{"id":28951901,"url":"https://github.com/pabs-code/img-cartoonizer-using-opencv","last_synced_at":"2026-05-04T23:33:36.229Z","repository":{"id":299300797,"uuid":"1002597269","full_name":"pabs-code/img-cartoonizer-using-opencv","owner":"pabs-code","description":"A streamline app using 3 ways to cartoonized an image using OpenCV and Python.","archived":false,"fork":false,"pushed_at":"2025-06-17T00:03:08.000Z","size":17,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-23T16:39:20.039Z","etag":null,"topics":["bilateral-filtering","color-quantization","edge-detection","edge-enhancement","laplacian-edge-detection","numpy","opencv","python"],"latest_commit_sha":null,"homepage":"","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/pabs-code.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,"zenodo":null}},"created_at":"2025-06-15T19:58:05.000Z","updated_at":"2025-06-17T00:03:12.000Z","dependencies_parsed_at":"2025-06-15T21:39:46.463Z","dependency_job_id":"110c45f7-8c44-453e-997e-8ea17b2215ef","html_url":"https://github.com/pabs-code/img-cartoonizer-using-opencv","commit_stats":null,"previous_names":["pabs-code/cartoonize-img-using-opencv"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pabs-code/img-cartoonizer-using-opencv","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pabs-code%2Fimg-cartoonizer-using-opencv","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pabs-code%2Fimg-cartoonizer-using-opencv/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pabs-code%2Fimg-cartoonizer-using-opencv/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pabs-code%2Fimg-cartoonizer-using-opencv/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pabs-code","download_url":"https://codeload.github.com/pabs-code/img-cartoonizer-using-opencv/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pabs-code%2Fimg-cartoonizer-using-opencv/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32628830,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-04T10:08:07.713Z","status":"ssl_error","status_checked_at":"2026-05-04T10:08:02.005Z","response_time":58,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["bilateral-filtering","color-quantization","edge-detection","edge-enhancement","laplacian-edge-detection","numpy","opencv","python"],"created_at":"2025-06-23T16:01:01.376Z","updated_at":"2026-05-04T23:33:36.223Z","avatar_url":"https://github.com/pabs-code.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cartoonizing an Image Using Opencv\n\nA Streamlit-based application that allows users to upload an image and apply one of three cartoonization techniques to transform it into a stylized cartoon version.\n\n## Table of Contents\n\n  - [About the Project](#-about-the-project)\n    - [What Cartoonizer Techniques are Used?](#what-cartoonizer-techniques-are-used)\n    - [How It Works:](#how-it-works)\n  - [Features](#-features)\n  - [Getting Started](#-getting-started)\n    - [Prerequisites](#prerequisites)\n  - [Installation](#-installation)\n  - [Running Script](#-running-script)\n  - [Expectations When Running This App](#-expectations-when-running-this-app)\n  - [Demo](#-demo)\n  - [Acknowledgments](#-acknowledgments)\n  - [License](#-license)\n\n---\n\n## About the Project\n\n### What Cartoonizer Techniques are Used?\n\nThis **Cartoonizer App** is a simple yet powerful image processing tool that applies different cartoonization techniques to an uploaded image. It uses **OpenCV** and **Streamlit** for performance, visualization, and user interaction.\n\n### How It Works:\n\nThe app applies one of the following techniques to generate a cartoon-style version of the input image:\n\n1. **Bilateral Filtering + Edge Detection** – Smooths and sharpens edges for a cartoon-like effect.\n2. **Color Quantization + Edge Enhancement** – Reduces colors and sharpens edges for a more stylized look.\n3. **Laplacian Edge Detection** – Uses edge detection to enhance sharpness and detail.\n\nThe user can select a technique, upload an image, and view both the original and cartoonized versions on the app.\n\n---\n\n## Features\n\n- Easy-to-use **Streamlit** interface.\n- Supports common image formats: `.jpg`, `.jpeg`, and `.png`.\n- Three different cartoonization techniques:\n  - Bilateral Filtering + Edge Detection\n  - Color Quantization + Edge Enhancement\n  - Laplacian Edge Detection\n- Real-time preview of the original and cartoonized image.\n\n---\n\n## Getting Started\n\n### Prerequisites\n\nBefore you begin, ensure you have the following installed:\n\n| Dependency | Version |\n| ---------- | ------- |\n| Python     | 3.8+    |\n| Streamlit  | ≥1.20   |\n| OpenCV     | ≥4.5    |\n| Pillow     | ≥9.1    |\n\nYou can install them using pip:\n\n```bash\npip install streamlit opencv-python pillow\n```\n\n---\n\n## Installation\n\nTo install and run the app locally:\n\n```bash\n# Clone this repository (if needed)\ngit clone https://github.com/YOUR_GITHUB_USERNAME/img-cartoonizer-using-opencv.git\ncd img-cartoonizer-using-opencv\n\n# Install dependencies\npip install streamlit opencv-python pillow\n\n# Run the app\nstreamlit run app.py\n```\n\n---\n\n## Running Script\n\nOnce installed, simply run the following command in your terminal:\n\n```bash\nstreamlit run app.py\n```\n\nThis will launch the Streamlit application in your browser, where you can interact with the app.\n\n---\n\n## Expectations When Running This App\n\n- The user must upload an image in `.jpg`, `.jpeg`, or `.png` format.\n- One of the three cartoonization techniques must be selected from the dropdown menu.\n- The output will display both the original and cartoonized versions of the image side-by-side.\n\n\u003e ⚠️ If no file is uploaded or a method is not selected, the app will not show any processed image.\n\n---\n\n## Demo\n\nHere’s a quick overview of how the app looks in action:\n\n1. Open your browser and go to `http://localhost:8501` (or the URL provided by Streamlit).\n2. Upload an image.\n3. Select a cartoonization method.\n4. View the original and processed images on the web app UI.\n\nhttps://github.com/user-attachments/assets/eed42b99-be5f-470f-ba0c-0733e301a8e0\n\n---\n\n## Acknowledgments\n\n- **Streamlit** – For the easy-to-use UI.\n- **OpenCV** – For powerful image processing capabilities.\n- **Pillow (PIL)** – For handling and displaying images in the app.\n\n---\n\n## License\n\nThis project is licensed under the **MIT License** — see the [LICENSE](LICENSE) file for details.\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpabs-code%2Fimg-cartoonizer-using-opencv","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpabs-code%2Fimg-cartoonizer-using-opencv","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpabs-code%2Fimg-cartoonizer-using-opencv/lists"}