docs: generate ground-truth visualization videos for benchmark datasets #245
Description
Description
Generate sample videos for each benchmark dataset used in the Tracker Comparison documentation page. Each video takes ground-truth annotations (bounding boxes + IDs from the dataset's TXT files), draws them on the corresponding frames using the same visual style as the Tracker CLI, and exports a video. Three videos per dataset, four datasets total (12 videos). Upload to GitHub for review; the best one per dataset will later be embedded in the docs.
Tasks
- Identify and select three representative sequences from each of the four datasets (MOT17, SportsMOT, SoccerNet Tracking, DenseTrack). 12 sequences total.
- Write a script that loads ground-truth MOT TXT annotations and corresponding video frames for a given sequence, using the existing parsers in
trackers/io/mot.py. - Visualize annotations on each frame: draw bounding boxes and labels (tracker ID + class name if available) with black text at top-left, box and label background colored by tracker ID. Match the Tracker CLI visual style.
- Export each annotated sequence as a video file (MP4).
- Upload the 12 generated videos to GitHub for review. The best video per dataset will later be chosen for the documentation page.