Project evidence / Early work
Tomato Leaf Disease CNN
The README describes a CNN training and inference pipeline, but the audited tree does not contain the referenced training script, prediction module, model artifact, dependency manifest, templates, or static application files. The archival entry therefore reports only what is observable and treats all performance language as unverified.
- Status
- Early work
- Evidence
- verified repository
- Last reviewed
- 2026-09-08
Overview
An early tomato leaf-classification repository whose audited commit contains a Flask inference wrapper, Dockerfile, README, and interface images.
Early computer-vision learning repository; model performance and end-to-end reproducibility are not claimed.
Problem
Explore a web-facing image-classification workflow for identifying tomato leaf disease categories.
Implementation
The audited source contains a Flask wrapper around an imported prediction function, API-key middleware for one route, and a Waitress launch path; required supporting implementation is missing.
- Flask routes for browser and API inference are present in source
- Base64 image-request handling is sketched
- A container command for the Flask application is present
Security and reliability
- The archival summary does not repeat unverified model-quality or deployment claims.
Limitations
- Training, prediction, model, dependency, template, and static files referenced by the code or README are absent.
- Accuracy, robustness, reliability, real-time behavior, and dataset provenance are not reproducibly evidenced.
- CORS is enabled globally, one prediction route is unauthenticated, and request-size limits are not visible.
- No tests, CI, release, or license are present.