Create README.md

README.md

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+---
+license: mit
+language:
+- en
+pipeline_tag: image-feature-extraction
+---
+# MetaColorModel
+
+## Overview
+MetaColorModel is a Hugging Face-compatible model designed to extract metadata and dominant colors from images. It is built using PyTorch and the Hugging Face `transformers` library, and can be used for image analysis tasks, such as understanding image properties and identifying the most prominent colors.
+
+## Model Details
+- **Model Type**: Custom image feature extraction model
+- **Configuration**: Includes parameters to specify the number of dominant colors (`k`), metadata size, and color size (e.g., RGB).
+- **Dependencies**:
+  - `transformers`
+  - `Pillow`
+  - `numpy`
+
+## Example Use Case
+The model can be used in:
+- Image search and indexing
+- Content moderation
+- Color scheme analysis for design and marketing
+- Metadata extraction for organizing photo libraries
+
+## Installation
+To use this model, first install the required dependencies:
+```bash
+pip install transformers Pillow numpy
+```
+
+## Usage
+
+Here is an example of how to use MetaColorModel:
+
+```python
+from transformers import AutoConfig
+from meta_color_model import MetaColorModel
+
+# Load the model
+config = AutoConfig.from_pretrained("Surya2706/meta_color_model")
+model = MetaColorModel.from_pretrained("Surya2706/meta_color_model", config=config)
+
+# Input image path
+image_path = "example_image.jpg"
+
+# Extract metadata and dominant colors
+result = model.forward(image_path)
+print("Metadata:", result["metadata"])
+print("Dominant Colors:", result["dominant_colors"])
+```
+
+## Inputs
+- **Image Path**: A file path to the image you want to process.
+
+## Outputs
+- **Metadata**: Extracted EXIF metadata (if available).
+- **Dominant Colors**: A list of the top `k` dominant colors in RGB format.
+
+## Training
+This model can be trained further or fine-tuned for specific tasks.
+
+### Dataset
+To train or fine-tune the model, you can prepare a dataset of images and their metadata, structured as follows:
+```
+data/
+├── images/
+│   ├── image1.jpg
+│   ├── image2.jpg
+│   └── ...
+├── metadata_colors.csv
+```
+
+The `metadata_colors.csv` file should contain metadata and dominant color labels for the images.
+
+### Training Script
+Use the `Trainer` class from Hugging Face or implement a custom PyTorch training loop to fine-tune the model.
+
+## License
+This model is released under the Apache 2.0 License.
+
+## Citation
+If you use this model in your work, please cite:
+```
+@misc{MetaColorModel,
+  title={MetaColorModel: A Hugging Face-Compatible Image Analysis Model},
+  author={Surya},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/surya2706/image-metadata-extract}}
+}
+```
+
+## Acknowledgments
+- Built with the Hugging Face `transformers` library.
+- Uses `Pillow` for image processing and `numpy` for numerical operations.
+
+## Feedback
+For questions or feedback, please contact [[email protected]] or open an issue on the [GitHub repository](https://github.com/Surya2706/image-metadata-extract).