video
video | category
stringclasses 2
values | label
stringclasses 1
value | duration
float64 5
5
| num_frames
int64 300
300
| noise_density
float64 0.5
0.5
| speckle_size
int64 1
1
| speed
int64 2
2
| direction
stringclasses 1
value | fps
int64 60
60
| resolution
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
|
motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
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motion_only
|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
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|
motion_only
| 5
| 300
| 0.5
| 1
| 2
|
horizontal
| 60
|
960x540
|
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|
motion_only
| 5
| 300
| 0.5
| 1
| 2
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| 60
|
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|
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|
motion_only
| 5
| 300
| 0.5
| 1
| 2
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| 60
|
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|
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|
motion_only
| 5
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| 0.5
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| 60
|
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| 5
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| 0.5
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| 60
|
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| 60
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| 60
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| 5
| 300
| 0.5
| 1
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| 60
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|
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motion_only
| 5
| 300
| 0.5
| 1
| 2
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| 60
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|
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| 5
| 300
| 0.5
| 1
| 2
|
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| 60
|
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|
End of preview. Expand
in Data Studio
Motion-Text Classifier Dataset
A binary classification dataset for distinguishing between pure motion and text-revealed-through-motion in speckle noise videos.
Dataset Description
This dataset contains 1000 videos (5 seconds each) designed to test motion-based perception:
- Motion-only (500 videos): Pure background noise scrolling horizontally
- Text videos (500 videos): Single words revealed through opposing foreground/background motion
All videos use identical noise parameters to ensure the only distinguishing feature is the presence of foreground content.
Dataset Structure
dataset/
βββ train/
β βββ motion_0000.mp4 to motion_0449.mp4 (450 videos)
β βββ text_0000.mp4 to text_0449.mp4 (450 videos)
β βββ metadata.csv
βββ test/
βββ motion_0450.mp4 to motion_0499.mp4 (50 videos)
βββ text_0450.mp4 to text_0499.mp4 (50 videos)
βββ metadata.csv
Usage
from datasets import load_dataset
# Load dataset
dataset = load_dataset("mukul54/motion-text-classifier")
# Access samples
train_sample = dataset['train'][0]
print(train_sample['label']) # 'motion_only' or 'text_fg_bg'
print(train_sample['text']) # word shown (None for motion_only)
Video Parameters
All videos share identical generation parameters:
| Parameter | Value |
|---|---|
| Resolution | 960Γ540 |
| FPS | 60 |
| Duration | 5.0 seconds |
| Noise Density | 0.5 |
| Speckle Size | 1 |
| Speed | 2 |
| Direction | Horizontal |
Labels
- motion_only: Background noise only (no foreground object)
- text_fg_bg: Text revealed through opposite motion of foreground/background using the same noise pattern
Key Features
- Pure motion detection: Text is invisible in static frames
- Controlled experiment: All parameters identical except foreground content
- Temporal encoding: Information only available through motion analysis
Use Cases
- Testing motion perception in vision models
- Temporal feature extraction benchmarks
- Zero-shot video understanding
- Motion-based object detection
Citation
If you use this dataset, please cite:
@dataset{motion_text_classifier,
title={Motion-Text Classifier: Speckle Noise Motion Detection Dataset},
author={Mukul},
year={2025},
publisher={HuggingFace},
url={https://huggingface.co/datasets/mukul54/motion-text-classifier}
}
License
MIT License
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