{"id":18051332,"url":"https://github.com/myself-aas/orange_classification_android_app","last_synced_at":"2025-10-23T18:02:05.897Z","repository":{"id":260303407,"uuid":"880459020","full_name":"myself-aas/Orange_Classification_Android_App","owner":"myself-aas","description":"Android app that uses a TensorFlow Lite model for image classification of different type of oranges, trained through Google's Teachable Machine.","archived":false,"fork":false,"pushed_at":"2024-10-30T18:01:47.000Z","size":40385,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-05T07:09:39.300Z","etag":null,"topics":["android","android-app","android-application","android-development","android-studio","android-ui","image-classification","machine-learning","object-detection","teachable-machine","tensorflow-lite"],"latest_commit_sha":null,"homepage":"","language":"Java","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/myself-aas.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":"2024-10-29T19:03:09.000Z","updated_at":"2024-11-02T10:50:02.000Z","dependencies_parsed_at":"2025-02-10T14:52:33.700Z","dependency_job_id":null,"html_url":"https://github.com/myself-aas/Orange_Classification_Android_App","commit_stats":null,"previous_names":["myself-aas/orange_classification_android_app"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/myself-aas%2FOrange_Classification_Android_App","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/myself-aas%2FOrange_Classification_Android_App/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/myself-aas%2FOrange_Classification_Android_App/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/myself-aas%2FOrange_Classification_Android_App/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/myself-aas","download_url":"https://codeload.github.com/myself-aas/Orange_Classification_Android_App/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247299844,"owners_count":20916192,"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":["android","android-app","android-application","android-development","android-studio","android-ui","image-classification","machine-learning","object-detection","teachable-machine","tensorflow-lite"],"created_at":"2024-10-30T22:30:03.378Z","updated_at":"2025-10-23T18:01:55.885Z","avatar_url":"https://github.com/myself-aas.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# Orange Classification Android App: Real-Time Fruit Classification\n\nThis Android app uses TensorFlow Lite to classify oranges directly on-device. Developed with Android Studio and written in Java, it enables real-time, low-latency classification via a user-friendly interface, ideal for agriculture and food applications. Features include real-time classification, and a seamless UI. Built for Android 5.0 (Lollipop) or higher, this project is open-source and designed for easy deployment and collaboration.\n\n\n## Acknowledgements\n\n - [TensorFlow Lite Community](https://www.tensorflow.org/community) - for providing robust tools and documentation, enabling seamless integration of machine learning on mobile platforms.\n - [Android Open Source Community](https://source.android.com/) - for sharing invaluable resources and frameworks.\n - [Bangladesh Agricultural University](https://bau.edu.bd/) - for supporting the project's research foundation.\n\n## Documentation\n\nThe Orange Classification Android App is designed to classify oranges based on various parameters using machine learning techniques. This section provides an overview of the app's components and functionalities:\n\n- **MainActivity.java**: The entry point of the application, managing the user interface and interactions.\n- **CameraFragment**: Handles camera operations and image capture for classification.\n- **ViewModel**: Manages UI-related data in a lifecycle-conscious way, ensuring data survives configuration changes.\n- **ML Model**: Utilizes a pre-trained model for orange classification, providing accurate results based on the input images.\n\nFor detailed technical documentation, refer to the `inline comments` in the code files.\n\n## Screenshots\n\n![App Screenshot](https://github.com/myself-aas/Orange_Classification_Android_App/blob/main/Screenshot-1.png)\n![App Screenshot](https://github.com/myself-aas/Orange_Classification_Android_App/blob/main/Screenshot-2.png)\n\n## Features\n\n- **Image Classification:** Accurately classify different types of oranges using machine learning algorithms.\n- **User-Friendly Interface:** Intuitive design for easy navigation and interaction.