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README.md

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+---
+license: mit
+tags:
+  - violence-detection
+  - video-classification
+  - pytorch
+  - uniformerv2
+  - clip
+datasets:
+  - rwf-2000
+metrics:
+  - accuracy
+---
+
+# CUE-Net: Violence Detection Model
+
+## Model Description
+
+CUE-Net (CLIP-based UniFormerV2 Enhanced Network) là mô hình phát hiện bạo lực từ video giám sát, được huấn luyện trên bộ dữ liệu RWF-2000.
+
+## Architecture
+
+- **Backbone**: CLIP ViT-L/14-336
+- **Framework**: UniFormerV2
+- **Input**: 64 frames × 336 × 336
+- **Classes**: 2 (Fight, NonFight)
+- **Parameters**: ~354M
+
+## Performance
+
+| Metric | Score |
+|--------|-------|
+| Accuracy | 89.50% |
+| F1-Score | 89.48% |
+
+## Usage
+
+```python
+from slowfast.models.build import build_model
+from slowfast.config.defaults import get_cfg
+
+cfg = get_cfg()
+cfg.merge_from_file("config.yaml")
+model = build_model(cfg)
+
+# Load checkpoint
+checkpoint = torch.load("cuenet_rwf2000_epoch51.pyth")
+model.load_state_dict(checkpoint["model_state"])
+```
+
+## Training Details
+
+- Optimizer: AdamW
+- Learning rate: 4e-4
+- Epochs: 51
+- Batch size: 2-4