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https://github.com/ashishtukaral/fruit-ripeness-and-disease-detection
Welcome to the Fruit Ripeness and Disease Detection System! This application utilizes advanced YOLOV8 models to detect various fruits and diagnose diseases in bananas, mangoes, and pomegranates. Built with Flask, the web application allows users to either upload images for analysis or use a live video feed for real-time detection.
https://github.com/ashishtukaral/fruit-ripeness-and-disease-detection
classification cnn computer-vision deep-learning detection flask html-css-javascript machine-learning neural-network oops-in-python opencv python yolov8
Last synced: about 1 month ago
JSON representation
Welcome to the Fruit Ripeness and Disease Detection System! This application utilizes advanced YOLOV8 models to detect various fruits and diagnose diseases in bananas, mangoes, and pomegranates. Built with Flask, the web application allows users to either upload images for analysis or use a live video feed for real-time detection.
- Host: GitHub
- URL: https://github.com/ashishtukaral/fruit-ripeness-and-disease-detection
- Owner: AshishTukaral
- License: mit
- Created: 2024-07-01T13:47:06.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-08-07T13:05:26.000Z (5 months ago)
- Last Synced: 2024-08-08T15:36:52.820Z (5 months ago)
- Topics: classification, cnn, computer-vision, deep-learning, detection, flask, html-css-javascript, machine-learning, neural-network, oops-in-python, opencv, python, yolov8
- Language: HTML
- Homepage:
- Size: 74.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE