86 lines
2.6 KiB
Markdown
86 lines
2.6 KiB
Markdown
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# Fish Action Dataset Preparation
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This folder contains scripts to prepare your fish action video dataset for SlowFast training.
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## Important: No Video Pre-splitting Required
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**SlowFast does NOT require you to pre-split videos into clips.** The framework automatically:
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- Loads your full-length videos
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- Samples short clips (typically 2-4 seconds) during training
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- Randomly samples one clip per video for training/validation
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- Uniformly samples multiple clips per video for testing
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The clip duration is determined by configuration parameters:
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- `NUM_FRAMES`: Number of frames to sample (e.g., 8, 16, 32, 64)
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- `SAMPLING_RATE`: Interval between sampled frames (e.g., 2, 8)
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- `TARGET_FPS`: Target frames per second (typically 30)
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Example: With `NUM_FRAMES=32` and `SAMPLING_RATE=2`, the clip duration is approximately:
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`(32-1) × 2 / 30 ≈ 2.07 seconds`
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## Dataset Structure
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Your videos should be organized as follows:
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```
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~/data/fish/fish_action_videos/
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├── class1/
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│ ├── video1.mp4
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│ ├── video2.mp4
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│ └── ...
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├── class2/
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│ ├── video1.mp4
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│ ├── video2.mp4
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│ └── ...
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└── ...
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```
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Each subfolder represents a class, and contains multiple video files.
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## Usage
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Run the preparation script:
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```bash
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python dataset/prepare_fish_dataset.py \
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--video_dir ~/data/fish/fish_action_videos \
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--output_dir ./dataset
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```
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### Options
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- `--video_dir`: Root directory containing class subfolders (default: `~/data/fish/fish_action_videos`)
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- `--output_dir`: Output directory for CSV files (default: `./dataset`)
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- `--train_ratio`: Ratio of videos for training (default: 0.7)
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- `--val_ratio`: Ratio of videos for validation (default: 0.15)
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- `--test_ratio`: Ratio of videos for testing (default: 0.15)
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- `--seed`: Random seed for reproducibility (default: 42)
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## Output
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The script will generate:
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1. **train.csv**: Training set with format `path_to_video label`
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2. **val.csv**: Validation set with format `path_to_video label`
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3. **test.csv**: Test set with format `path_to_video label`
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4. **label_map.txt**: Mapping of label indices to class names
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## Configuration
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After running the script, configure SlowFast by setting:
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- `DATA.PATH_TO_DATA_DIR`: Path to the output directory (where CSV files are located)
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- `DATA.PATH_PREFIX`: Path to the video directory (`~/data/fish/fish_action_videos`)
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Example configuration:
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```yaml
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DATA:
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PATH_TO_DATA_DIR: "/home/ubuntu/projects/FishAction/dataset"
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PATH_PREFIX: "/home/ubuntu/data/fish/fish_action_videos"
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```
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## Supported Video Formats
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The script supports common video formats:
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- `.mp4`, `.avi`, `.mov`, `.mkv`, `.webm`, `.flv`, `.m4v`
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