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A image processing for identify rice crop pest damages\n\n- Offline/Online Mobile app\n- This is a capstone project in third year to fourth year\n# \n![Android](https://img.shields.io/badge/Android-3DDC84?style=for-the-badge\u0026logo=android\u0026logoColor=white)\n![Flutter](https://img.shields.io/badge/Flutter-%2302569B.svg?style=for-the-badge\u0026logo=Flutter\u0026logoColor=white)\n![Supabase](https://img.shields.io/badge/Supabase-3ECF8E?style=for-the-badge\u0026logo=supabase\u0026logoColor=white)\n![SQLite](https://img.shields.io/badge/sqlite-%2307405e.svg?style=for-the-badge\u0026logo=sqlite\u0026logoColor=white)\n![TensorFlow](https://img.shields.io/badge/TensorFlow-%23FF6F00.svg?style=for-the-badge\u0026logo=TensorFlow\u0026logoColor=white)\n![Python](https://img.shields.io/badge/python-3670A0?style=for-the-badge\u0026logo=python\u0026logoColor=ffdd54)\n\n\n# Objectives\n- Develop a mobile app to predict crop insect infestations by analysing disease or damage caused by pests like stem borers, rice bugs, leafhoppers, and leaf folders using MobileNetV2.\n- Provide an insect list with detailed information to enhance users’ knowledge of insects.\n- Choosing an option manually based on the barangay in panabo, such as Southern, Consolacion, Quezon(Cabili), and Nanyo.\n- Provide history reports that display the number of insects most commonly attacking crops.\n\n## Screenshots\n\u003cimg src=\"https://github.com/user-attachments/assets/fede1c2b-4d8e-4866-8f68-319cfbd54351\" width=\"200\" height=\"400px\"  /\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/09bb44c3-8fc6-4310-bf85-0c8a469931ac\" width=\"200\" height=\"400px\"  /\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/59fe1e63-f792-4d2b-9ee8-aa1623b70944\" width=\"200\" height=\"400px\"  /\u003e\n\u003cimg src=\"https://github.com/user-attachments/assets/bd7b1532-15f8-4eba-8ca7-5f1e7410a6eb\" width=\"200\" height=\"400px\"  /\u003e\n\n\n## Run Project Locally\nMake sure it required install flutter cli and android studio with java\n\n1. Clone flutter project\n```bash\n  git clone https://github.com/karlmacas29/cropsight-capstone-main.git\n```\n\n2. Access in folder\n```bash\n  cd cropsight-capstone-main\n```\n\n3. Get all package\n```bash\n  flutter pub get\n```\n\n4. Run \n```bash\n  flutter run\n```\n\n## For MobileNetV2 Export with Tensorflow Lite\n\nLink for [InstectMobileNetV2TrainVal](https://drive.google.com/file/d/1F6Kq0fs7kk2dpAyP8rUzkYAQ1LpJ2ZN8/view?usp=sharing)\n\n## Members\n- Flaven Charles Llanes\n- Kian Cusperos\n- Karl R. Macas\n- Jhonry Sala\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkarlmacas29%2Fcropsight-capstone-main","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkarlmacas29%2Fcropsight-capstone-main","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkarlmacas29%2Fcropsight-capstone-main/lists"}