| # Two-Stream Violence Detection Network | |
| ## Model Architecture | |
| - **Type**: Two-Stream Network (Spatial + Temporal) | |
| - **Streams**: | |
| 1. **RGB Stream**: ResNet3D (r3d_18) to process raw video frames. Captures appearance info. | |
| 2. **Optical Flow Stream**: ResNet3D (r3d_18) to process computed dense optical flow. Captures motion info. | |
| - **Fusion**: Features from both streams are concatenated and passed through fully connected layers. | |
| - **Input**: 16 Frames (RGB) + 16 Flow Fields (Computed on the fly). | |
| - **Computation**: Optical flow is computed using Farneback algorithm within the Dataloader. | |
| ## Dataset Structure | |
| Expects `Dataset` folder in parent directory. | |
| ``` | |
| Dataset/ | |
| ├── violence/ | |
| └── no-violence/ | |
| ``` | |
| ## How to Run | |
| 1. Install dependencies: `torch`, `opencv-python` (with contrib if needed for some algorithms, but Farneback is standard), `torchvision`. | |
| 2. Run `python train.py`. | |