mmdetection/docs/en/user_guides/tracking_inference.md

Inference

We provide demo scripts to inference a given video or a folder that contains continuous images. The source codes are available here.

Note that if you use a folder as the input, the image names there must be sortable , which means we can re-order the images according to the numbers contained in the filenames. We now only support reading the images whose filenames end with .jpg, .jpeg and .png.

Inference MOT models

This script can inference an input video / images with a multiple object tracking or video instance segmentation model.

python demo/mot_demo.py \
    ${INPUTS}
    ${CONFIG_FILE} \
    [--checkpoint ${CHECKPOINT_FILE}] \
    [--detector ${DETECTOR_FILE}] \
    [--reid ${REID_FILE}] \
    [--score-thr ${SCORE_THR}] \
    [--device ${DEVICE}] \
    [--out ${OUTPUT}] \
    [--show]

The INPUT and OUTPUT support both mp4 video format and the folder format.

Important: For DeepSORT, SORT, StrongSORT, they need load the weight of the reid and the weight of the detector separately. Therefore, we use --detector and --reid to load weights. Other algorithms such as ByteTrack, OCSORT QDTrack MaskTrackRCNN and Mask2Former use --checkpoint to load weights.

Optional arguments:

• CHECKPOINT_FILE: The checkpoint is optional.
• DETECTOR_FILE: The detector is optional.
• REID_FILE: The reid is optional.
• SCORE_THR: The threshold of score to filter bboxes.
• DEVICE: The device for inference. Options are cpu or cuda:0, etc.
• OUTPUT: Output of the visualized demo. If not specified, the --show is obligate to show the video on the fly.
• --show: Whether show the video on the fly.

Examples of running mot model:

# Example 1: do not specify --checkpoint to use --detector
python demo/mot_demo.py \
    demo/demo_mot.mp4 \
    configs/sort/sort_faster-rcnn_r50_fpn_8xb2-4e_mot17halftrain_test-mot17halfval.py \
    --detector \
    https://download.openmmlab.com/mmtracking/mot/faster_rcnn/faster-rcnn_r50_fpn_4e_mot17-half-64ee2ed4.pth \
    --out mot.mp4

# Example 2: use --checkpoint
python demo/mot_demo.py \
    demo/demo_mot.mp4 \
    configs/qdtrack/qdtrack_faster-rcnn_r50_fpn_8xb2-4e_mot17halftrain_test-mot17halfval.py \
    --checkpoint https://download.openmmlab.com/mmtracking/mot/qdtrack/mot_dataset/qdtrack_faster-rcnn_r50_fpn_4e_mot17_20220315_145635-76f295ef.pth \
    --out mot.mp4