docs: generate ground-truth visualization videos for benchmark datasets

## 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.