0), int(
-                        (point_11[1] + point_21[1] + point_31[1] + point_41[1])
-                        / 4.0)
-                point_1, point_2, point_3, point_4 = corners[1][0]
-                x2, y2 = int(
-                    (point_1[0] + point_2[0] + point_3[0] + point_4[0]) /
-                    4.0), int(
-                        (point_1[1] + point_2[1] + point_3[1] + point_4[1]) /
-                        4.0)
-                return x1, x2, y1, y2
-        return None
-
-    # set camera clipping parameters
-    def set_cut_params(self, x1, y1, x2, y2):
-        self.x1 = int(x1)
-        self.y1 = int(y1)
-        self.x2 = int(x2)
-        self.y2 = int(y2)
-        print(self.x1, self.y1, self.x2, self.y2)
-
-    # set parameters to calculate the coords between cube and mycobot
-    def set_params(self, c_x, c_y, ratio):
-        self.c_x = c_x
-        self.c_y = c_y
-        self.ratio = 220.0 / ratio
-
-    # calculate the coords between cube and mycobot
-    def get_position(self, x, y):
-        return ((y - self.c_y) * self.ratio +
-                self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y)
-
-    """
-    Calibrate the camera according to the calibration parameters.
-    Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
-    If two ARuco values have been calculated, clip the video.
-    """
-
-    def transform_frame(self, frame):
-        # enlarge the image by 1.5 times
-        fx = 1.5
-        fy = 1.5
-        frame = cv2.resize(frame, (0, 0),
-                           fx=fx,
-                           fy=fy,
-                           interpolation=cv2.INTER_CUBIC)
-        if self.x1 != self.x2:
-            # the cutting ratio here is adjusted according to the actual situation
-            frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15),
-                          int(self.x1 * 0.7):int(self.x2 * 1.15)]
-        return frame
-
-    # according the class_id to get object name
-    def id_class_name(self, class_id):
-        for key, value in self.labels.items():
-            if class_id == int(key):
-                return value
-
-    # detect object
-    def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection):
-        i = 0
-        MIN_MATCH_COUNT = 5
-        # sift = cv2.xfeatures2d.SIFT_create()
-
-        # find the keypoints and descriptors with SIFT
-        # kp = []
-        # des = []
-        kp = kp_list
-        des = desc_list
-
-        # for i in goal:
-        #     kp0, des0 = sift.detectAndCompute(i, None)
-        #     kp.append(kp0)
-        #     des.append(des0)
-
-        # kp1, des1 = sift.detectAndCompute(goal, None)
-        # kp2, des2 = sift.detectAndCompute(img, None)
-        kp2, des2 = kp_img, desc_img
-
-        # FLANN parameters
-        FLANN_INDEX_KDTREE = 0
-        index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
-        search_params = dict(checks=50)  # or pass empty dictionary
-        flann = cv2.FlannBasedMatcher(index_params, search_params)
-
-        x, y = 0, 0
-        try:
-            for i in range(len(des)):
-                matches = flann.knnMatch(des[i], des2, k=2)
-                # store all the good matches as per Lowe's ratio test.  根据Lowe比率测试存储所有良好匹配项。
-                good = []
-                for m, n in matches:
-                    if m.distance < 0.7 * n.distance:
-                        good.append(m)
-
-                # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时
-                if len(good) > MIN_MATCH_COUNT:
-
-                    # extract corresponding point pairs from matching 从匹配中提取出对应点对
-                    # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引
-                    src_pts = np.float32([kp[i][m.queryIdx].pt
-                                          for m in good]).reshape(-1, 1, 2)
-                    dst_pts = np.float32([kp2[m.trainIdx].pt
-                                          for m in good]).reshape(-1, 1, 2)
-
-                    # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵
-                    M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,
-                                                 5.0)
-                    matchesMask = mask.ravel().tolist()
-                    # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置
-                    h, w, d = goal[i].shape
-                    pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1],
-                                      [w - 1, 0]]).reshape(-1, 1, 2)
-                    dst = cv2.perspectiveTransform(pts, M)
-                    coord = (dst[0][0] + dst[1][0] + dst[2][0] +
-                              dst[3][0]) / 4.0
-                    connection.send((DRAW_COORDS, coord))
-                    # cv2.putText(img, "{}".format(coord), (50, 60),
-                    #         fontFace=None, fontScale=1,
-                    #         color=(0, 255, 0), lineType=1)
-                    print(format(dst[0][0][0]))
-                    x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] +
-                         dst[3][0][0]) / 4.0
-                    y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] +
-                         dst[3][0][1]) / 4.0
-
-                    # bound box  绘制边框
-                    # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
-                    connection.send((DRAW_RECT, dst))
-                    # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA)
-        except Exception as e:
-            pass
-
-        if x + y > 0:
-            return x, y
-        else:
-            return None
-
-# The path to save the image folder
-def parse_folder(folder):
-    restore = []
-    path1 = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/ai_ultraarm/' + folder
-    path2 = '/home/h/catkin_ws/src/mycobot_ros/mycobot_ai/ai_ultraarm/' + folder
-
-    if os.path.exists(path1):
-        path = path1
-    elif os.path.exists(path2):
-        path = path2
-
-    for i, j, k in os.walk(path):
-        for l in k:
-            restore.append(cv2.imread(folder + '/{}'.format(l)))
-    return restore
-
-def compute_keypoints_and_descriptors(sift, images_lists):
-    kp_list = []
-    desc_list = []
-    for images in images_lists:
-        kp_tmp = []
-        desc_tmp = []
-        for img in images:
-            kp, desc = sift.detectAndCompute(img, None)
-            kp_tmp.append(kp)
-            desc_tmp.append(desc)
-        kp_list.append(kp_tmp)
-        desc_list.append(desc_tmp)
-
-    return kp_list, desc_list
-
-GET_FRAME = 1
-STOP_PROCESSING = 2
-DRAW_COORDS = 3
-DRAW_RECT = 4
-CLEAR_DRAW = 5
-CROP_FRAME = 6
-
-def get_frame(connection):
-    connection.send(GET_FRAME)
-    frame = connection.recv()
-    return frame
-
-def process_transform_frame(frame, x1, y1, x2, y2):
-    # enlarge the image by 1.5 times
-    fx = 1.5
-    fy = 1.5
-    frame = cv2.resize(frame, (0, 0),
-                        fx=fx,
-                        fy=fy,
-                        interpolation=cv2.INTER_CUBIC)
-#    if x1 != x2:
-        # the cutting ratio here is adjusted according to the actual situation
-#        frame = frame[int(y2 * 0.2):int(y1 * 1.15),
-#                        int(x1 * 0.7):int(x2 * 1.15)]
-    return frame
-
-def process_display_frame(connection):
-    cap_num = 0
-    coord = None
-    dst = None
-    x1 = 0
-    y1 = 0
-    x2 = 0
-    y2 = 0
-    cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
-    if not cap.isOpened():
-        cap.open()
-    while cv2.waitKey(1) < 0:
-        _, frame = cap.read()
-        frame = process_transform_frame(frame, x1, y1, x2, y2)
-        if connection.poll():
-            request = connection.recv()
-            if request == GET_FRAME:
-                connection.send(frame)
-            elif request == CLEAR_DRAW:
-                coord = None
-                dst = None
-            elif type(request) is tuple:
-                if request[0] == DRAW_COORDS:
-                    coord = request[1]
-                elif request[0] == DRAW_RECT:
-                    dst = request[1]
-                elif request[0] == CROP_FRAME:
-                    x1 = request[1]
-                    y1 = request[2]
-                    x2 = request[3]
-                    y2 = request[4]
-
-        if not coord is None:
-            cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None,
-                    fontScale=1, color=(0, 255, 0), lineType=1)
-        if not dst is None:
-            frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
-        cv2.imshow("figure", frame)
-        time.sleep(0.04)
-    connection.send(STOP_PROCESSING)
-
-def run():
-    parent_conn, child_conn = Pipe()
-    child = Process(target = process_display_frame, args=(child_conn,))
-    child.start()
-
-    res_queue = [[], [], [], []]
-    res_queue[0] = parse_folder('res/red')
-    res_queue[1] = parse_folder('res/green')
-    res_queue[2] = parse_folder('res/blue')
-    res_queue[3] = parse_folder('res/gray')
-
-    sift = cv2.xfeatures2d.SIFT_create()
-    kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue)
-
-    # init a class of Object_detect
-    detect = Object_detect()
-
-    # init mycobot
-    detect.run()
-
-    # _init_ = 20  #
-    init_num = 0
-    nparams = 0
-    # num = 0
-    # real_sx = real_sy = 0
-    while True:
-        start_time = time.time()
-        if parent_conn.poll():
-            data = parent_conn.recv()
-            if data == STOP_PROCESSING:
-                break
-        # read camera
-        frame = get_frame(parent_conn)
-        # deal img
-        #frame = detect.transform_frame(frame)
-
-        # if _init_ > 0:
-        #     _init_ -= 1
-        #     continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                # cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1) / 20.0,
-                (detect.sum_y1) / 20.0,
-                (detect.sum_x2) / 20.0,
-                (detect.sum_y2) / 20.0,
-            )
-            parent_conn.send((CROP_FRAME,
-                (detect.sum_x1) / 20.0,
-                (detect.sum_y1) / 20.0,
-                (detect.sum_x2) / 20.0,
-                (detect.sum_y2) / 20.0))
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                # cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                print ("ok")
-                continue
-        elif nparams == 10:
-            nparams += 1
-            # calculate and set params of calculating real coord between cube and mycobot
-            detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0,
-                              (detect.sum_y1 + detect.sum_y2) / 20.0,
-                              abs(detect.sum_x1 - detect.sum_x2) / 10.0 +
-                              abs(detect.sum_y1 - detect.sum_y2) / 10.0)
-            print("ok")
-            continue
-
-        # get detect result
-        kp_img, desc_img = sift.detectAndCompute(frame, None)
-        frame = get_frame(parent_conn)
-        for i, v in enumerate(res_queue):
-            # HACK: to update frame every time
-            detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn)
-            if detect_result:
-                x, y = detect_result
-                # calculate real coord between cube and mycobot
-                real_x, real_y = detect.get_position(x, y)
-                detect.color = i
-                detect.pub_marker(real_x / 1000.0, real_y / 1000.0)
-                detect.decide_move(real_x, real_y, detect.color)
-                # if num == 5:
-                #     detect.color = i
-                #     detect.pub_marker(real_sx / 5.0 / 1000.0,
-                #                       real_sy / 5.0 / 1000.0)
-                #     detect.decide_move(real_sx / 5.0, real_sy / 5.0,
-                #                        detect.color)
-                #     num = real_sx = real_sy = 0
-                # else:
-                #     num += 1
-                #     real_sy += real_y
-                #     real_sx += real_x
-                parent_conn.send(CLEAR_DRAW)
-
-        # cv2.imshow("figure", frame)
-        time.sleep(0.05)
-        end_time = time.time()
-        print("loop_time = ", end_time - start_time)
-
-        # close the window
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            # cap.release()
-            cv2.destroyAllWindows()
-            sys.exit()
-
-    child.join()
-    
-
-if __name__ == "__main__":
-    run()
-    # Object_detect().take_photo()
-    # Object_detect().cut_photo()
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_encode.py b/mycobot_ai/ai_ultraarm/scripts/detect_encode.py
deleted file mode 100755
index 7bbe645..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_encode.py
+++ /dev/null
@@ -1,248 +0,0 @@
-# encoding: UTF-8
-#!/usr/bin/env python2
-import cv2 as cv
-import os
-import numpy as np
-import time
-import rospy
-from visualization_msgs.msg import Marker
-from moving_utils import Movement
-
-# y轴偏移量
-pump_y = -55
-# x轴偏移量
-pump_x = 15
-
-
-class Detect_marker(Movement):
-    def __init__(self):
-        super(Detect_marker, self).__init__()
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-
-        # which robot
-        self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
-        self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
-        self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
-        self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
-        self.raspi = False
-        if "dev" in self.robot_m5:
-            self.Pin = [2, 5]
-        elif "dev" in self.robot_wio:
-            self.Pin = [20, 21]
-            for i in self.move_coords:
-                i[2] -= 20
-        elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
-            import RPi.GPIO as GPIO
-            self.GPIO = GPIO
-            GPIO.setwarnings(False)
-            GPIO.setmode(GPIO.BCM)
-            GPIO.setup(20, GPIO.OUT)
-            GPIO.setup(21, GPIO.OUT)
-            self.raspi = True
-        if self.raspi:
-            self.gpio_status(False)
-        else:
-            self.pub_pump(False, self.Pin)
-        # Creating a Camera Object
-        cap_num = 0
-        self.cap = cv.VideoCapture(cap_num, cv.CAP_V4L)
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv.aruco.Dictionary_get(cv.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv.aruco.DetectorParameters_create()
-        self.calibrationParams = cv.FileStorage(
-            "calibrationFileName.xml", cv.FILE_STORAGE_READ)
-        # Get distance coefficient.
