oneoffcoder/dl-pose-yolo repository overview

In order to use the Docker image, you need to set up your input directories in a certain way.

custom/
├── annots
├── cuts
├── images
└── inspect

Here, we have a root folder called custom.

• All your input images should be placed in custom/images, and all sub-directories should be empty.
• The custom/annots will store the annotations (bounding-boxes) of where humans are detected. These are just a bunch of JSON files (output).
• The custom/cuts folder will store the cut images; one input image may generate multiple cuts if there are more than one human detected. These are just a bunch of JPG files (output).
• The custom/inspect will store the images with the bounding boxes of where humans were detected for visual inspection. These are just a bunch of JPG files (output).

To use the Docker image, then issue a command like the following. Note that you must have CUDA and cuDNN installed. Take note of the mount which mounts your custom directory to the container /yolo/custom directory.

docker run -it \
    -v `pwd`/custom:/yolo/custom \
    --gpus=all \
    --shm-size=5g \
    oneoffcoder/dl-pose-yolo \
      --image_folder custom/images \
      --annot_folder custom/annots \
      --inspect_folder custom/inspect \
      --cut_folder custom/cuts \
      --batch_size 8 \
      --n_cpu 8