User uploads an image for classification. The quality of the image is checked by the Python backend.
If the image quality is low, the user is prompted to crop or enhance it before proceeding.
Using OpenCV, a bounding box is created around the primary object in the image.
TensorFlow extracts features from the image and classifies the waste type.
The classified waste type is matched in the database to retrieve recycling instructions.
The user sees the result and can provide feedback to improve future classifications.