Create Rust crate skeleton with Cargo.toml, main.rs, and config.rs.
Includes package metadata, dependencies (anyhow, axum, image, ndarray,
ort, serde, tokio, tower, tracing), and config module with LABELS
constants, SERVICE_NAME, SERVICE_VERSION, DEFAULT_INPUT_SIZE, and
resolve_model_path function. Config tests verify label order, relative
path resolution, and absolute path preservation.
Also includes approved spec and implementation plan documents.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Extend shared types for image classification, including PredictionProbability, UploaderMetadata, and ImageClassificationRecord.
- Create image_classifications table in the database with necessary fields and foreign key constraints.
- Implement disease mappers to convert database rows to shared disease records.
- Develop uploader client to handle image uploads to external service.
- Create image model service to load and classify images using TensorFlow.js.
- Add API routes for image classification, including GET for history and POST for new classifications.
- Implement frontend components for image classification form and display results.
- Update dashboard to integrate image classification functionality and display results.
- Document implementation plan for backend image classification.
- Add disease detail page component with data fetching and error handling
- Create shared types for diseases and classifications
- Implement API routes for diseases, classifications, and dashboard summary
- Develop reusable components for risk badge and disease card
- Build catalog page with search and filter functionality
- Update dashboard page with data-backed summary and manual classification form
- Register new routes in the web application
- Ensure type safety and consistency across shared modules
