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911a5bf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | # Deepfake Detector
PyTorch-based deepfake detection model using:
- ResNet18 backbone for spatial feature extraction
- BiLSTM for temporal modeling
## Input
Tensor shape: (B, T, C, H, W)
- B: batch size
- T: number of frames
- C: channels (RGB)
- H, W: image size (e.g., 128x128 or 224x224)
You must extract frames yourself before inference.
## Output
- 0 = Real
- 1 = Fake
## Usage
```python
from inference import run_inference
import torch
x = torch.randn(1, 16, 3, 128, 128)
print(run_inference(x))
```
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