ProjectsComputer Vision
Vegetable Image Classification App
A vegetable image recognition app that identifies 15 produce categories from uploaded photos and presents clear confidence results.
My Role
- 01Trained the vegetable image classification model.
- 02Built the image-classification pipeline for upload, prediction, and confidence output.
- 03Implemented the Streamlit UI with confidence scores and Top-5 predictions.
Features
- 01Simple image upload with drag-and-drop or file browse.
- 02Primary prediction and confidence score that are easy to understand.
- 03Top-5 predictions for transparency.
- 04Confidence visualization through score bars.
- 05Recognized class catalog so users know the model scope.
- 06Clean responsive UI for a complete ML demo experience.
Impact
- Makes vegetable type identification from photos quick and easy.
- Builds user trust through confidence scores and Top-5 predictions.
- Shows a complete path from TensorFlow model training to web inference.
Stack
PythonTensorFlowKerasStreamlitCNN