-        self.dist_coeffs = self.calibrationParams.getNode("distCoeffs").mat()
-
-        height = self.cap.get(4)
-        focal_length = width = self.cap.get(3)
-        center = [width / 2, height / 2]
-        # Calculate the camera matrix.
-        self.camera_matrix = np.array(
-            [
-                [focal_length, 0, center[0]],
-                [0, focal_length, center[1]],
-                [0, 0, 1],
-            ],
-            dtype=np.float32,
-        )
-        # init a node and a publisher
-        rospy.init_node("encode_marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1
-        self.marker.color.r = 0.3
-        self.marker.color.g = 0.3
-        self.marker.color.b = 0.3
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-    # Grasping motion
-    def move(self, x, y):
-        if self.raspi:
-            coords = [
-                [145.6, -64.9, 285.2, 179.88, 7.67, 179],
-                [130.1, -155.6, 243.9, 178.99, 5.38, -179.9]
-            ]
-        else:
-            coords = [
-                [135.0, -65.5, 280.1, 178.99, 5.38, -179.9],
-                [136.1, -141.6, 243.9, 178.99, 5.38, -179.9]
-            ]
-
-        # publish marker
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = (coords[0][0]-x)/1000.0
-        self.marker.pose.position.y = (coords[0][1]-y)/1000.0
-        self.pub.publish(self.marker)
-
-        # send coordinates to move mycobot
-        self.pub_coords(coords[0], 30, 1)
-        time.sleep(2)
-        self.pub_coords([coords[0][0]-x, coords[0][1]-y,
-                        240, 178.99, 5.38, -179.9], 25, 1)
-        time.sleep(2)
-        self.pub_coords([coords[0][0]-x, coords[0][1]-y,
-                        200, 178.99, 5.38, -179.9], 25, 1)
-        time.sleep(2)
-        if "dev" in self.robot_m5 or self.raspi:
-            self.pub_coords([coords[0][0]-x, coords[0][1]-y,
-                            90, 178.99, 5.38, -179.9], 25, 1)
-        elif "dev" in self.robot_wio:
-            self.pub_coords([coords[0][0]-x+20, coords[0][1] -
-                            y-10, 70, 178.99, 5.38, -179.9], 25, 1)
-        time.sleep(2)
-        if self.raspi:
-            self.gpio_status(True)
-        else:
-            self.pub_pump(True, self.Pin)
-        time.sleep(1)
-        self.pub_coords(coords[0], 30, 1)
-        time.sleep(3)
-        self.pub_coords(coords[1], 30, 1)
-        time.sleep(2)
-        if self.raspi:
-            self.gpio_status(False)
-        else:
-            self.pub_pump(False, self.Pin)
-        # publish marker
-        time.sleep(1)
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = coords[1][0]/1000.0
-        self.marker.pose.position.y = coords[1][1]/1000.0
-        self.pub.publish(self.marker)
-
-        self.pub_coords(coords[0], 30, 1)
-        time.sleep(2)
-
-    def gpio_status(self, flag):
-        if flag:
-            self.GPIO.output(20, 0)
-            self.GPIO.output(21, 0)
-        else:
-            self.GPIO.output(20, 1)
-            self.GPIO.output(21, 1)
-
-    # decide whether grab cube
-    def decide_move(self, x, y):
-
-        print(x, y)
-        # detect the cube status move or run
-        if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5:  # mm
-            self.cache_x, self.cache_y = x, y
-            return
-        else:
-            self.cache_x = self.cache_y = 0
-            if "dev" in self.robot_jes:
-                if x > -20:
-                    y += 10
-                if y > -25:
-                    x -= 5
-                x += 10
-
-            self.move(x, y)
-
-    # init mycobot
-    def init_mycobot(self):
-
-        for _ in range(5):
-            print _
-            self.pub_coords([145.6, -64.9, 285.2, 179.88, 7.67, 179], 20, 1)
-            time.sleep(0.5)
-
-    def run(self):
-        global pump_y, pump_x
-        self.init_mycobot()
-        num = sum_x = sum_y = 0
-        while cv.waitKey(1) < 0:
-            success, img = self.cap.read()
-            if not success:
-                print("It seems that the image cannot be acquired correctly.")
-                break
-
-            # transfrom the img to model of gray
-            gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)
-            # Detect ArUco marker.
-            corners, ids, rejectImaPoint = cv.aruco.detectMarkers(
-                gray, self.aruco_dict, parameters=self.aruco_params
-            )
-
-            if len(corners) > 0:
-                if ids is not None:
-                    # get informations of aruco
-                    ret = cv.aruco.estimatePoseSingleMarkers(
-                        corners, 0.03, self.camera_matrix, self.dist_coeffs
-                    )
-                    # rvec:rotation offset,tvec:translation deviator
-                    (rvec, tvec) = (ret[0], ret[1])
-                    (rvec - tvec).any()
-                    xyz = tvec[0, 0, :]
-                    # calculate the coordinates of the aruco relative to the pump
-                    xyz = [round(xyz[0]*1000+pump_y, 2), round(xyz[1]
-                                                               * 1000+pump_x, 2), round(xyz[2]*1000, 2)]
-
-                    for i in range(rvec.shape[0]):
-                        # draw the aruco on img
-                        cv.aruco.drawDetectedMarkers(img, corners)
-                        cv.aruco.drawAxis(
-                            img,
-                            self.camera_matrix,
-                            self.dist_coeffs,
-                            rvec[i, :, :],
-                            tvec[i, :, :],
-                            0.03,
-                        )
-
-                        if num < 40:
-                            if self.raspi:
-                                sum_x -= 30
-                            sum_x += xyz[1]
-                            sum_y += xyz[0]
-                            num += 1
-                        elif num == 40:
-                            self.decide_move(sum_x/40.0, sum_y/40.0)
-                            num = sum_x = sum_y = 0
-
-            cv.imshow("encode_image", img)
-
-
-if __name__ == "__main__":
-    detect = Detect_marker()
-    detect.run()
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_color.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_color.py
deleted file mode 100755
index cc9124e..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_color.py
+++ /dev/null
@@ -1,461 +0,0 @@
-# -*- 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,sys
-import rospy
-from visualization_msgs.msg import Marker   
-from pymycobot.mypalletizer import MyPalletizer
-from moving_utils import Movement
-
-
-IS_CV_4 = cv2.__version__[0] == '4'
-__version__ = "1.0"
-# Adaptive seeed
-
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x = 160, camera_y = 10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-
-        # declare mypal260
-        self.mc = None
-
-        # 移动角度
-        self.move_angles = [
-            [0, 0, 0, 0],  # init the point
-            [-29.0, 5.88, -4.92, -76.28],  # point to grab
-            [17.4, -10.1, -87.27, 5.8, -2.02, 15],  # point to grab
-        ]
-
-        # 移动坐标
-        self.move_coords = [
-            [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]
-        self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
-        self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
-        self.raspi = False
-        if "dev" in self.robot_m5:
-            self.Pin = [2, 5]
-        elif "dev" in self.robot_wio:
-            self.Pin = [20, 21]
-            for i in self.move_coords:
-                i[2] -= 20
-        elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
-            import RPi.GPIO as GPIO
-            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)
-        self.Pin = [2, 5]
-
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # set color HSV
-        self.HSV = {
-            "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])],
-            "red": [np.array([0, 43, 46]), np.array([8, 255, 255])],
-            "green": [np.array([35, 43, 46]), np.array([77, 255, 255])],
-            "blue": [np.array([100, 43, 46]), np.array([124, 255, 255])],
-            "cyan": [np.array([78, 43, 46]), np.array([99, 255, 255])],
-        }
-        # use to calculate coord between cube and mypal260
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the mypal260
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mypal260
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-    # publish marker
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-    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)
-
-    # Grasping motion
-    def move(self, x, y, color):
-        # send Angle to move mypal260
-        print(color)
-        self.mc.send_angles(self.move_angles[0], 20)
-        time.sleep(3)
-
-        # send coordinates to move mypal260
-        self.mc.send_coords([x, y, 160, 0], 20, 0)
-        time.sleep(1.5)
-        self.mc.send_coords([x, y, 90, 0], 20, 0)
-        time.sleep(1.5)
-
-        # open pump
-        if self.raspi:
-            self.gpio_status(True)
-        else:
-            self.pub_pump(True, self.Pin)
-        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 self.raspi:
-            self.gpio_status(False)
-        else:
-            self.pub_pump(False, self.Pin)
-        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)
-        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):
-        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( 
-            img,
-            (x - 20, y - 20),
-            (x + 20, y + 20),
-            (0, 255, 0),
-            thickness=2,
-            lineType=cv2.FONT_HERSHEY_COMPLEX,
-        )
-        # add text on rectangle
-        cv2.putText(img, "({},{})".format(x, y), (x, y),
-                    cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (243, 0, 0), 2,)
-
-    # get points of two aruco
-    def get_calculate_params(self, img):
-        # Convert the image to a gray image
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        # Detect ArUco marker.
-        corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
-            gray, self.aruco_dict, parameters=self.aruco_params
-        )
-
-        """
-        Two Arucos must be present in the picture and in the same order.
-        There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
-        Determine the center of the aruco by the four corners of the aruco.
