This project uses front-end separation, and the client has the following three forms of implementation:
- Manual gesture recognition, which means that the user determines the segmentation of continuous gestures
- Dynamic gesture recognition based on frame difference method
- Dynamic gesture recognition based on object tracking
The server encapsulates Temporal Relation Networks.
Test on Ubuntu16.04 + Python3.6 + cuda9.0 + cudnn7.0.5 + Pytorch0.3.1 + opencv3.4（aliyun NVIDIA P100）, make sure you have installed the above environment.
$ pip install flask
$ pip install pillow
$ pip install moviepy
$ sudo apt-get install ffmpeg
$ pip install -U scikit-learn
$ pip install scipy
$ pip install flask_uploads
and then download the weight file and configuration file, and place them in the server/model folder. Finally, run server.py
.placeholderunder empty folder can be deleted
Test on Ubuntu16.04/Mac OS + Python3.6 + OpenCV3.4 + opencv_contrib
$ pip install pillow
$ pip install requests
- server-address: gesture recognition server address
$ python run_manual.py -s [server-address]
Interactive mode: press the keyboard s key before each action, and press the s key again after the action is complete to complete the recognition
you can choose the Background Subtraction Methods
- method: knn or mog
- threshold: The sum of the length and width of the contour identified by the algorithm is greater than the threshold is considered to be the hand
$ python run_frameDifferent -s [server-address] --method [method] --threshold [threshold]
GPU support is required to run this version, we tested on Ubuntu 16.04 + cuda9.0 + cudnn7.0.5 + tensorflow1.6. You need to install tensorflow1.6-gpu extra and darkflow, You can download darkflow from here.
$ pip install tensorflow-gpu
$ pip install Cython
$ cd darkflow
$ pip install .
# Check whether the installation is complete
$ flow --h
and then download the weight file and configuration file, and place them in the model folder and cfg folder respectively. Finally, run
$ python run_objectDetection.py -s [server-address]
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