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README.md

@@ -1,63 +1,27 @@
----
-license: mit
-datasets:
-- nlphuji/flickr30k
-language:
-- en
----
-# Dataset Card for Conditional Latent Coding (CLC)
+# CLC: Compression Model Checkpoints
 
-## Dataset Description
+This repository contains checkpoint files for the CLC compression model at various bitrates, along with reference datasets.
 
-- **Repository:** [GitHub - ydchen0806/CLC](https://github.com/ydchen0806/CLC)
-- **Paper:** [Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression (AAAI25 Oral)](https://arxiv.org/pdf/2502.09971)
-- **Authors:** Siqi Wu†, Yinda Chen†, Dong Liu, Zhihai He*
-- **Contact:** [email protected]
+## Contents
 
-## Overview
+- **checkpoints/**: Model checkpoint files for different bitrates
+- **reference_images.tar.gz**: Reference images used for compression
+- **kodak_dataset.tar.gz**: Kodak test dataset
 
-This repository contains datasets and pre-trained models for the **Conditional Latent Coding (CLC)** framework, a state-of-the-art deep image compression method. The implementation is built on [CompressAI](https://github.com/InterDigitalInc/CompressAI) and [TCM](https://github.com/jmliu206/LIC_TCM).
+## Usage
 
+These checkpoints can be loaded using the CLC model implementation. See the code repository for details on how to use these files.
 
-## Dataset Structure
+## Bitrates
 
-### Core Components
-1. **Reference Features** (`flicker_features.pkl`):
-   - Precomputed feature dictionary using spatial pyramid pooling and k-means clustering
-   - Format: Pickle file containing clustered image features
+The following bitrates are available:
+- 0.001
+- 0.0025
+- 0.0035
+- 0.0067
+- 0.013
+- 0.05
 
-2. **Training Dataset** (`Flickr2K.hdf5`):
-   - Contains 2,650 high-resolution images (256×256 patches)
-   - HDF5 structure:
-     ```
-     /Flickr2K
-         ├── image_0001
-         ├── image_0002
-         └── ...
-     ```
+## Last Updated
 
-3. **Pre-trained Models**:
-   - Multiple rate points (0.0025-0.05 bpp):
-     - `0.0025checkpoint_best.pth.tar`
-     - `0.05checkpoint_best.pth.tar`
-   - Compatibility: PyTorch 1.7+ with CUDA support
-
-## 📜 Citation
-
-If you use this model or find it useful, please cite:
-
-```bibtex
-@article{wu2025conditional,
-  title={Conditional Latent Coding with Learnable Synthesized Reference for Deep Image Compression},
-  author={Wu, Siqi and Chen, Yinda and Liu, Dong and He, Zhihai},
-  journal={AAAI Conference on Artificial Intelligence},
-  year={2025}
-}
-```
-
-## 📧 Contact
-
-For questions or collaborations, feel free to reach out:
-
-- **GitHub**: [CLC Repository](https://github.com/ydchen0806/CLC)  
-- **Email**: [[email protected]](mailto:[email protected])
+Thu Mar 27 20:28:17 UTC 2025