-        """
-        if len(corners) > 0:
-            if ids is not None:
-                if len(corners) <= 1 or ids[0] == 1:
-                    return None
-                x1 = x2 = y1 = y2 = 0
-                point_11, point_21, point_31, point_41 = corners[0][0]
-                x1, y1 = int((point_11[0] + point_21[0] + point_31[0] + point_41[0]) / 4.0), int(
-                    (point_11[1] + point_21[1] + point_31[1] + point_41[1]) / 4.0)
-                point_1, point_2, point_3, point_4 = corners[1][0]
-                x2, y2 = int((point_1[0] + point_2[0] + point_3[0] + point_4[0]) / 4.0), int(
-                    (point_1[1] + point_2[1] + point_3[1] + point_4[1]) / 4.0)
-                return x1, x2, y1, y2
-        return None
-
-    # set camera clipping parameters
-    def set_cut_params(self, x1, y1, x2, y2):
-        self.x1 = int(x1)
-        self.y1 = int(y1)
-        self.x2 = int(x2)
-        self.y2 = int(y2)
-        print(self.x1, self.y1, self.x2, self.y2)
-
-    # set parameters to calculate the coords between cube and mypal260
-    def set_params(self, c_x, c_y, ratio):
-        self.c_x = c_x
-        self.c_y = c_y
-        self.ratio = 220.0/ratio
-
-    # calculate the coords between cube and mypal260
-    def get_position(self, x, y):
-        return ((y - self.c_y)*self.ratio + self.camera_x), ((x - self.c_x)*self.ratio + self.camera_y)
-
-    """
-    Calibrate the camera according to the calibration parameters.
-    Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
-    If two ARuco values have been calculated, clip the video.
-    """
-    def transform_frame(self, frame):
-        # enlarge the image by 1.5 times
-        fx = 1.5
-        fy = 1.5
-        frame = cv2.resize(frame, (0, 0), fx=fx, fy=fy,
-                           interpolation=cv2.INTER_CUBIC)
-        if self.x1 != self.x2:
-            # the cutting ratio here is adjusted according to the actual situation
-            frame = frame[int(self.y2*0.2):int(self.y1*1.15),
-                          int(self.x1*0.7):int(self.x2*1.15)]
-        return frame
-
-    # detect cube color
-    def color_detect(self, img):
-        # set the arrangement of color'HSV
-        x = y = 0
-        for mycolor, item in self.HSV.items():
-            # print("mycolor:",mycolor)
-            redLower = np.array(item[0])
-            redUpper = np.array(item[1])
-
-            # transfrom the img to model of gray
-            hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-            # print("hsv",hsv)
-
-            # wipe off all color expect color in range
-            mask = cv2.inRange(hsv, item[0], item[1])
-
-            # a etching operation on a picture to remove edge roughness
-            erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2)
-
-            # the image for expansion operation, its role is to deepen the color depth in the picture
-            dilation = cv2.dilate(erosion, np.ones(
-                (1, 1), np.uint8), iterations=2)
-
-            # adds pixels to the image
-            target = cv2.bitwise_and(img, img, mask=dilation)
-
-            # the filtered image is transformed into a binary image and placed in binary
-            ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY)
-
-            # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected
-            contours, hierarchy = cv2.findContours(
-                dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-            if len(contours) > 0:
-                # do something about misidentification
-                boxes = [
-                    box
-                    for box in [cv2.boundingRect(c) for c in contours]
-                    if min(img.shape[0], img.shape[1]) / 10
-                    < min(box[2], box[3])
-                    < min(img.shape[0], img.shape[1]) / 1
-                ]
-                if boxes:
-                    for box in boxes:
-                        x, y, w, h = box
-                    # find the largest object that fits the requirements
-                    c = max(contours, key=cv2.contourArea)
-                    # get the lower left and upper right points of the positioning object
-                    x, y, w, h = cv2.boundingRect(c)
-                    # locate the target by drawing rectangle
-                    cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2)
-                    # calculate the rectangle center
-                    x, y = (x*2+w)/2, (y*2+h)/2
-                    # calculate the real coordinates of mypal260 relative to the target
-                    
-                    if mycolor == "red":
-                        self.color = 0
-                    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 mypal260
-    detect.run()
-
-    _init_ = 20  
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-       # read camera
-        _, frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-        if _init_ > 0:
-            _init_ -= 1
-            continue
-
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1)/20.0,
-                (detect.sum_y1)/20.0,
-                (detect.sum_x2)/20.0,
-                (detect.sum_y2)/20.0,
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and mypal260
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                continue
-        elif nparams == 10:
-            nparams += 1
-            # calculate and set params of calculating real coord between cube and mypal260
-            detect.set_params(
-                (detect.sum_x1+detect.sum_x2)/20.0,
-                (detect.sum_y1+detect.sum_y2)/20.0,
-                abs(detect.sum_x1-detect.sum_x2)/10.0 +
-                abs(detect.sum_y1-detect.sum_y2)/10.0
-            )
-            print("ok")
-            continue
-
-        # get detect result
-        detect_result = detect.color_detect(frame)
-        if detect_result is None:
-            cv2.imshow("figure", frame)
-            continue
-        else:
-            x, y = detect_result
-            # calculate real coord between cube and mypal260
-            real_x, real_y = detect.get_position(x, y)
-            if num == 20:
-                detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0)
-                detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color)
-                num = real_sx = real_sy = 0
-
-            else:
-                num += 1
-                real_sy += real_y
-                real_sx += real_x
-
-        cv2.imshow("figure", frame)
-
-        # close the window
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            cap.release()
-            cv2.destroyAllWindows()
-            sys.exit()
\ No newline at end of file
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_color_wio.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_color_wio.py
deleted file mode 100755
index fa7b0bf..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_color_wio.py
+++ /dev/null
@@ -1,393 +0,0 @@
-#encoding:utf-8
-
-from tokenize import Pointfloat
-import cv2
-import numpy as np
-import time
-import json
-import os
-import rospy
-from visualization_msgs.msg import Marker
-
-from moving_utils import Movement
-
-IS_CV_4 = cv2.__version__[0] == '4'
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x=150, camera_y=-10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 =0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # set color HSV
-        self.HSV = {
-            "yellow": [np.array([11, 115, 70]), np.array([40, 255, 245])],
-            "red": [np.array([0, 43, 46]), np.array([8, 255, 255])],
-		}
-        # use to calculate coord between cube and mycobot
-        self.sum_x1= self.sum_x2= self.sum_y2= self.sum_y1= 0
-        # The coordinates of the grab center point relative to the mycobot
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mycobot
-        self.c_x, self.c_y = 0,0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker 
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-    # publish marker
-    def pub_marker(self, x, y , z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-	    
-
-    # Grasping motion
-    def move(self, x,y,color):
-        angles = [
-           [-7.11, -6.94, -55.01, -24.16, 0, -38.84],  # init the point
-            [-1.14, -10.63, -87.8, 9.05, -3.07, -37.7],  # point to grab
-            [17.4, -10.1, -87.27, 5.8, -2.02, -37.7],  # point to grab
-        ]
-
-        coords = [
-        [106.1, -141.6, 240.9, -173.34, -8.15, -83.11],  # above the red bucket
-        [208.2, -127.8, 246.9, -157.51, -17.5, -71.18],  # above the green bucket
-        [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],
-
-        ]
-
-        # send Angle to move mycobot
-        self.pub_angles(angles[0], 20)
-        time.sleep(1.5)
-        self.pub_angles(angles[1], 20)
-        time.sleep(1.5)
-        self.pub_angles(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, 40,  -178.9, -1.57, -25.95], 20, 1)
-        time.sleep(1.5)
-        # open pump
-        self.pub_pump(True,[20,21])
-        time.sleep(0.5)
-        self.pub_angles(angles[2], 20)
-        time.sleep(3)
-        self.pub_marker(coords[2][0]/1000.0, coords[2][1]/1000.0, coords[2][2]/1000.0)
-        
-        self.pub_angles(angles[1], 20)
-        time.sleep(1.5)
-        self.pub_marker(coords[3][0]/1000.0, coords[3][1]/1000.0, coords[3][2]/1000.0)
-        
-        self.pub_angles(angles[0], 20)
-        time.sleep(1.5)
-        self.pub_marker(coords[4][0]/1000.0, coords[4][1]/1000.0, coords[4][2]/1000.0)
-        
-        self.pub_coords(coords[color], 20, 1)
-        self.pub_marker(coords[color][0]/1000.0, coords[color][1]/1000.0, coords[color][2]/1000.0)
-        time.sleep(2)
-        # close pump
-        self.pub_pump(False,[20,21])
-        if color==1:
-           self.pub_marker(coords[color][0]/1000.0+0.04, coords[color][1]/1000.0-0.02)
-        elif color==0:
-           self.pub_marker(coords[color][0]/1000.0+0.03, coords[color][1]/1000.0)
-        self.pub_angles(angles[0], 20)
-        time.sleep(3)
-
-
-    # decide whether grab cube
-    def decide_move(self, x, y, color):
-
-        
-        print(x, y,self.cache_x, self.cache_y)
-        # detect the cube status move or run
-        if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
-            self.cache_x, self.cache_y = x, y
-            return
-        else:
-            self.cache_x = self.cache_y = 0
-            self.move(x-10,y+10,color)
-
-    # init mycobot
-    def run(self):
-        
-        for _ in range(10):
-            self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -38.84], 20)
-            print(_)
-            time.sleep(0.5)
-        self.pub_pump(False,[20,21])
-
-    # 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
-   
-    # detect cube color
-    def color_detect(self, img):
-        # set the arrangement of color'HSV
-        x = y = 0
-        for mycolor, item in self.HSV.items():
-            redLower = np.array(item[0])
-            redUpper = np.array(item[1])
-            # transfrom the img to model of gray
-            hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
-            # wipe off all color expect color in range
-            mask = cv2.inRange(hsv, item[0], item[1])
-            # a etching operation on a picture to remove edge roughness
-            erosion = cv2.erode(mask, np.ones((1, 1), np.uint8), iterations=2)
-            # the image for expansion operation, its role is to deepen the color depth in the picture
-            dilation =cv2.dilate(erosion, np.ones((1, 1), np.uint8), iterations=2)
-            # adds pixels to the image
-            target = cv2.bitwise_and(img, img, mask=dilation)
-            # the filtered image is transformed into a binary image and placed in binary
-            ret, binary = cv2.threshold(dilation, 127, 255, cv2.THRESH_BINARY)
-            # get the contour coordinates of the image, where contours is the coordinate value, here only the contour is detected
-            contours, hierarchy = cv2.findContours(
-                dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-            if len(contours) > 0:
