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--- |
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license: mit |
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task_categories: |
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- video-classification |
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- zero-shot-classification |
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tags: |
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- motion-detection |
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- temporal-vision |
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- speckle-noise |
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size_categories: |
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- n<1K |
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--- |
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# Motion-Text Classifier Dataset |
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A binary classification dataset for distinguishing between pure motion and text-revealed-through-motion in speckle noise videos. |
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## Dataset Description |
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This dataset contains 1000 videos (5 seconds each) designed to test motion-based perception: |
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- **Motion-only (500 videos)**: Pure background noise scrolling horizontally |
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- **Text videos (500 videos)**: Single words revealed through opposing foreground/background motion |
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All videos use identical noise parameters to ensure the **only** distinguishing feature is the presence of foreground content. |
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## Dataset Structure |
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``` |
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dataset/ |
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├── train/ |
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│ ├── motion_0000.mp4 to motion_0449.mp4 (450 videos) |
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│ ├── text_0000.mp4 to text_0449.mp4 (450 videos) |
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│ └── metadata.csv |
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└── test/ |
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├── motion_0450.mp4 to motion_0499.mp4 (50 videos) |
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├── text_0450.mp4 to text_0499.mp4 (50 videos) |
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└── metadata.csv |
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``` |
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## Usage |
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```python |
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from datasets import load_dataset |
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# Load dataset |
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dataset = load_dataset("mukul54/motion-text-classifier") |
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# Access samples |
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train_sample = dataset['train'][0] |
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print(train_sample['label']) # 'motion_only' or 'text_fg_bg' |
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print(train_sample['text']) # word shown (None for motion_only) |
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``` |
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## Video Parameters |
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All videos share identical generation parameters: |
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| Parameter | Value | |
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|-----------|-------| |
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| Resolution | 960×540 | |
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| FPS | 60 | |
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| Duration | 5.0 seconds | |
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| Noise Density | 0.5 | |
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| Speckle Size | 1 | |
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| Speed | 2 | |
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| Direction | Horizontal | |
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## Labels |
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- **motion_only**: Background noise only (no foreground object) |
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- **text_fg_bg**: Text revealed through opposite motion of foreground/background using the same noise pattern |
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## Key Features |
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- **Pure motion detection**: Text is invisible in static frames |
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- **Controlled experiment**: All parameters identical except foreground content |
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- **Temporal encoding**: Information only available through motion analysis |
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## Use Cases |
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- Testing motion perception in vision models |
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- Temporal feature extraction benchmarks |
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- Zero-shot video understanding |
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- Motion-based object detection |
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## Citation |
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If you use this dataset, please cite: |
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```bibtex |
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@dataset{motion_text_classifier, |
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title={Motion-Text Classifier: Speckle Noise Motion Detection Dataset}, |
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author={Mukul}, |
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year={2025}, |
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publisher={HuggingFace}, |
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url={https://huggingface.co/datasets/mukul54/motion-text-classifier} |
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} |
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``` |
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## License |
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MIT License |
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