---
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 [suryak2706@gmail.com] or open an issue on the [GitHub repository](https://github.com/Surya2706/image-metadata-extract).