-                # do something about misidentification  
-                boxes = [
-                        box
-                        for box in [cv2.boundingRect(c) for c in contours]
-                        if min(img.shape[0], img.shape[1]) / 10
-                        < min(box[2], box[3])
-                        < min(img.shape[0], img.shape[1]) / 1
-                    ]
-                if boxes:
-                    for box in boxes:
-                        x, y, w, h = box
-                    # find the largest object that fits the requirements
-                    c = max(contours, key=cv2.contourArea)
-                    # get the lower left and upper right points of the positioning object
-                    x, y, w, h = cv2.boundingRect(c)
-                    # locate the target by drawing rectangle
-                    cv2.rectangle(img, (x, y), (x+w, y+h), (153, 153, 0), 2)
-                    # calculate the rectangle center
-                    x, y = (x*2+w)/2, (y*2+h)/2
-                    # calculate the real coordinates of mycobot relative to the target
-                    if mycolor == "yellow":
-                        self.color = 1
-                    elif mycolor == "red":
-                        self.color = 0
-                    
-        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)
-    if not cap.isOpened():
-        cap.open()
-    # init a class of Object_detect
-    detect = Object_detect()
-    # init mycobot
-    detect.run()
-    
-    _init_ = 20  # 
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-       # read camera
-        _,frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-        
-
-        if _init_ > 0:
-            _init_-=1
-            continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure",frame)
-                continue
-            else:
-                x1,x2,y1,y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame,x1,y1)
-                detect.draw_marker(frame,x2,y2)
-                detect.sum_x1+=x1
-                detect.sum_x2+=x2
-                detect.sum_y1+=y1
-                detect.sum_y2+=y2
-                init_num+=1
-                continue
-        elif init_num==20:
-            detect.set_cut_params(
-                (detect.sum_x1)/20.0, 
-                (detect.sum_y1)/20.0, 
-                (detect.sum_x2)/20.0, 
-                (detect.sum_y2)/20.0, 
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num+=1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure",frame)
-                continue
-            else:
-                x1,x2,y1,y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame,x1,y1)
-                detect.draw_marker(frame,x2,y2)
-                detect.sum_x1+=x1
-                detect.sum_x2+=x2
-                detect.sum_y1+=y1
-                detect.sum_y2+=y2
-                nparams+=1
-                continue
-        elif nparams==10:
-            nparams+=1
-            # calculate and set params of calculating real coord between cube and mycobot
-            detect.set_params(
-                (detect.sum_x1+detect.sum_x2)/20.0, 
-                (detect.sum_y1+detect.sum_y2)/20.0, 
-                abs(detect.sum_x1-detect.sum_x2)/10.0+abs(detect.sum_y1-detect.sum_y2)/10.0
-            )
-            print "ok"
-            continue
-            
-        # get detect result
-        detect_result = detect.color_detect(frame)
-        if detect_result is None:
-            cv2.imshow("figure",frame)
-            continue
-        else:
-            x, y = detect_result
-            # calculate real coord between cube and mycobot
-            real_x, real_y = detect.get_position(x, y)
-            if num == 20:
-                detect.pub_marker(real_sx/20.0/1000.0, real_sy/20.0/1000.0)
-                detect.decide_move(real_sx/20.0, real_sy/20.0, detect.color)
-                num = real_sx = real_sy = 0
-
-            else:
-                num += 1
-                real_sy += real_y
-                real_sx += real_x
-
-        cv2.imshow("figure",frame)
-    
-
-        
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_img.py
deleted file mode 100755
index 47bc937..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img.py
+++ /dev/null
@@ -1,588 +0,0 @@
-# encoding:utf-8
-#!/usr/bin/env python2
-
-from tokenize import Pointfloat
-import cv2
-import numpy as np
-import time
-import json
-import os
-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
-
-IS_CV_4 = cv2.__version__[0] == '4'
-__version__ = "1.0"  # Adaptive seeed
-
-
-class Object_detect(Movement):
-    def __init__(self, camera_x=150, camera_y=-10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-        
-        	
-        # 移动角度
-        self.move_angles = [
-            [-7.11, -6.94, -55.01, -24.16, 0, 15],  # init the point
-            [-1.14, -10.63, -87.8, 9.05, -3.07, 15],  # 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],
-            [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],
-        ]
-        # 判断连接设备:ttyUSB*为M5，ttyACM*为seeed
-        self.robot_m5 = os.popen("ls /dev/ttyUSB*").readline()[:-1]
-        self.robot_wio = os.popen("ls /dev/ttyACM*").readline()[:-1]
-        self.robot_raspi = os.popen("ls /dev/ttyAMA*").readline()[:-1]
-        self.robot_jes = os.popen("ls /dev/ttyTHS1").readline()[:-1]
-        self.raspi = False
-        if "dev" in self.robot_m5:
-            self.Pin = [2, 5]
-        elif "dev" in self.robot_wio:
-            self.Pin = [20, 21]
-            for i in self.move_coords:
-                i[2] -= 20
-        elif "dev" in self.robot_raspi or "dev" in self.robot_jes:
-            import RPi.GPIO as GPIO
-            self.GPIO = GPIO
-            GPIO.setwarnings(False)
-            GPIO.setmode(GPIO.BCM)
-            GPIO.setup(20, GPIO.OUT)
-            GPIO.setup(21, GPIO.OUT)
-
-            self.raspi = True
-        if self.raspi:
-            self.gpio_status(False)
-        self.Pin = [2, 5]
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # load model of img recognition
-        # self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
-        # self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
-        # self.label_path = os.path.join(dir_path, "labels.json")
-        # load class labels
-        # self.labels = json.load(open(self.label_path))
-	
-	
-
-        
-        # use to calculate coord between cube and mycobot
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the mycobot
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mycobot
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # if IS_CV_4:
-        #     self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
-        # else:
-        #     print('Load tensorflow model need the version of opencv is 4.')
-        #     exit(0)
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-        self.cache_x = self.cache_y = 0
-
-
-    # publish marker
-
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-    def gpio_status(self, flag):
-        if flag:
-            self.GPIO.output(20, 0)
-            self.GPIO.output(21, 0)
-        else:
-            self.GPIO.output(20, 1)
-            self.GPIO.output(21, 1)
-
-    # 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)
-        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)
-        print self.move_coords[color]
-        self.pub_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)
-        # close pump
-        if self.raspi:
-            self.gpio_status(False)
-        else:
-            self.pub_pump(False, self.Pin)
-        time.sleep(1)
-        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)
-
-    # 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
-            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
-    def run(self):
-        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)
-
-    # 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):
-        # 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,
-        # )
-
-        # Detecting.
-        # self.net.setInput(blob)
-        # out = self.net.forward()
-        # x, y = 0, 0
-
-        # 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()
-
-        # find the keypoints and descriptors with SIFT
-        kp = []
-        des = []
-
-        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)
-
-        # 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)
-                    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:
-            return x, y
-        else:
-            return None
-
-
-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)))
-    
-    cap_num = 0
-    cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
-    if not cap.isOpened():
-        cap.open()
-    # init a class of Object_detect
-    detect = Object_detect()
-    # init mycobot
-    detect.run()
-
-    _init_ = 20  #
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-       # read camera
-        _, frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-
-        if _init_ > 0:
-            _init_ -= 1
-            continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1)/20.0,
-                (detect.sum_y1)/20.0,
-                (detect.sum_x2)/20.0,
-                (detect.sum_y2)/20.0,
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                continue
-        elif nparams == 10:
-            nparams += 1
-            # calculate and set params of calculating real coord between cube and mycobot
-            detect.set_params(
-                (detect.sum_x1+detect.sum_x2)/20.0,
-                (detect.sum_y1+detect.sum_y2)/20.0,
-                abs(detect.sum_x1-detect.sum_x2)/10.0 +
-                abs(detect.sum_y1-detect.sum_y2)/10.0
-            )
-            print "ok"
-            continue
-        # get detect result
-        detect_result = detect.obj_detect(frame, goal)
-        if detect_result is None:
-            cv2.imshow("figure", frame)
-            continue
-        else:
-            x, y = detect_result
-            # calculate real coord between cube and mycobot
-            real_x, real_y = detect.get_position(x, y)
-            if num == 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)
-                num = real_sx = real_sy = 0
-
-            else:
-                num += 1
-                real_sy += real_y
-                real_sx += real_x
-
-        cv2.imshow("figure", frame)
-
-
-if __name__ == "__main__":
-    run()
-    # Object_detect().take_photo()
-    # Object_detect().cut_photo()
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder.py
deleted file mode 100755
index 2fa3d92..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder.py
+++ /dev/null
@@ -1,530 +0,0 @@
-# encoding:utf-8
-#!/usr/bin/env python2
-
-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
-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
-
-IS_CV_4 = cv2.__version__[0] == '4'
-__version__ = "1.0"  # Adaptive seeed
-
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x=150, camera_y=-10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-
-        # 移动角度
-        self.move_angles = [
-            [-7.11, -6.94, -55.01, -24.16, 0, 15],  # init the point
-            [-1.14, -10.63, -87.8, 9.05, -3.07, 15],  # 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],  
-        ]
-
-        # 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]
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # load model of img recognition
-        # self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
-        # self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
-        # self.label_path = os.path.join(dir_path, "labels.json")
-        # # load class labels
-        # self.labels = json.load(open(self.label_path))
-
-        # use to calculate coord between cube and mycobot
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the mycobot
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mycobot
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # if IS_CV_4:
-        #     self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
-        # else:
-        #     print('Load tensorflow model need the version of opencv is 4.')
