{"id":31943663,"url":"https://github.com/vishwa-ud/image-understanding-and-processing","last_synced_at":"2026-04-19T07:34:38.815Z","repository":{"id":290822685,"uuid":"933493676","full_name":"Vishwa-ud/Image-Understanding-and-Processing","owner":"Vishwa-ud","description":"Image Understanding and Processing with OpenCV-Python.","archived":false,"fork":false,"pushed_at":"2025-04-30T18:00:37.000Z","size":76962,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-30T19:22:01.405Z","etag":null,"topics":["histogram-equalization","imageenhancement","iup","jupyter-notebook","matplotlib","opencv-python","python3"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Vishwa-ud.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":"2025-02-16T04:53:09.000Z","updated_at":"2025-04-30T18:00:43.000Z","dependencies_parsed_at":"2025-04-30T19:33:09.276Z","dependency_job_id":null,"html_url":"https://github.com/Vishwa-ud/Image-Understanding-and-Processing","commit_stats":null,"previous_names":["vishwa-ud/image-understanding-and-processing"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Vishwa-ud/Image-Understanding-and-Processing","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vishwa-ud%2FImage-Understanding-and-Processing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vishwa-ud%2FImage-Understanding-and-Processing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vishwa-ud%2FImage-Understanding-and-Processing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vishwa-ud%2FImage-Understanding-and-Processing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Vishwa-ud","download_url":"https://codeload.github.com/Vishwa-ud/Image-Understanding-and-Processing/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Vishwa-ud%2FImage-Understanding-and-Processing/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279018563,"owners_count":26086405,"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","status":"online","status_checked_at":"2025-10-14T02:00:06.444Z","response_time":60,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["histogram-equalization","imageenhancement","iup","jupyter-notebook","matplotlib","opencv-python","python3"],"created_at":"2025-10-14T09:59:39.022Z","updated_at":"2025-10-14T09:59:48.130Z","avatar_url":"https://github.com/Vishwa-ud.png","language":"Jupyter Notebook","readme":"# 📷 Image Understanding and Processing with OpenCV-Python\n\n## 🚀 Introduction\nThis repository provides an introduction to image processing and understanding using **OpenCV** with **Python**. OpenCV is an open-source computer vision library that allows for real-time image and video processing, making it widely used in fields such as **robotics, AI, and medical imaging**.\n\n## 🔧 Prerequisites\nEnsure you have **Python** installed on your system before proceeding. It is recommended to use **Python 3.6 or later**.\n\n---\n\n### 🖼️ Image Processing Topics Covered\n\n1. **Image Smoothing / Blurring Filters using OpenCV**\n   - Averaging (Lowpass) filter with `cv2.filter2D`\n   - Box filter with `cv2.boxFilter`\n   - Simple blur with `cv2.blur`\n   - Median filter with `cv2.medianBlur` (good for salt-and-pepper noise)\n   - Gaussian filter with `cv2.GaussianBlur`\n\n2. **Noise Removal Techniques**\n   - Salt noise removal using Min Filter (PIL)\n   - Pepper noise removal using Max Filter (PIL)\n   - Both Salt \u0026 Pepper noise removal using Median Filter\n\n3. **PIL-Based Image Processing**\n   - `ImageFilter.MinFilter` and `ImageFilter.MaxFilter`\n   - Grayscale conversion using `ImageOps.grayscale`\n   - Edge detection using `ImageFilter.FIND_EDGES`\n\n4. **Edge Detection**\n   - Sobel operator using `cv2.Sobel` (X and Y derivatives)\n   - Laplacian operator using `cv2.Laplacian`\n   - Laplacian of Gaussian (LoG): combining Gaussian blur + Laplacian\n\n5. **Histogram Equalization**\n   - Improve contrast of:\n     - Dark images\n     - Bright images\n     - Low contrast images\n\n6. **Image Transformations**\n   - Negative Transformation (invert pixel values)\n   - Power-Law (Gamma) Transformation for brightness correction\n\n---\n\n## 📥 Installation\nTo set up your environment, install the required dependencies using **pip**:\n\n```bash\npip install opencv-python\npip install matplotlib\npython -m pip install jupyter\n```\n\n## ▶️ Running Jupyter Notebook\nTo start working with Jupyter Notebook, run the following command:\n\n```bash\npython -m notebook\n```\n\nThis will open **Jupyter Notebook** in your web browser, allowing you to execute and visualize **OpenCV-based image processing** scripts. \n\n## ⌨️ Jupyter Notebook Shortcuts\nHere are some essential **Jupyter Notebook keyboard shortcuts** to improve efficiency:\n\n### General Shortcuts\n- `Shift + Enter` → Run the current cell and move to the next\n- `Ctrl + Enter` → Run the current cell but stay on it\n- `Alt + Enter` → Run the current cell and insert a new one below\n- `Esc + A` → Insert a new cell **above**\n- `Esc + B` → Insert a new cell **below**\n- `Esc + D + D` → Delete the selected cell\n- `Esc + M` → Convert cell to **Markdown**\n- `Esc + Y` → Convert cell to **Code**\n- `Esc + L` → Toggle **line numbers** in cell\n- `Esc + H` → Show **help menu**\n\n### Navigation\n- `Up/Down Arrow` → Move **between cells**\n- `Ctrl + Shift + -` → Split a cell at the cursor\n- `Shift + Tab` → Show **tooltip** for functions\n- `Ctrl + Shift + P` → Open **command palette**\n\n## 🤝 Contributing\nContributions are welcome! Feel free to submit **issues** or **pull requests** to enhance this repository. \n\n## 📜 License\nThis project is licensed under the **MIT License**. See the `LICENSE` file for more details.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvishwa-ud%2Fimage-understanding-and-processing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvishwa-ud%2Fimage-understanding-and-processing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvishwa-ud%2Fimage-understanding-and-processing/lists"}