\n- **Real-Time Processing:** Quickly analyze images captured by the device's camera for immediate results.\n- **Offline Functionality:** Perform classification without the need for an internet connection.\n- **Support for Multiple Devices:** Compatible with a wide range of Android devices running version 5.0 (Lollipop) and above.\n- **Lightweight and Efficient:** Optimized for performance and low resource consumption.\n## Deployment\n\nTo deploy the Orange Classification Android App, follow these steps:\n1. **Clone the Repository**:\n```bash\n  git clone https://github.com/myself-aas/Orange_Classification_Android_App.git\n```\n2. **Open the Project**:\nOpen Android Studio and select `Open an existing Android Studio project.`\nNavigate to the cloned repository and select it.\n\n3. **Build the Project**:\nEnsure all dependencies are synced by clicking on `Sync Project with Gradle Files.`\n\n4. **Run the App**:\nConnect your Android device or start an emulator.\nClick on the `Run` button in Android Studio to deploy the app.\n\n5. **Permissions**:\nEnsure your app has the necessary permissions for camera and storage access in the AndroidManifest.xml file.\n\n6. **Testing**:\nTest the app on various devices to ensure compatibility and functionality.\n\n\n`This section provides clear, step-by-step instructions for deploying your app, making it easier for users to get started.`\n\n\n# Hi, I'm Ashif A.! 👋\n\n\n## 🚀 About Me\nI am Ashif Ahmed Shuvo, a passionate Android developer with a keen interest in artificial intelligence and machine learning. My goal is to leverage technology to create innovative solutions that enhance everyday experiences. With a strong foundation in programming and a commitment to continuous learning, I strive to contribute to impactful projects.\n\n\n\n## 🔗 Links\n[![portfolio](https://img.shields.io/badge/my_portfolio-000?style=for-the-badge\u0026logo=ko-fi\u0026logoColor=white)](https://myself-aas.github.io/portfolio/)\n[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white)](https://www.linkedin.com/in/me-aas/)\n[![twitter](https://img.shields.io/badge/twitter-1DA1F2?style=for-the-badge\u0026logo=twitter\u0026logoColor=white)](https://x.com/myself_aas)\n\n## FAQ\n\n**Q1: What is the purpose of the Orange Classification app?**  \nA1: The Orange Classification app is designed to classify oranges using machine learning techniques based on images captured through the device's camera.\n\n**Q2: How do I install the app?**  \nA2: Clone the repository and import it into Android Studio. Ensure you have the necessary dependencies and SDK installed, then build and run the app.\n\n**Q3: What are the system requirements?**  \nA3: The app requires an Android device running Android 5.0 (Lollipop) or higher with camera functionality.\n\n**Q4: How can I contribute to this project?**  \nA4: Contributions are welcome! Please fork the repository, make your changes, and submit a pull request for review.\n\n**Q5: Where can I find more information about the machine learning model?**  \nA5: Detailed information about the machine learning model can be found in the  `inline comments` within the code.\n\n## Authors\n\n- [Ashif Ahmed Shuvo](https://github.com/myself-aas)\n\n\n## Badges\n\n![Android](https://img.shields.io/badge/Platform-Android-green.svg)\n![Kotlin](https://img.shields.io/badge/Language-Kotlin-blue.svg)\n![License](https://img.shields.io/badge/License-MIT-yellow.svg)\n[![GitHub stars](https://img.shields.io/github/stars/myself-aas/Orange_Classification_Android_App.svg?style=social\u0026label=Star)](https://github.com/myself-aas/Orange_Classification_Android_App/stargazers)\n[![GitHub issues](https://img.shields.io/github/issues/myself-aas/Orange_Classification_Android_App.svg)](https://github.com/myself-aas/Orange_Classification_Android_App/issues)\n[![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue.svg)](https://linkedin.com/in/me-aas/)\n[![GitHub](https://img.shields.io/badge/GitHub-Visit_repo-lightgrey.svg)](https://github.com/myself-aas)\n\n\n## Support\n\nFor support, email shuvoasifahmed@gmail.com.\n\n\n## License\n\n[MIT](https://choosealicense.com/licenses/mit/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmyself-aas%2Forange_classification_android_app","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmyself-aas%2Forange_classification_android_app","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmyself-aas%2Forange_classification_android_app/lists"}