-        #     exit(0)
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-        self.cache_x = self.cache_y = 0
-
-    # publish marker
-
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-    def gpio_status(self, flag):
-        if flag:
-            self.GPIO.output(20, 0)
-            self.GPIO.output(21, 0)
-        else:
-            self.GPIO.output(20, 1)
-            self.GPIO.output(21, 1)
-
-    # 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
-        self.pub_coords([x, y, 90, -178.9, -1.57, -66], 25, 1)
-        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)
-
-        print(self.move_coords[color])
-        self.pub_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)
-        # 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)
-
-    # decide whether grab cube
-    def decide_move(self, x, y, color):
-        print(x, y, self.cache_x, self.cache_y)
-        # detect the cube status move or run
-        if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5:  # mm
-            self.cache_x, self.cache_y = x, y
-            return
-        else:
-            self.cache_x = self.cache_y = 0
-            # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动
-            print(x, y)
-            self.move(x, y, color)
-
-    # init mycobot
-    def run(self):
-        for _ in range(5):
-            self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -15], 20)
-            print(_)
-            time.sleep(0.5)
-
-    # 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):
-        i = 0
-        MIN_MATCH_COUNT = 5
-        sift = cv2.xfeatures2d.SIFT_create()
-
-        # find the keypoints and descriptors with SIFT
-        kp = []
-        des = []
-
-        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)
-
-        # 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)
-                    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:
-            return x, y
-        else:
-            return None
-
-# The path to save the image folder
-def parse_folder(folder):
-    restore = []
-    path = '/home/ubuntu/catkin_ws/src/mycobot_ros/mycobot_ai/' + folder
-    for i, j, k in os.walk(path):
-        for l in k:
-            restore.append(cv2.imread(folder + '/{}'.format(l)))
-    return restore
-
-
-def run():
-
-    # 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/gray')
-    res_queue[3] = parse_folder('res/blue')
-
-    cap_num = 0
-    cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
-    if not cap.isOpened():
-        cap.open()
-    # init a class of Object_detect
-    detect = Object_detect()
-    # init mycobot
-    detect.run()
-
-#    _init_ = 20  #
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-        start_time = time.time()
-        # read camera
-        _, frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-
-#        if _init_ > 0:
-#            _init_ -= 1
-#            continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1) / 20.0,
-                (detect.sum_y1) / 20.0,
-                (detect.sum_x2) / 20.0,
-                (detect.sum_y2) / 20.0,
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                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
-        for i, v in enumerate(res_queue):
-            detect_result = detect.obj_detect(frame, v)
-            if detect_result is None:
-                cv2.imshow("figure", frame)
-                continue
-            else:
-                x, y = detect_result
-                # calculate real coord between cube and mycobot
-                real_x, real_y = detect.get_position(x, y)
-                if num == 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
-
-            cv2.imshow("figure", frame)
-
-        end_time = time.time()
-        print("loop_time = ", end_time - start_time)
-
-
-if __name__ == "__main__":
-    run()
-    # Object_detect().take_photo()
-    # Object_detect().cut_photo()
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder_opt.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder_opt.py
deleted file mode 100755
index 971082f..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_folder_opt.py
+++ /dev/null
@@ -1,624 +0,0 @@
-# encoding:utf-8
-#!/usr/bin/env python2
-
-from multiprocessing import Process, Pipe
-
-from cgi import parse
-from difflib import restore
-# import queue
-from sys import path
-from tokenize import Pointfloat
-from turtle import color
-# from typing_extensions import Self
-import cv2
-import numpy as np
-import time
-import json
-import os
-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]
-        # choose place to set cube
-        self.color = 0
-        # parameters to calculate camera clipping parameters
-        self.x1 = self.x2 = self.y1 = self.y2 = 0
-        # set cache of real coord
-        self.cache_x = self.cache_y = 0
-        # load model of img recognition
-        # self.model_path = os.path.join(dir_path, "frozen_inference_graph.pb")
-        # self.pbtxt_path = os.path.join(dir_path, "graph.pbtxt")
-        # self.label_path = os.path.join(dir_path, "labels.json")
-        # # load class labels
-        # self.labels = json.load(open(self.label_path))
-
-        # use to calculate coord between cube and mycobot
-        self.sum_x1 = self.sum_x2 = self.sum_y2 = self.sum_y1 = 0
-        # The coordinates of the grab center point relative to the mycobot
-        self.camera_x, self.camera_y = camera_x, camera_y
-        # The coordinates of the cube relative to the mycobot
-        self.c_x, self.c_y = 0, 0
-        # The ratio of pixels to actual values
-        self.ratio = 0
-        # Get ArUco marker dict that can be detected.
-        self.aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_6X6_250)
-        # Get ArUco marker params.
-        self.aruco_params = cv2.aruco.DetectorParameters_create()
-
-        # if IS_CV_4:
-        #     self.net = cv2.dnn.readNetFromTensorflow(self.model_path, self.pbtxt_path)
-        # else:
-        #     print('Load tensorflow model need the version of opencv is 4.')
-        #     exit(0)
-
-        # init a node and a publisher
-        rospy.init_node("marker", anonymous=True)
-        self.pub = rospy.Publisher('/cube', Marker, queue_size=1)
-        # init a Marker
-        self.marker = Marker()
-        self.marker.header.frame_id = "/joint1"
-        self.marker.ns = "cube"
-        self.marker.type = self.marker.CUBE
-        self.marker.action = self.marker.ADD
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-
-        # marker position initial
-        self.marker.pose.position.x = 0
-        self.marker.pose.position.y = 0
-        self.marker.pose.position.z = 0.03
-        self.marker.pose.orientation.x = 0
-        self.marker.pose.orientation.y = 0
-        self.marker.pose.orientation.z = 0
-        self.marker.pose.orientation.w = 1.0
-
-        self.cache_x = self.cache_y = 0
-
-    # publish marker
-    def pub_marker(self, x, y, z=0.03):
-        self.marker.header.stamp = rospy.Time.now()
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        self.marker.color.g = self.color
-        self.pub.publish(self.marker)
-
-    def gpio_status(self, flag):
-        if flag:
-            self.GPIO.output(20, 0)
-            self.GPIO.output(21, 0)
-        else:
-            self.GPIO.output(20, 1)
-            self.GPIO.output(21, 1)
-
-    # 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
-        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)
-
-        print(self.move_coords[color])
-
-        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
-        self.gpio_status(False)
-        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
-        if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5:  # mm
-            self.cache_x, self.cache_y = x, y
-            return
-        else:
-            self.cache_x = self.cache_y = 0
-            # 调整吸泵吸取位置，y增大,向左移动;y减小,向右移动;x增大,前方移动;x减小,向后方移动
-            print(x, y)
-            self.move(x, y, color)
-
-    # init mycobot
-    def run(self):
-        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(
-            img,
-            (x - 20, y - 20),
-            (x + 20, y + 20),
-            (0, 255, 0),
-            thickness=2,
-            lineType=cv2.FONT_HERSHEY_COMPLEX,
-        )
-        # add text on rectangle
-        cv2.putText(
-            img,
-            "({},{})".format(x, y),
-            (x, y),
-            cv2.FONT_HERSHEY_COMPLEX_SMALL,
-            1,
-            (243, 0, 0),
-            2,
-        )
-
-    # get points of two aruco
-    def get_calculate_params(self, img):
-        # Convert the image to a gray image
-        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-        # Detect ArUco marker.
-        corners, ids, rejectImaPoint = cv2.aruco.detectMarkers(
-            gray, self.aruco_dict, parameters=self.aruco_params)
-
-        """
-        Two Arucos must be present in the picture and in the same order.
-        There are two Arucos in the Corners, and each aruco contains the pixels of its four corners.
-        Determine the center of the aruco by the four corners of the aruco.
-        """
-        if len(corners) > 0:
-            if ids is not None:
-                if len(corners) <= 1 or ids[0] == 1:
-                    return None
-                x1 = x2 = y1 = y2 = 0
-                point_11, point_21, point_31, point_41 = corners[0][0]
-                x1, y1 = int(
-                    (point_11[0] + point_21[0] + point_31[0] + point_41[0]) /
-                    4.0), int(
-                        (point_11[1] + point_21[1] + point_31[1] + point_41[1])
-                        / 4.0)
-                point_1, point_2, point_3, point_4 = corners[1][0]
-                x2, y2 = int(
-                    (point_1[0] + point_2[0] + point_3[0] + point_4[0]) /
-                    4.0), int(
-                        (point_1[1] + point_2[1] + point_3[1] + point_4[1]) /
-                        4.0)
-                return x1, x2, y1, y2
-        return None
-
-    # set camera clipping parameters
-    def set_cut_params(self, x1, y1, x2, y2):
-        self.x1 = int(x1)
-        self.y1 = int(y1)
-        self.x2 = int(x2)
-        self.y2 = int(y2)
-        print(self.x1, self.y1, self.x2, self.y2)
-
-    # set parameters to calculate the coords between cube and mycobot
-    def set_params(self, c_x, c_y, ratio):
-        self.c_x = c_x
-        self.c_y = c_y
-        self.ratio = 220.0 / ratio
-
-    # calculate the coords between cube and mycobot
-    def get_position(self, x, y):
-        return ((y - self.c_y) * self.ratio +
-                self.camera_x), ((x - self.c_x) * self.ratio + self.camera_y)
-
-    """
-    Calibrate the camera according to the calibration parameters.
-    Enlarge the video pixel by 1.5 times, which means enlarge the video size by 1.5 times.
-    If two ARuco values have been calculated, clip the video.
-    """
-
-    def transform_frame(self, frame):
-        # enlarge the image by 1.5 times
-        fx = 1.5
-        fy = 1.5
-        frame = cv2.resize(frame, (0, 0),
-                           fx=fx,
-                           fy=fy,
-                           interpolation=cv2.INTER_CUBIC)
-        if self.x1 != self.x2:
-            # the cutting ratio here is adjusted according to the actual situation
-            frame = frame[int(self.y2 * 0.2):int(self.y1 * 1.15),
-                          int(self.x1 * 0.7):int(self.x2 * 1.15)]
-        return frame
-
-    # according the class_id to get object name
-    def id_class_name(self, class_id):
-        for key, value in self.labels.items():
-            if class_id == int(key):
-                return value
-
-    # detect object
-    def obj_detect(self, img, goal, kp_img, desc_img, kp_list, desc_list, connection):
-        i = 0
-        MIN_MATCH_COUNT = 5
-        # sift = cv2.xfeatures2d.SIFT_create()
-
-        # find the keypoints and descriptors with SIFT
-        # kp = []
-        # des = []
-        kp = kp_list
-        des = desc_list
-
-        # for i in goal:
-        #     kp0, des0 = sift.detectAndCompute(i, None)
-        #     kp.append(kp0)
-        #     des.append(des0)
-
-        # kp1, des1 = sift.detectAndCompute(goal, None)
-        # kp2, des2 = sift.detectAndCompute(img, None)
-        kp2, des2 = kp_img, desc_img
-
-        # FLANN parameters
-        FLANN_INDEX_KDTREE = 0
-        index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=5)
-        search_params = dict(checks=50)  # or pass empty dictionary
-        flann = cv2.FlannBasedMatcher(index_params, search_params)
-
-        x, y = 0, 0
-        try:
-            for i in range(len(des)):
-                matches = flann.knnMatch(des[i], des2, k=2)
-                # store all the good matches as per Lowe's ratio test.  根据Lowe比率测试存储所有良好匹配项。
-                good = []
-                for m, n in matches:
-                    if m.distance < 0.7 * n.distance:
-                        good.append(m)
-
-                # When there are enough robust matching point pairs 当有足够的健壮匹配点对（至少个MIN_MATCH_COUNT）时
-                if len(good) > MIN_MATCH_COUNT:
-
