# PyTorchVideo Training (No SlowFast)

Your environment currently has a PyTorchVideo / torchvision mismatch that breaks `pytorchvideo.transforms`.
So we train with **PyTorchVideo decoding + a small custom transform pipeline** (no SlowFast).

## 1) Prereqs

- You already created CSV files (e.g. `train.csv`, `val.csv`) with:
  - `relative/path/to/video.mp4 <label_int>`
- Your videos live under:
  - `/home/ubuntu/data/fish/fish_action_videos`
- Your CSV folder is:
  - `/home/ubuntu/projects/FishAction/data/fish/fish_action_training_dataset`

## 2) Train (fine-tune pretrained X3D)

From repo root:

```bash
cd /home/ubuntu/projects/FishAction

python train_pytorchvideo_x3d.py \
  --csv_dir /home/ubuntu/projects/FishAction/data/fish/fish_action_training_dataset \
  --path_prefix /home/ubuntu/data/fish/fish_action_videos \
  --model x3d_m \
  --pretrained \
  --num_frames 16 \
  --sampling_rate 5 \
  --batch_size 4 \
  --epochs 30 \
  --num_workers 4 \
  --amp \
  --output_dir /home/ubuntu/projects/FishAction/checkpoints/ptv_x3d_m
```

Notes:
- `--pretrained` uses `torch.hub` and will download weights to `~/.cache/torch/hub/` on first run.
- If you hit OOM, lower `--batch_size` to `2` or `1`.

## 3) Outputs

The script writes into `--output_dir`:
- `config.json`
- `checkpoint_last.pt`
- `checkpoint_best.pt`