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Training

You can refer to install.md for preparing your own dataset. Basically, just convert your dataset into coco format, and it's ready to go.

We have 3 key train scripts, they are:

  • train_coco.py: this is basically most common used train script for coco;
  • train_detr.py: use this for any DETR or transformer based model;
  • train_net.py: Experimented changing training strategy script, used for experiement;
  • train_custom_datasets.py: train all customized datasets;

For demo usage, you can using:

  • demo.py: for demo visualize result;
  • demo_lazyconfig.py: for demo using *.py as config file;

Inference

You can direcly call demo.py to inference, visualize. A classic command would be:

python demo.py --config-file configs/coco/sparseinst/sparse_inst_r50vd_giam_aug.yaml --video-input ~/Movies/Videos/86277963_nb2-1-80.flv -c 0.4 --opts MODEL.WEIGHTS weights/sparse_inst_r50vd_giam_aug_8bc5b3.pth

Deploy

YOLOv7 can be easily deploy via ONNX, you can using export_onnx.py and according config file to convert.

You u got any problems on any model arch, please fire an issue.