-                    # extract corresponding point pairs from matching 从匹配中提取出对应点对
-                    # query index of small objects, training index of scenarios 小对象的查询索引，场景的训练索引
-                    src_pts = np.float32([kp[i][m.queryIdx].pt
-                                          for m in good]).reshape(-1, 1, 2)
-                    dst_pts = np.float32([kp2[m.trainIdx].pt
-                                          for m in good]).reshape(-1, 1, 2)
-
-                    # Using matching points to find homography matrix in cv2.ransac 利用匹配点找到CV2.RANSAC中的单应矩阵
-                    M, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC,
-                                                 5.0)
-                    matchesMask = mask.ravel().tolist()
-                    # Calculate the distortion of image, that is the corresponding position in frame 计算图1的畸变，也就是在图2中的对应的位置
-                    h, w, d = goal[i].shape
-                    pts = np.float32([[0, 0], [0, h - 1], [w - 1, h - 1],
-                                      [w - 1, 0]]).reshape(-1, 1, 2)
-                    dst = cv2.perspectiveTransform(pts, M)
-                    coord = (dst[0][0] + dst[1][0] + dst[2][0] +
-                              dst[3][0]) / 4.0
-                    connection.send((DRAW_COORDS, coord))
-                    # cv2.putText(img, "{}".format(coord), (50, 60),
-                    #         fontFace=None, fontScale=1,
-                    #         color=(0, 255, 0), lineType=1)
-                    print(format(dst[0][0][0]))
-                    x = (dst[0][0][0] + dst[1][0][0] + dst[2][0][0] +
-                         dst[3][0][0]) / 4.0
-                    y = (dst[0][0][1] + dst[1][0][1] + dst[2][0][1] +
-                         dst[3][0][1]) / 4.0
-
-                    # bound box  绘制边框
-                    # img = cv2.polylines(img, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
-                    connection.send((DRAW_RECT, dst))
-                    # cv2.polylines(mixture, [np.int32(dst)], True, (0, 255, 0), 2, cv2.LINE_AA)
-        except Exception as e:
-            pass
-
-        if x + y > 0:
-            return x, y
-        else:
-            return None
-
-# The path to save the image folder
-def parse_folder(folder):
-    restore = []
-    path = '/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 = []
-    for images in images_lists:
-        kp_tmp = []
-        desc_tmp = []
-        for img in images:
-            kp, desc = sift.detectAndCompute(img, None)
-            kp_tmp.append(kp)
-            desc_tmp.append(desc)
-        kp_list.append(kp_tmp)
-        desc_list.append(desc_tmp)
-
-    return kp_list, desc_list
-
-GET_FRAME = 1
-STOP_PROCESSING = 2
-DRAW_COORDS = 3
-DRAW_RECT = 4
-CLEAR_DRAW = 5
-CROP_FRAME = 6
-
-def get_frame(connection):
-    connection.send(GET_FRAME)
-    frame = connection.recv()
-    return frame
-
-def process_transform_frame(frame, x1, y1, x2, y2):
-    # enlarge the image by 1.5 times
-    fx = 1.5
-    fy = 1.5
-    frame = cv2.resize(frame, (0, 0),
-                        fx=fx,
-                        fy=fy,
-                        interpolation=cv2.INTER_CUBIC)
-#    if x1 != x2:
-        # the cutting ratio here is adjusted according to the actual situation
-#        frame = frame[int(y2 * 0.2):int(y1 * 1.15),
-#                        int(x1 * 0.7):int(x2 * 1.15)]
-    return frame
-
-def process_display_frame(connection):
-    cap_num = 0
-    coord = None
-    dst = None
-    x1 = 0
-    y1 = 0
-    x2 = 0
-    y2 = 0
-    cap = cv2.VideoCapture(cap_num, cv2.CAP_V4L)
-    if not cap.isOpened():
-        cap.open()
-    while cv2.waitKey(1) < 0:
-        _, frame = cap.read()
-        frame = process_transform_frame(frame, x1, y1, x2, y2)
-        if connection.poll():
-            request = connection.recv()
-            if request == GET_FRAME:
-                connection.send(frame)
-            elif request == CLEAR_DRAW:
-                coord = None
-                dst = None
-            elif type(request) is tuple:
-                if request[0] == DRAW_COORDS:
-                    coord = request[1]
-                elif request[0] == DRAW_RECT:
-                    dst = request[1]
-                elif request[0] == CROP_FRAME:
-                    x1 = request[1]
-                    y1 = request[2]
-                    x2 = request[3]
-                    y2 = request[4]
-
-        if not coord is None:
-            cv2.putText(frame, "{}".format(coord), (50, 60), fontFace=None,
-                    fontScale=1, color=(0, 255, 0), lineType=1)
-        if not dst is None:
-            frame = cv2.polylines(frame, [np.int32(dst)], True, 244, 3, cv2.LINE_AA)
-        cv2.imshow("figure", frame)
-        time.sleep(0.04)
-    connection.send(STOP_PROCESSING)
-
-
-def run():
-    parent_conn, child_conn = Pipe()
-    child = Process(target = process_display_frame, args=(child_conn,))
-    child.start()
-
-    # Object_detect().take_photo()
-    # Object_detect().cut_photo()
-    # goal = Object_detect().distinguist()
-    
-    res_queue = [[], [], [], []]
-    res_queue[0] = parse_folder('res/red')
-    res_queue[1] = parse_folder('res/green')
-    res_queue[2] = parse_folder('res/blue')
-    res_queue[3] = parse_folder('res/gray')
-
-    # res_queue = []
-    # res_queue.extend(parse_folder('res/red'))
-    # res_queue.extend(parse_folder('res/green'))
-    # res_queue.extend(parse_folder('res/gray'))
-    # res_queue.extend(parse_folder('res/blue'))
-
-    sift = cv2.xfeatures2d.SIFT_create()
-    kp_list, desc_list = compute_keypoints_and_descriptors(sift, res_queue)
-
-    # init a class of Object_detect
-    detect = Object_detect()
-
-    # init mycobot
-    detect.run()
-
-    # _init_ = 20  #
-    init_num = 0
-    nparams = 0
-    # num = 0
-    # real_sx = real_sy = 0
-    while True:
-        start_time = time.time()
-        if parent_conn.poll():
-            data = parent_conn.recv()
-            if data == STOP_PROCESSING:
-                break
-        # read camera
-        frame = get_frame(parent_conn)
-        # deal img
-        #frame = detect.transform_frame(frame)
-
-        # if _init_ > 0:
-        #     _init_ -= 1
-        #     continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                # cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                init_num += 1
-                continue
-        elif init_num == 20:
-            detect.set_cut_params(
-                (detect.sum_x1) / 20.0,
-                (detect.sum_y1) / 20.0,
-                (detect.sum_x2) / 20.0,
-                (detect.sum_y2) / 20.0,
-            )
-            parent_conn.send((CROP_FRAME,
-                (detect.sum_x1) / 20.0,
-                (detect.sum_y1) / 20.0,
-                (detect.sum_x2) / 20.0,
-                (detect.sum_y2) / 20.0))
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num += 1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                # cv2.imshow("figure", frame)
-                continue
-            else:
-                x1, x2, y1, y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame, x1, y1)
-                detect.draw_marker(frame, x2, y2)
-                detect.sum_x1 += x1
-                detect.sum_x2 += x2
-                detect.sum_y1 += y1
-                detect.sum_y2 += y2
-                nparams += 1
-                print "ok"
-                continue
-        elif nparams == 10:
-            nparams += 1
-            # calculate and set params of calculating real coord between cube and mycobot
-            detect.set_params((detect.sum_x1 + detect.sum_x2) / 20.0,
-                              (detect.sum_y1 + detect.sum_y2) / 20.0,
-                              abs(detect.sum_x1 - detect.sum_x2) / 10.0 +
-                              abs(detect.sum_y1 - detect.sum_y2) / 10.0)
-            print("ok")
-            continue
-
-        # get detect result
-        kp_img, desc_img = sift.detectAndCompute(frame, None)
-        frame = get_frame(parent_conn)
-        for i, v in enumerate(res_queue):
-            # HACK: to update frame every time
-            detect_result = detect.obj_detect(frame, v, kp_img, desc_img, kp_list[i], desc_list[i], parent_conn)
-            if detect_result:
-                x, y = detect_result
-                # calculate real coord between cube and mycobot
-                real_x, real_y = detect.get_position(x, y)
-                detect.color = i
-                detect.pub_marker(real_x / 1000.0, real_y / 1000.0)
-                detect.decide_move(real_x, real_y, detect.color)
-                # if num == 5:
-                #     detect.color = i
-                #     detect.pub_marker(real_sx / 5.0 / 1000.0,
-                #                       real_sy / 5.0 / 1000.0)
-                #     detect.decide_move(real_sx / 5.0, real_sy / 5.0,
-                #                        detect.color)
-                #     num = real_sx = real_sy = 0
-                # else:
-                #     num += 1
-                #     real_sy += real_y
-                #     real_sx += real_x
-                parent_conn.send(CLEAR_DRAW)
-
-        # cv2.imshow("figure", frame)
-        time.sleep(0.05)
-        end_time = time.time()
-        print("loop_time = ", end_time - start_time)
-
-        # close the window
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            cap.release()
-            cv2.destroyAllWindows()
-            sys.exit()
-
-    child.join()
-    
-
-if __name__ == "__main__":
-    run()
-    # Object_detect().take_photo()
-    # Object_detect().cut_photo()
diff --git a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_wio.py b/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_wio.py
deleted file mode 100755
index c0e30ff..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/detect_obj_img_wio.py
+++ /dev/null
@@ -1,406 +0,0 @@
-#encoding:utf-8
-
-from tokenize import Pointfloat
-import cv2
-import numpy as np
-import time
-import json
-import os
-import rospy
-from visualization_msgs.msg import Marker
-
-from moving_utils import Movement
-
-IS_CV_4 = cv2.__version__[0] == '4'
-
-class Object_detect(Movement):
-
-    def __init__(self, camera_x=150, camera_y=-10):
-        # inherit the parent class
-        super(Object_detect, self).__init__()
-        # get path of file
-        dir_path = os.path.dirname(__file__)
-        # 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)
-
-    # Grasping motion
-    def move(self, x,y,color):
-        angles = [
-           [-7.11, -6.94, -55.01, -24.16, 0, -38.84],  # init the point
-            [-1.14, -10.63, -87.8, 9.05, -3.07, -37.7],  # point to grab
-            [17.4, -10.1, -87.27, 5.8, -2.02, -37.7],  # point to grab
-        ]
-
-        coords = [
-        [106.1, -141.6, 240.9, -173.34, -8.15, -83.11],  # above the red bucket
-        [208.2, -127.8, 246.9, -157.51, -17.5, -71.18],  # above the green bucket
-        [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],
-
-        ]
-
-        # send Angle to move mycobot
-        self.pub_angles(angles[0], 20)
-        time.sleep(1.5)
-        self.pub_angles(angles[1], 20)
-        time.sleep(1.5)
-        self.pub_angles(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, 40,  -178.9, -1.57, -25.95], 20, 1)
-        time.sleep(1.5)
-        # open pump
-        self.pub_pump(True)
-        time.sleep(0.5)
-        self.pub_angles(angles[2], 20)
-        time.sleep(3)
-        self.pub_marker(coords[2][0]/1000.0, coords[2][1]/1000.0, coords[2][2]/1000.0)
-        
-        self.pub_angles(angles[1], 20)
-        time.sleep(1.5)
-        self.pub_marker(coords[3][0]/1000.0, coords[3][1]/1000.0, coords[3][2]/1000.0)
-        
-        self.pub_angles(angles[0], 20)
-        time.sleep(1.5)
-        self.pub_marker(coords[4][0]/1000.0, coords[4][1]/1000.0, coords[4][2]/1000.0)
-        
-        self.pub_coords(coords[color], 20, 1)
-        self.pub_marker(coords[color][0]/1000.0, coords[color][1]/1000.0, coords[color][2]/1000.0)
-        time.sleep(2)
-        # close pump
-        self.pub_pump(False)
-        if color==1:
-           self.pub_marker(coords[color][0]/1000.0+0.04, coords[color][1]/1000.0-0.02)
-        elif color==0:
-           self.pub_marker(coords[color][0]/1000.0+0.03, coords[color][1]/1000.0)
-        self.pub_angles(angles[0], 20)
-        time.sleep(3)
-
-
-    # decide whether grab cube
-    def decide_move(self, x, y, color):
-
-        
-        print(x, y,self.cache_x, self.cache_y)
-        # detect the cube status move or run
-        if (abs(x - self.cache_x) + abs(y - self.cache_y)) / 2 > 5: # mm
-            self.cache_x, self.cache_y = x, y
-            return
-        else:
-            self.cache_x = self.cache_y = 0
-            self.move(x,y,color)
-
-    # init mycobot
-    def run(self):
-        
-        for _ in range(10):
-            self.pub_angles([-7.11, -6.94, -55.01, -24.16, 0, -38.84], 20)
-            print(_)
-            time.sleep(0.5)
-        self.pub_pump(False)
-
-    # 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, frame):
-        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,
-        )
-
-        # Detecting.
