{"id":21151913,"url":"https://github.com/abhifuturetech/cnn-imageproc-robotics","last_synced_at":"2025-07-09T09:32:15.955Z","repository":{"id":249985922,"uuid":"823163757","full_name":"AbhiFutureTech/CNN-ImageProc-Robotics","owner":"AbhiFutureTech","description":"This project aims to develop and implement robust object recognition techniques for robotics applications using CNNs and advanced image processing methods.","archived":false,"fork":false,"pushed_at":"2024-07-29T03:34:11.000Z","size":2995,"stargazers_count":9,"open_issues_count":1,"forks_count":3,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-04T21:39:39.602Z","etag":null,"topics":["computer-vision","convolutional-neural-networks","image-processing","python","robotics","simulation","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AbhiFutureTech.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-07-02T14:17:23.000Z","updated_at":"2024-10-19T00:18:45.000Z","dependencies_parsed_at":"2024-11-20T11:29:02.550Z","dependency_job_id":"5f5bd9ed-03f4-4bd6-9458-b52ad0a32549","html_url":"https://github.com/AbhiFutureTech/CNN-ImageProc-Robotics","commit_stats":null,"previous_names":["abhifuturetech/robotic-object-recongtion-via-cnn-and-image-processing","abhifuturetech/cnn-imageproc-robotics"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AbhiFutureTech/CNN-ImageProc-Robotics","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhiFutureTech%2FCNN-ImageProc-Robotics","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhiFutureTech%2FCNN-ImageProc-Robotics/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhiFutureTech%2FCNN-ImageProc-Robotics/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhiFutureTech%2FCNN-ImageProc-Robotics/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AbhiFutureTech","download_url":"https://codeload.github.com/AbhiFutureTech/CNN-ImageProc-Robotics/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhiFutureTech%2FCNN-ImageProc-Robotics/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264431139,"owners_count":23607191,"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":["computer-vision","convolutional-neural-networks","image-processing","python","robotics","simulation","tensorflow"],"created_at":"2024-11-20T10:19:54.225Z","updated_at":"2025-07-09T09:32:15.948Z","avatar_url":"https://github.com/AbhiFutureTech.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Robotic Object Recognition via CNN and Image Processing\n\n   ![4](https://github.com/patilabhi20/Robotic-Tasks-via-Large-Language-Models/assets/157373320/90c2a08c-40b1-4b8e-ace7-39f194143c1a)\n\nWelcome to the Robotic Object Recognition via Convolutional Neural Networks (CNN) and Image Processing repository! This project aims to develop and implement robust object recognition techniques for robotics applications using CNNs and advanced image processing methods.\n\n        \n## Table of Contents\n* Introduction\n* Features\n* Installation\n* Usage\n* Examples\n* Contributing\n* Contact\n  \n\n## Introduction\n\nThe Robotic Object Recognition via CNN and Image Processing project focuses on integrating state-of-the-art deep learning techniques and image processing algorithms to enable precise and efficient object recognition in robotic systems. This enhances the capability of robots to understand and interact with their environment effectively.\n\n\n## Features\n\n* CNN-Based Object Recognition: Implement CNN models for accurate and real-time object recognition.\n* Image Processing Techniques: Utilize advanced image processing methods for preprocessing and enhancing image data.\n* Real-Time Recognition: Achieve real-time object recognition suitable for dynamic robotic applications.\n* Dataset Integration: Support for various datasets to train and evaluate object recognition models.\n* Modular Design: Easily adaptable and extendable codebase for different robotic platforms.\n\n\n## ⚙️ Installation\n\nTo set up the project, clone the repository and install the required dependencies:\n\n  ``` \ngit clone https://github.com/yourusername/Robotic-Object-Recognition-via-CNN-and-Image-Processing.git\ncd Robotic-Object-Recognition-via-CNN-and-Image-Processing\npip install -r requirements.txt\n  ```\n\nEnsure you have the necessary hardware and software configurations as detailed in the documentation.\n\n\n## Usage\n\nThe project includes various modules and examples to demonstrate object recognition using CNN and image processing techniques. You can run these examples to see the system in action or customize them to fit your specific needs.\n\n  ``` \npython examples/object_recognition.py\npython examples/image_preprocessing.py\n  ```\n\nFor detailed usage instructions, refer to the documentation provided in the docs folder.\n\n\n## Examples\n\nHere are some basic examples to get you started:\n\n![color_detection](https://github.com/patilabhi20/Robotic-Tasks-via-Large-Language-Models/assets/157373320/3d469ee4-0045-4b2c-88b5-88f40c8a9d57)\n\n* Object Recognition\n\n    ``` \n   from recognition.cnn_model import CNNModel\n   cnn_model = CNNModel()\n   cnn_model.load_model('models/object_recognition_model.h5')\n   result = cnn_model.predict('images/test_image.jpg')\n   print(f\"Recognized Object: {result}\") \n  ``` \n\n* Image Preprocessing\n\n  ``` \n   from processing.image_preprocessor import ImagePreprocessor\n   image_preprocessor = ImagePreprocessor()\n   preprocessed_image = image_preprocessor.process('images/raw_image.jpg')\n   preprocessed_image.show()\n    ``` \nCheck out the examples folder for more detailed examples and use cases.\n\n\n## Contributing\n\nWe welcome contributions from the community! Please read our Contributing Guide for more information on how to get involved.\n\n* Fork the repository\n* Create a new branch (git checkout -b feature-branch)\n* Commit your changes (git commit -m 'Add some feature')\n* Push to the branch (git push origin feature-branch)\n* Create a new Pull Request\n\n\n## Contact\nIf you have any questions, suggestions, or feedback, feel free to contact us at abhianantapatil@gmail.com.\n\n\n##\nThank you for your interest in the Robotic Object Recognition via CNN and Image Processing project! We hope you find it useful and engaging. Happy coding!\n\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhifuturetech%2Fcnn-imageproc-robotics","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhifuturetech%2Fcnn-imageproc-robotics","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhifuturetech%2Fcnn-imageproc-robotics/lists"}