ShallowSORT

SJTU EI339 Artificial Intelligence course project: Multi-Object Tracking based on Deep SORT.

Demo

For example, the tracking result of MOT16-02 is: (click to watch it on Youtube)

Prerequisites

Anaconda (or Miniconda) is highly recommended for this project.

Install CenterNet according to its instructions
Install necessary packages for deep SORT with pip install -r requirements.txt
Get pretrained models:
- CenterNet's models can be found in the model zoo, and they are supposed to be put under CenterNet/models
- Deep SORT's models can be downloaded from Google Drive and then put under deep_sort/deep/checkpoint

Usage

MOT Challenge

mot_challenge.py takes the path to a MOT Challenge sequence and produces the tracking result in a text file (its format is consistent with MOT Challenge requirements for evaluation).

python mot_challenge.py [-h]
                          [--model_path MODEL_PATH]
                          [--arch ARCH]
                          [--deepsort_checkpoint DEEPSORT_CHECKPOINT]
                          [--output_file OUTPUT_FILE]
                          [--min_confidence MIN_CONFIDENCE]
                          [--min_detection_height MIN_DETECTION_HEIGHT]
                          [--nms_max_overlap NMS_MAX_OVERLAP]
                          [--max_cosine_distance MAX_COSINE_DISTANCE]
                          [--debug]
                          [--debug_dir DEBUG_DIR]
                          [--no_cuda]
                        sequence_dir

Video Demo

demo_video.py takes the path to a video and produces the tracking result in a video for visualization.

python demo_video.py [-h]
                       [--model_path MODEL_PATH]
                       [--arch ARCH]
                       [--deepsort_checkpoint DEEPSORT_CHECKPOINT]
                       [--output OUTPUT]
                       [--min_confidence MIN_CONFIDENCE]
                       [--max_cosine_distance MAX_COSINE_DISTANCE]
                       [--no_cuda]
                    video_path

References

SORT: Simple Online and Realtime Tracking, paper, code
Deep SORT: Simple Online and Realtime Tracking with a Deep Association Metric, paper, code
CenterNet: Objects as Points, paper, code
Deep SORT with YOLOv3: ZQPei/deep_sort_pytorch
MOTChallenge: The Multiple Object Tracking Benchmark, MOTChallenge

izackwu / ShallowSORT