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facebook/sam3 video tracking on our own match
footage, in two rounds:roboflow-jvuqo/football-players-detection-3zvbc (broadcast)
for generality. RF-DETR Nano, 30 epochs, effective batch 16 — 5.7 min on one RTX 3090.| Detector | Goals | Notes |
|---|---|---|
| zero-shot COCO Nano | 3/8 | + 1 false event |
| Nano fine-tuned on broadcast only | 1/8 | domain shift — worse than zero-shot! |
| this model v1 (agreement labels) | 7/8 | ball location finally correct |
| this model v2 (+ blur labels), sliced inference | 8/8 | all goals at the user's exact times |
1from rfdetr import RFDETRNano
2from huggingface_hub import hf_hub_download
3
4ckpt = hf_hub_download("build-small-hackathon/futheros-ball-rfdetr",
5 "checkpoint_best_total_v2.pth")
6model = RFDETRNano(pretrain_weights=ckpt)
7detections = model.predict(image, threshold=0.35) # class 1 = ball