-        self.net.setInput(blob)
-        out = self.net.forward()
-        x, y = 0, 0
-
-        # 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,
-                )
-
-        if x+y > 0:
-            return x, y
-        else:
-            return None
-
-    
-
-
-
-
-if __name__ == "__main__":
-    # open the camera
-    cap_num = 0
-    cap = cv2.VideoCapture(cap_num)
-    if not cap.isOpened():
-        cap.open()
-    # init a class of Object_detect
-    detect = Object_detect()
-    # init mycobot
-    detect.run()
-    
-    _init_ = 20  # 
-    init_num = 0
-    nparams = 0
-    num = 0
-    real_sx = real_sy = 0
-    while cv2.waitKey(1) < 0:
-       # read camera
-        _,frame = cap.read()
-        # deal img
-        frame = detect.transform_frame(frame)
-        
-
-        if _init_ > 0:
-            _init_-=1
-            continue
-        # calculate the parameters of camera clipping
-        if init_num < 20:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure",frame)
-                continue
-            else:
-                x1,x2,y1,y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame,x1,y1)
-                detect.draw_marker(frame,x2,y2)
-                detect.sum_x1+=x1
-                detect.sum_x2+=x2
-                detect.sum_y1+=y1
-                detect.sum_y2+=y2
-                init_num+=1
-                continue
-        elif init_num==20:
-            detect.set_cut_params(
-                (detect.sum_x1)/20.0, 
-                (detect.sum_y1)/20.0, 
-                (detect.sum_x2)/20.0, 
-                (detect.sum_y2)/20.0, 
-            )
-            detect.sum_x1 = detect.sum_x2 = detect.sum_y1 = detect.sum_y2 = 0
-            init_num+=1
-            continue
-
-        # calculate params of the coords between cube and mycobot
-        if nparams < 10:
-            if detect.get_calculate_params(frame) is None:
-                cv2.imshow("figure",frame)
-                continue
-            else:
-                x1,x2,y1,y2 = detect.get_calculate_params(frame)
-                detect.draw_marker(frame,x1,y1)
-                detect.draw_marker(frame,x2,y2)
-                detect.sum_x1+=x1
-                detect.sum_x2+=x2
-                detect.sum_y1+=y1
-                detect.sum_y2+=y2
-                nparams+=1
-                continue
-        elif nparams==10:
-            nparams+=1
-            # calculate and set params of calculating real coord between cube and mycobot
-            detect.set_params(
-                (detect.sum_x1+detect.sum_x2)/20.0, 
-                (detect.sum_y1+detect.sum_y2)/20.0, 
-                abs(detect.sum_x1-detect.sum_x2)/10.0+abs(detect.sum_y1-detect.sum_y2)/10.0
-            )
-            print "ok"
-            continue
-            
-        # get detect result
-        detect_result = detect.obj_detect(frame)
-        if detect_result is None:
-            cv2.imshow("figure",frame)
-            continue
-        else:
-            x, y = detect_result
-            # calculate real coord between cube and mycobot
-            real_x, real_y = detect.get_position(x, y)
-            if num == 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)
-                num = real_sx = real_sy = 0
-
-            else:
-                num += 1
-                real_sy += real_y
-                real_sx += real_x
-
-        cv2.imshow("figure",frame)
-    
-
-        
-
diff --git a/mycobot_ai/ai_ultraarm/scripts/frozen_inference_graph.pb b/mycobot_ai/ai_ultraarm/scripts/frozen_inference_graph.pb
deleted file mode 100644
index 92189ed..0000000
Binary files a/mycobot_ai/ai_ultraarm/scripts/frozen_inference_graph.pb and /dev/null differ
diff --git a/mycobot_ai/ai_ultraarm/scripts/graph.pbtxt b/mycobot_ai/ai_ultraarm/scripts/graph.pbtxt
deleted file mode 100644
index ce68612..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/graph.pbtxt
+++ /dev/null
@@ -1,2682 +0,0 @@
-node {
-  name: "image_tensor"
-  op: "Placeholder"
-  attr {
-    key: "dtype"
-    value {
-      type: DT_UINT8
-    }
-  }
-  attr {
-    key: "shape"
-    value {
-      shape {
-        dim {
-          size: -1
-        }
-        dim {
-          size: 300
-        }
-        dim {
-          size: 300
-        }
-        dim {
-          size: 3
-        }
-      }
-    }
-  }
-}
-node {
-  name: "Preprocessor/mul"
-  op: "Mul"
-  input: "image_tensor"
-  input: "Preprocessor/mul/x"
-}
-node {
-  name: "Preprocessor/sub"
-  op: "Sub"
-  input: "Preprocessor/mul"
-  input: "Preprocessor/sub/y"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1"
-  op: "Conv2D"
-  input: "Preprocessor/sub"
-  input: "FeatureExtractor/MobilenetV1/Conv2d_0/weights/read/_104__cf__107"
-  input: "^FeatureExtractor/Assert/Assert"
-  attr {
-    key: "data_format"
-    value {
-      s: "NHWC"
-    }
-  }
-  attr {
-    key: "padding"
-    value {
-      s: "SAME"
-    }
-  }
-  attr {
-    key: "strides"
-    value {
-      list {
-        i: 1
-        i: 2
-        i: 2
-        i: 1
-      }
-    }
-  }
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/add_1"
-  op: "Add"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/mul_1"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/sub/_103__cf__106"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
-  op: "Relu6"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/batchnorm/add_1"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
-  op: "DepthwiseConv2dNative"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_0/Relu6"
-  input: "FeatureExtractor/MobilenetV1/Conv2d_1_depthwise/depthwise_weights/read/_101__cf__104"
-  attr {
-    key: "data_format"
-    value {
-      s: "NHWC"
-    }
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-  attr {
-    key: "padding"
-    value {
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-    }
-  }
-  attr {
-    key: "strides"
-    value {
-      list {
-        i: 1
-        i: 1
-        i: 1
-        i: 1
-      }
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-  }
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul_1"
-  op: "Mul"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/depthwise"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul/_99__cf__102"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/add_1"
-  op: "Add"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/mul_1"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/sub/_100__cf__103"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
-  op: "Relu6"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/BatchNorm/batchnorm/add_1"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/mul_1"
-  op: "Conv2D"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_depthwise/Relu6"
-  input: "FeatureExtractor/MobilenetV1/Conv2d_1_pointwise/weights/read/_98__cf__101"
-  attr {
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-    value {
-      s: "NHWC"
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-  attr {
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-    value {
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-  }
-  attr {
-    key: "strides"
-    value {
-      list {
-        i: 1
-        i: 1
-        i: 1
-        i: 1
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-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/add_1"
-  op: "Add"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/mul_1"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/sub/_97__cf__100"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
-  op: "Relu6"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/BatchNorm/batchnorm/add_1"
-}
-node {
-  name: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_2_depthwise/depthwise"
-  op: "DepthwiseConv2dNative"
-  input: "FeatureExtractor/MobilenetV1/MobilenetV1/Conv2d_1_pointwise/Relu6"
-  input: "FeatureExtractor/MobilenetV1/Conv2d_2_depthwise/depthwise_weights/read/_95__cf__98"
-  attr {
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-  name: "ClassPredictor/concat/sigmoid"
-  op: "Sigmoid"
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diff --git a/mycobot_ai/ai_ultraarm/scripts/labels.json b/mycobot_ai/ai_ultraarm/scripts/labels.json
deleted file mode 100644
index 570e618..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/labels.json
+++ /dev/null
@@ -1,82 +0,0 @@
-{
-  "1": "person",
-  "2": "bicycle",
-  "3": "car",
-  "4": "motorcycle",
-  "5": "airplane",
-  "6": "bus",
-  "7": "train",
-  "8": "truck",
-  "9": "boat",
-  "10": "traffic light",
-  "11": "fire hydrant",
-  "13": "stop sign",
-  "14": "parking meter",
-  "15": "bench",
-  "16": "bird",
-  "17": "cat",
-  "18": "dog",
-  "19": "horse",
-  "20": "sheep",
-  "21": "cow",
-  "22": "elephant",
-  "23": "bear",
-  "24": "zebra",
-  "25": "giraffe",
-  "27": "backpack",
-  "28": "umbrella",
-  "31": "handbag",
-  "32": "tie",
-  "33": "suitcase",
-  "34": "frisbee",
-  "35": "skis",
-  "36": "snowboard",
-  "37": "sports ball",
-  "38": "kite",
-  "39": "baseball bat",
-  "40": "baseball glove",
-  "41": "skateboard",
-  "42": "surfboard",
-  "43": "tennis racket",
-  "44": "bottle",
-  "46": "wine glass",
-  "47": "cup",
-  "48": "fork",
-  "49": "knife",
-  "50": "spoon",
-  "51": "bowl",
-  "52": "banana",
-  "53": "apple",
-  "54": "sandwich",
-  "55": "orange",
-  "56": "broccoli",
-  "57": "carrot",
-  "58": "hot dog",
-  "59": "pizza",
-  "60": "donut",
-  "61": "cake",
-  "62": "chair",
-  "63": "couch",
-  "64": "potted plant",
-  "65": "bed",
-  "67": "dining table",
-  "70": "toilet",
-  "72": "tv",
-  "73": "laptop",
-  "74": "mouse",
-  "75": "remote",
-  "76": "keyboard",
-  "77": "cell phone",
-  "78": "microwave",
-  "79": "oven",
-  "80": "toaster",
-  "81": "sink",
-  "82": "refrigerator",
-  "84": "book",
-  "85": "clock",
-  "86": "vase",
-  "87": "scissors",
-  "88": "teddy bear",
-  "89": "hair drier",
-  "90": "toothbrush"
-}
\ No newline at end of file
diff --git a/mycobot_ai/ai_ultraarm/scripts/local_photo/takephoto.jpeg b/mycobot_ai/ai_ultraarm/scripts/local_photo/takephoto.jpeg
deleted file mode 100644
index e4c2563..0000000
Binary files a/mycobot_ai/ai_ultraarm/scripts/local_photo/takephoto.jpeg and /dev/null differ
diff --git a/mycobot_ai/ai_ultraarm/scripts/moving_utils.py b/mycobot_ai/ai_ultraarm/scripts/moving_utils.py
deleted file mode 100755
index 7fbb75a..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/moving_utils.py
+++ /dev/null
@@ -1,49 +0,0 @@
-#encoding: UTF-8
-#!/usr/bin/env python2
-import rospy
-import time,os
-
-from mira_communication.msg import MiraSetAngles, MiraSetCoords, MiraPumpStatus
-
-
-class Movement(object):
-	"""Tools class: Communication with mycobot."""
