# Violence Detection using Conv3D

## Model Architecture
- **Type**: 3D Convolutional Neural Network (Conv3D)
- **Input**: Video sequence of 16 frames, resized to 112x112.
- **Structure**:
  - 4 Conv3D Layers with BatchNorm, ReLU, and MaxPooling.
  - Flatten Layer.
  - 2 Fully Connected Layers.
  - Dropout (0.5) for regularization.
- **Output**: Binary Classification (Violence vs No-Violence).

## Dataset Structure
The code expects a `Dataset` folder in the parent directory (or modify `DATASET_DIR` in `train.py`).
Structure:
```
Dataset/
├── violence/
│   ├── video1.mp4
│   └── ...
└── no-violence/
    ├── video2.mp4
    └── ...
```

## How to Run
1. Install dependencies: `torch`, `opencv-python`, `scikit-learn`, `numpy`.
2. Run `python train.py`.