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README.md

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+---
+license: mit
+task_categories:
+- video-classification
+- audio-classification
+- image-to-text
+pretty_name: Hav-Cocap AVCaps Dataset
+tags:
+- video-captioning
+- audio-visual
+- multimodal
+- cocap
+size_categories:
+- 10K<n<100K
+---
+
+# Hav-Cocap AVCaps Dataset
+
+This dataset contains the complete CoCap and Hav-Cocap implementations for audio-visual captioning.
+
+## Contents
+
+- **CoCap/**: Original CoCap framework implementation
+- **Hav-Cocap/**: Enhanced Hav-Cocap implementation with improvements
+- **requirements.txt**: Python dependencies for the project
+
+## Project Structure
+
+### CoCap
+- `cocap/`: Core modules for audio-visual captioning
+  - `data/`: Dataset loading and preprocessing
+  - `modeling/`: Model architectures and training
+  - `modules/`: Audio encoder, CLIP, BEATs, etc.
+  - `utils/`: Utility functions
+- `configs/`: Configuration files for different datasets (MSRVTT, MSVD, VATEX)
+- `tools/`: Training and evaluation scripts
+- `model_zoo/`: Pre-trained model checkpoints
+
+### Hav-Cocap
+- `dataset/AVCaps/`: AVCaps dataset with videos and captions
+  - Train/Val/Test splits
+  - Video files (240p H.264 format)
+  - Caption annotations (JSON format)
+- `learn/`: Educational notebooks and examples
+- `model/`: Model architecture implementations
+
+## Installation
+
+```bash
+pip install -r requirements.txt
+```
+
+## Dataset Details
+
+The AVCaps dataset includes:
+- Audio-visual caption pairs
+- Multiple splits (train/val/test)
+- Preprocessed video files
+- JSON caption annotations
+
+## Usage
+
+See the training scripts in `CoCap/tools/` for training examples:
+- `train_avcaps.py`: Main training script for AVCaps dataset
+- `train_net.py`: General training script
+
+## Citation
+
+If you use this dataset or code, please cite the original CoCap paper and this dataset.
+
+## License
+
+MIT License - See LICENSE file for details