Project forked from:
Windows Version please check out doc/win_install.md
- Get the code.
git clone -b pytorch https://github.com/marcnunez/CabinMonitoringV1.git- Install pytorch 0.4.0 and other dependencies.
pip install -r requirements.txt- Download the models manually: (Google Drive). Place them into `./models
- Input dir: Run AlphaPose for all images in a folder with:
python3 demo.py --indir ${img_directory} --outdir examples/res
- Video: Run AlphaPose for a video and save the rendered video with:
python3 video_demo.py --video ${path to video} --outdir examples/res --save_video
- Webcam: Run AlphaPose using webcam and visualize the results with:
python3 webcam_demo.py --webcam 0 --posebatch 40 --nThreads 5 --sp --vis --nms 0.25 --pdf True --nClasses 33 --pathModel ./models/sppe/coco_cabin.pth
- Input list: Run AlphaPose for images in a list and save the rendered images with:
python3 demo.py --list examples/list-coco-demo.txt --indir ${img_directory} --outdir examples/res --save_img
- Note: If you meet OOM(out of memory) problem, decreasing the pose estimation batch until the program can run on your computer:
python3 demo.py --indir ${img_directory} --outdir examples/res --posebatch 30
- Getting more accurate: You can enable flip testing to get more accurate results by disable fast_inference, e.g.:
python3 demo.py --indir ${img_directory} --outdir examples/res --fast_inference False
- Speeding up: Checkout the speed_up.md for more details.
- Output format: Checkout the output.md for more details.
- For more: Checkout the run.md for more options