-	def __init__(self):
-		super(Movement, self).__init__()
-		self.angle_pub = rospy.Publisher("mycobot/angles_goal", MiraSetAngles, queue_size=5)
-		self.coord_pub = rospy.Publisher("mycobot/coords_goal", MiraSetCoords, queue_size=5)
-
-		self.pump_pub = rospy.Publisher("mycobot/pump_status", MiraPumpStatus, queue_size=10)
-
-		self.angles = MiraSetAngles()
-		self.coords = MiraSetCoords()
-		self.pump = MiraPumpStatus()
-
-	def pub_coords(self, item, sp=20):
-		self.coords.x = item[0]
-		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.speed = sp
-		# self.coords.model = m
-		self.coord_pub.publish(self.coords)
-
-
-	def pub_angles(self, item, sp):
-		self.angles.joint_1 = item[0]
-		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.speed = sp
-		self.angle_pub.publish(self.angles)
-
-
-	def pub_pump(self, flag):
-		self.pump.Status= flag
-		# self.pump.Pin1 = Pin[0]
-		# self.pump.Pin2 = Pin[1]
-		self.pump_pub.publish(self.pump)
diff --git a/mycobot_ai/ai_ultraarm/scripts/mtx_dist.npz b/mycobot_ai/ai_ultraarm/scripts/mtx_dist.npz
deleted file mode 100644
index 88f1cee..0000000
Binary files a/mycobot_ai/ai_ultraarm/scripts/mtx_dist.npz and /dev/null differ
diff --git a/mycobot_ai/ai_ultraarm/scripts/openVideo.py b/mycobot_ai/ai_ultraarm/scripts/openVideo.py
deleted file mode 100755
index a95db11..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/openVideo.py
+++ /dev/null
@@ -1,8 +0,0 @@
-import cv2 as cv
-
-if __name__ == "__main__":
-    cap_num = 0
-    cap = cv.VideoCapture(cap_num)
-    while cv.waitKey(1)<0:
-        _, img = cap.read()
-        cv.imshow("", img)
diff --git a/mycobot_ai/ai_ultraarm/scripts/pump.py b/mycobot_ai/ai_ultraarm/scripts/pump.py
deleted file mode 100755
index b91680c..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/pump.py
+++ /dev/null
@@ -1,23 +0,0 @@
-#encoding: UTF-8
-#!/usr/bin/env python2
-
-import rospy
-import time
-from moving_utils import Movement
-
-class Pump(Movement):
-
-	def __init__(self):
-		super(Pump, self).__init__()
-		rospy.init_node("pump", anonymous=True)
-
-	def run(self):
-		# self.pub_pump(True)
-		# time.sleep(1)
-		self.pub_pump(True)
-		time.sleep(5)
-		self.pub_pump(False)
-
-if __name__ == "__main__":
-	pump = Pump()
-	pump.run()
\ No newline at end of file
diff --git a/mycobot_ai/ai_ultraarm/scripts/scripts.tar.gz b/mycobot_ai/ai_ultraarm/scripts/scripts.tar.gz
deleted file mode 100644
index 5e01d6b..0000000
Binary files a/mycobot_ai/ai_ultraarm/scripts/scripts.tar.gz and /dev/null differ
diff --git a/mycobot_ai/ai_ultraarm/scripts/send_maker.py b/mycobot_ai/ai_ultraarm/scripts/send_maker.py
deleted file mode 100755
index 7fb84b4..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/send_maker.py
+++ /dev/null
@@ -1,72 +0,0 @@
-# encoding: utf-8
-
-import rospy
-import time
-from visualization_msgs.msg import Marker
-
-class Send_marker(object):
-    def __init__(self):
-        # 继承object类对象
-        super(Send_marker, self).__init__()
-        # 初始化一个节点，如果没有创建节点会导致无法发布信息
-        rospy.init_node("send_marker", anonymous=True)
-        # 创建一个发布者，用来发布marker
-        self.pub = rospy.Publisher("/test_marker", Marker, queue_size=1)
-        # 创建一个marker用来创建方块模型
-        self.marker = Marker()
-        # 配置其所属关系，其坐标均是相对于/joint1而言的。
-        # /joint1在模型中代表机械臂的底部
-        self.marker.header.frame_id = "/joint1"
-        # 设置marker的名称
-        self.marker.ns = "test_marker"
-        # 设置marker的类型是方块
-        self.marker.type = self.marker.CUBE
-        # 设置marker的动作为添加（没有这个名称的marker就为其添加一个）
-        self.marker.action = self.marker.ADD
-        # 设置marker的实际大小情况，单位为m
-        self.marker.scale.x = 0.04
-        self.marker.scale.y = 0.04
-        self.marker.scale.z = 0.04
-        # 设置marker的颜色，1.0表示255（这表示着一种比率换算）
-        self.marker.color.a = 1.0
-        self.marker.color.g = 1.0
-        self.marker.color.r = 1.0
-        # 初始化marker的位置以及其四维姿态
-        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
-
-    # 修改坐标并发布marker
-    def pub_marker(self, x, y, z=0.03):
-        # 设置marker的时间戳
-        self.marker.header.stamp = rospy.Time.now()
-        # 设置marker的空间坐标
-        self.marker.pose.position.x = x
-        self.marker.pose.position.y = y
-        self.marker.pose.position.z = z
-        # 发布marker
-        self.pub.publish(self.marker)
-
-    # 让marker发生位移效果
-    def run(self):
-        time.sleep(1)
-        self.pub_marker(0.2, 0)
-        time.sleep(1)
-        self.pub_marker(0.15, -0.05)
-        time.sleep(1)
-        self.pub_marker(0.15, 0.05)
-        time.sleep(1)
-        self.pub_marker(0.1, 0)
-        time.sleep(1)
-        self.pub_marker(0.136, -0.141)
-        time.sleep(1)
-        self.pub_marker(0.238, -0.147)
-        time.sleep(1)
-
-if __name__ == '__main__':
-    marker = Send_marker()
-    marker.run()
diff --git a/mycobot_ai/ai_ultraarm/scripts/test.py b/mycobot_ai/ai_ultraarm/scripts/test.py
deleted file mode 100755
index d73de19..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/test.py
+++ /dev/null
@@ -1,41 +0,0 @@
-# -*- coding: utf-8 -*-
-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,os
-
-mc = MyPalletizer(os.popen("ls /dev/ttyUSB*").readline()[:-1], 115200)
-
-# mc = MyPalletizer("/dev/ttyAMA0", 1000000)
-# mc.send_angles([-29.0, 5.88, -4.92, -76.28],25) # init the point coords:[155.3, -86.1, 218.4, -47.28]
-# 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)
-
-# mc.send_coords([141.2, -142.0, 206.2, -26.8],25,1) # above the red bucket
-# time.sleep(2)
-# mc.send_coords([234.3, -120, 210, -48.77],25,1) # above the green bucket
-# time.sleep(2)
-# 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.release_all_servos()
-# mc.set_servo_calibration(1)
-# mc.set_servo_calibration(2)
-# mc.set_servo_calibration(3)
-# mc.set_servo_calibration(4) 
\ No newline at end of file
diff --git a/mycobot_ai/ai_ultraarm/scripts/tools.py b/mycobot_ai/ai_ultraarm/scripts/tools.py
deleted file mode 100755
index 857db58..0000000
--- a/mycobot_ai/ai_ultraarm/scripts/tools.py
+++ /dev/null
@@ -1,101 +0,0 @@
-from pymycobot.mira import Mira
-import os
-import time
-port = "/dev/ttyUSB0"
-mc = Mira(port)
-mc.go_zero()
-
-
-radians_chushi= [0.34, 0, 0]
-chushi_angles = [19.48, 0.0, 0.0]
-chishi_coords = [165.93, 58.69, 120.0]
-
-radians_pre = [0.0, 0.09, 0.53]
-pre_angles = [0.0, 5.16, 30.37]
-pre_coords = [170.33, 0.0, 58.84]
-
-radians_zhuaqu = [0.0, 0.33, 0.87]
-zhuaqu_angles = [0.0, 18.91, 49.85]
-zhuaqu_coords = [172.26, 0.0, 21.8]
-
-radians_qilai = [0.0, 0.0, 0.0]
-qilai_angles = [0.0, 0.0, 0.0]
-qilai_coords = [176.0, 0.0, 120.0]
-
-
-move_blue = [-1.01, 0.22, 0.0]
-blue_angles = [-57.87, 12.61, 0.0]
-blue_coords = [107.54, -171.23, 117.11]
-
-move_gray = [-1.61, 0.0, 0.0]
-gray_angles = [-92.25, 0.0, 0.0]
-gray_coords = [-6.91, -175.86, 120.0]
-
-move_green = [0.48, 0.61, 0]
-green_angles = [27.5, 34.95, 0.0]
-green_coords = [217.09, 113.01, 98.36]
-
-move_red = [0.81, 0.0, 0.0]
-red_angles = [46.41, 0.0, 0.0]
-red_coords = [121.35, 127.48, 120.0]
-
-
-radians_chushi= [0.34, 0, 0]
-chushi_angles = [19.48, 0.0, 0.0]
-chishi_coords = [165.93, 58.69, 120.0]
-
-# mc.set_radians(radians_chushi, 50)
-# time.sleep(3)
-# print('chushi_angles:', mc.get_angles_info())
-# print('chishi_coords:', mc.get_coords_info())
-
-# mc.set_radians(radians_pre, 50)
-# time.sleep(3)
-# print('pre_angles:', mc.get_angles_info())
-# print('pre_coords:', mc.get_coords_info())
-
-# mc.set_radians(radians_zhuaqu, 50)
-# time.sleep(3)
-# print('zhuaqu_angles:', mc.get_angles_info())
-# print('zhuaqu_coords:', mc.get_coords_info())
-# # mc.set_gpio_state(0)
-
-# mc.set_radians(radians_qilai, 50)
-# time.sleep(3)
-# print('qilai_angles:', mc.get_angles_info())
-# print('qilai_coords:', mc.get_coords_info())
-
-# mc.set_radians(move_blue, 50)
-# time.sleep(4)
-# print('blue_angles:', mc.get_angles_info())
-# print('blue_coords:', mc.get_coords_info())
-# # mc.set_gpio_state(1)
-# time.sleep(2)
-
-# mc.set_radians(radians_chushi, 50)
-# time.sleep(5)
-# print('chushi_angles:', mc.get_angles_info())
-# print('chishi_coords:', mc.get_coords_info())
-
-# mc.set_radians(move_gray, 50)
-# time.sleep(6)
-# print('gray_angles:', mc.get_angles_info())
-# print('gray_coords:', mc.get_coords_info())
-
-# mc.set_radians(radians_chushi, 50)
-# time.sleep(2)
-
-mc.set_radians(move_green, 50)
-time.sleep(4)
-print('green_angles:', mc.get_angles_info())
-print('green_coords:', mc.get_coords_info())
-
-mc.set_radians(radians_chushi, 50)
-time.sleep(2)
-
-mc.set_radians(move_red, 50)
-time.sleep(4)
-print('red_angles:', mc.get_angles_info())
-print('red_coords:', mc.get_coords_info())
-
-mc.set_radians(radians_chushi, 50)