# Fish Action Dataset Preparation

This folder contains scripts to prepare your fish action video dataset for SlowFast training.

## Important: No Video Pre-splitting Required

**SlowFast does NOT require you to pre-split videos into clips.** The framework automatically:
- Loads your full-length videos
- Samples short clips (typically 2-4 seconds) during training
- Randomly samples one clip per video for training/validation
- Uniformly samples multiple clips per video for testing

The clip duration is determined by configuration parameters:
- `NUM_FRAMES`: Number of frames to sample (e.g., 8, 16, 32, 64)
- `SAMPLING_RATE`: Interval between sampled frames (e.g., 2, 8)
- `TARGET_FPS`: Target frames per second (typically 30)

Example: With `NUM_FRAMES=32` and `SAMPLING_RATE=2`, the clip duration is approximately:
`(32-1) × 2 / 30 ≈ 2.07 seconds`

## Dataset Structure

Your videos should be organized as follows:
```
~/data/fish/fish_action_videos/
├── class1/
│   ├── video1.mp4
│   ├── video2.mp4
│   └── ...
├── class2/
│   ├── video1.mp4
│   ├── video2.mp4
│   └── ...
└── ...
```

Each subfolder represents a class, and contains multiple video files.

## Usage

Run the preparation script:

```bash
python dataset/prepare_fish_dataset.py \
    --video_dir ~/data/fish/fish_action_videos \
    --output_dir ./dataset
```

### Options

- `--video_dir`: Root directory containing class subfolders (default: `~/data/fish/fish_action_videos`)
- `--output_dir`: Output directory for CSV files (default: `./dataset`)
- `--train_ratio`: Ratio of videos for training (default: 0.7)
- `--val_ratio`: Ratio of videos for validation (default: 0.15)
- `--test_ratio`: Ratio of videos for testing (default: 0.15)
- `--seed`: Random seed for reproducibility (default: 42)

## Output

The script will generate:

1. **train.csv**: Training set with format `path_to_video label`
2. **val.csv**: Validation set with format `path_to_video label`
3. **test.csv**: Test set with format `path_to_video label`
4. **label_map.txt**: Mapping of label indices to class names

## Configuration

After running the script, configure SlowFast by setting:

- `DATA.PATH_TO_DATA_DIR`: Path to the output directory (where CSV files are located)
- `DATA.PATH_PREFIX`: Path to the video directory (`~/data/fish/fish_action_videos`)

Example configuration:
```yaml
DATA:
  PATH_TO_DATA_DIR: "/home/ubuntu/projects/FishAction/dataset"
  PATH_PREFIX: "/home/ubuntu/data/fish/fish_action_videos"
```

## Supported Video Formats

The script supports common video formats:
- `.mp4`, `.avi`, `.mov`, `.mkv`, `.webm`, `.flv`, `.m4v`