VeggieAI

Project overview

Computer vision meets a useful web application.

VeggieAI connects vegetable image classification with price lookup, authenticated history and conversational guidance. A Flask web application uses a separate registry-backed model service. Two reproducibly loadable model packages are documented, while held-out accuracy and latency claims remain unsupported by committed training and evaluation artefacts.

• Python
• Flask
• Computer Vision
• Docker

Inside this build

• Separated the web application and inference service into a two-image container stack.
• Defined distinct four-label and five-label model contracts with model-specific preprocessing.
• Validated manifests, labels, package paths and checksums before serving.
• Rejected incompatible image shapes, channels and normalisation profiles before inference.
• Exercised health, metadata and prediction interfaces through service smoke tests.
• Kept OpenAI, Roboflow, email and remote-model integrations optional and explicitly configured.

Source code & links