Computer vision project that classifies 101 food categories with 80.2% accuracy using fine-tuned EfficientNetB2 and PyTorch. Features interactive Gradio UI, optimized inference (~100ms/image), and strategic training on 20% of Food101 dataset for efficient resource utilization.
python machine-learning computer-vision deep-learning pytorch image-recognition food-classification convolutional-neural-networks transfer-learning gradio inference-optimization efficientnet interactive-ui model-optimization deployment-ready
-
Updated
May 21, 2025 - Python