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Configuration to run AlphaPose in Docker container
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Ruben van de Ven 5aa2d0fac1
Add script to convert alphapose-results to coco-in 		2 months ago
detector Dockerfile for Alphapose 2 months ago
pretrained_models Dockerfile for Alphapose 2 months ago
.dockerignore Dockerfile for Alphapose 2 months ago
.gitignore ignore output & fetched data 2 months ago
Dockerfile get up to date CUDA and Alphapose repo 2 months ago
README.md Dockerfile for Alphapose 2 months ago
downloadCOCO.sh download MSCoco for training AlphaPose 2 months ago
loop_alphapose_training.py Add script to convert alphapose-results to coco-in 2 months ago

README.md

AlphaPose Docker

Create a docker image for AlphaPose (code at GitHub).

Building the image

docker build --tag alphapose .

Usage

Before the repository can be used, it is necessary to download the required auxilary models, as per the AlphaPose installation guide.

  1. YOLOv3 Object detector can be place in the detector/yolo/data repository.
  2. (Optionally) YOLOX models go in the detector/yolox/data repository.
  3. A pretrained AlphaPose model can be place in the pretrained_models directory. See their Model Zoo for the various options.
  4. For pose tracking, see the pose tracking module. Make sure to add the necessary folder as a volume to the docker run command.

Running

docker run --rm --gpus all -v `pwd`/out:/out -v `pwd`/detector/yolox/data:/build/AlphaPose/detector/yolox/data -v `pwd`/detector/yolo/data:/build/AlphaPose/detector/yolo/data -v `pwd`/pretrained_models:/build/AlphaPose/pretrained_models alphapose python3 scripts/demo_inference.py --cfg configs/coco/resnet/256x192_res50_lr1e-3_1x.yaml --checkpoint pretrained_models/fast_res50_256x192.pth --gpus 0 --indir examples/demo/ --save_img --vis_fast --outdir /out