This is a Gazebo and ROS package for generating a model.sav
of color and normals for various objects contained in the /models
directory fir use in object recognition. The package was modified from the work of Brandon Kinnman and Harsh Pandya from Electric Movement and Udacity RoboND.
- Gazebo 1.7
- ROS Kinetic
- sklearn
- numpy
- pcl 1.8
This assumes you have a ~/catkin_ws/src
directory structure.
clone the repo
cd ~/catkin_ws/src/
git clone https://github.com/jupidity/svm_model_generation.git
make in your workspace
cd ~/catkin_ws
catkin_make
if you wish to generate features from a particular model, it must be added to the /models
directory
otherwise, launch the training simulation
roslaunch svm_model_generation training.launch
a stick with an RGBD camera should appear in Gazebo sim. Next lauch the capture features node.
rosrun svm_model_generation capture_features.py
The model will be generated from 40 captures of the object in a rondom orientation with 256 histogram bins of HSV color space and geometric normals.