This project uses Convolutional Neural Networks (CNNs) to estimate calorie content from food images. The system processes an image using OpenCV for preprocessing (e.g., color correction, segmentation), and applies a trained CNN model to classify food types.
Each identified food item is then matched to known calorie-per-gram data. Using approximate portion sizing from image dimensions, the model calculates an estimated calorie value. This approach can support real-time food logging or meal tracking.
Technologies: Python, CNN, OpenCV