Initial commit: FishServer monorepo (FishAction, FishMeasure, fish_api)

Made-with: Cursor

FishAction/PYTORCHVIDEO_TRAINING.md

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+# 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`
+
+