Crop Disease Detection Using YOLOv8

This project utilizes YOLOv8 to build a crop disease detection and classification system in Google Colab. The system processes images and videos to identify diseases, providing an interactive interface for real-time analysis using Gradio.

Price: $10
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Project Template Outcomes

      • A comprehensive crop disease detection and classification system capable of accurately identifying diseases from input images and videos.
      • Utilizes deep learning techniques, specifically YOLOv8, for high-precision object detection and classification in agricultural contexts.
      • Delivers reliable and fast disease detection, enabling real-time analysis and assessment of crop health.
      • Provides an interactive user interface for easy use, allowing for the upload of images and videos to receive immediate visual feedback on detected diseases.
      • Suitable for various applications in agriculture, offering practical solutions for early disease detection, crop monitoring, and yield improvement.

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