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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-data-extract")
model = MetaColorModel.from_pretrained("Surya2706/meta-data-extract", 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/meta-data-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). |