/ros_grasp_detection

input : 224x224 image of object, output : grasp pose

Primary LanguagePython

Detecting grasping positions with deep neural networks using RGB images

  • Use grasp_detection for training model. This is for test. grasp_detection Link : https://github.com/Juna2/grasp_detection

  • Most of the files in this repo is from his work except test.py

  • test.py loads pretrained model in

    /home/<your_path>/catkin_ws/src/ros_grasp_detection/src/m4

  • you may change the path in test.py

  • I recommand you to train model with Juna2/grasp_detection(which is also modified version of robot-grasp-detection) first and copy the model to the path.

How to use

  1. $ catkin_make

  2. $ roslaunch ros_grasp_detection

  3. It subscribes "/croppedRoI" message which is 224x224 object image and publishes "/objects" which contains center x, y and degree. So you have to use another package to publish 224x224 object image to this package.

  4. The grasp detection result will be saved in

    /home/<your_path>/catkin_ws/src/ros_grasp_detection/src/image/bbox.jpg

  • One Thing you should know is that this test.py uses the model trained by modified robot-grasp-detection which is Juna2/grasp_detection.

sample