Overview

This high-precision computer vision model is specifically engineered to recognize and classify 65 distinct types of fruits and vegetables. Built using a deep Convolutional Neural Network (CNN), it handles variations in lighting, orientation, and background noise effectively.

Key Features

• Extensive Library: Identifies 65 categories (Full list included in the technical docs).
• Real-time Ready: Optimized for low-latency inference on standard CPU/GPU setups.
• Preprocessed Data: Trained on a meticulously cleaned dataset for high F1-score performance.

Technical Stack

Best Use Cases

Ideal for Smart Retail (automated checkout), Agricultural sorting, or Diet/Calorie tracking applications.