{"id":26857101,"url":"https://github.com/nav3005/image-colorizer","last_synced_at":"2025-03-31T00:31:20.647Z","repository":{"id":283111017,"uuid":"950754733","full_name":"Nav3005/Image-Colorizer","owner":"Nav3005","description":"Streamlit app for Colorization of B/W images through hallucinations ","archived":false,"fork":false,"pushed_at":"2025-03-18T16:40:32.000Z","size":0,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-18T16:41:52.638Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Nav3005.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2025-03-18T16:30:19.000Z","updated_at":"2025-03-18T16:40:35.000Z","dependencies_parsed_at":"2025-03-18T16:41:56.199Z","dependency_job_id":"51127101-92e5-406f-ba26-b86d3460d8f8","html_url":"https://github.com/Nav3005/Image-Colorizer","commit_stats":null,"previous_names":["nav3005/image-colorizer"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nav3005%2FImage-Colorizer","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nav3005%2FImage-Colorizer/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nav3005%2FImage-Colorizer/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Nav3005%2FImage-Colorizer/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Nav3005","download_url":"https://codeload.github.com/Nav3005/Image-Colorizer/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246399816,"owners_count":20770907,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-03-31T00:31:19.292Z","updated_at":"2025-03-31T00:31:20.501Z","avatar_url":"https://github.com/Nav3005.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Image Colorizer\n\nThis Streamlit application uses deep learning to automatically colorize black and white images. The app employs a pre-trained model based on the Zhang et al. colorization architecture to add realistic colors to grayscale photographs.\n\n## Features\n\n- Upload black and white images in JPG, JPEG, or PNG format\n- Real-time colorization using deep learning\n- Download capability for colorized images\n- User-friendly web interface\n\n## Prerequisites\n\n- Python 3.8 or higher\n- Required Python packages (listed in requirements.txt)\n- Model files (download instructions below)\n\n## Installation\n\n1. Clone this repository:\n```bash\ngit clone https://github.com/Nav3005/Image-Colorizer.git\ncd Image-Colorizer\n```\n\n2. Install the required packages:\n```bash\npip install -r requirements.txt\n```\n\n3. Download the model files:\n   - Create a `Model` directory in the project root\n   - Download the following files and place them in the `Model` directory:\n     - [colorization_deploy_v2.prototxt](https://raw.githubusercontent.com/richzhang/colorization/master/colorization/models/colorization_deploy_v2.prototxt)\n     - [colorization_release_v2.caffemodel](https://www.dropbox.com/s/dx0qvhhp5hbcx7z/colorization_release_v2.caffemodel?dl=1)\n     - [pts_in_hull.npy](https://raw.githubusercontent.com/richzhang/colorization/master/colorization/resources/pts_in_hull.npy)\n\n## Usage\n\n1. Run the Streamlit app:\n```bash\nstreamlit run app.py\n```\n\n2. Open your web browser and navigate to the provided local URL (typically http://localhost:8501)\n\n3. Upload a black and white image using the file uploader\n\n4. Wait for the colorization process to complete\n\n5. Download the colorized image using the \"Download Colorized Image\" button\n\n## Model Information\n\nThe colorization model used in this application is based on the research paper \"Colorful Image Colorization\" by Zhang et al. It uses a deep neural network trained on a large dataset of color images to predict the most likely colors for a given grayscale input.\n\n## Limitations\n\n- The model works best with natural photographs\n- Results may vary depending on the quality and content of the input image\n- Processing time depends on the image size and your computer's specifications\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n## Acknowledgments\n\n- Original colorization model by [Richard Zhang](https://github.com/richzhang/colorization)\n- Built with Streamlit ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnav3005%2Fimage-colorizer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnav3005%2Fimage-colorizer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnav3005%2Fimage-colorizer/lists"}