Yanis
001658898e
- Replace floating pill tab bar with classic anchored bottom bar (Home | FAB Scan | Map) - Add central FAB button (green, elevated) for Scanner - Move History → Notifications and Profile → Settings (accessible via header icons) - Add SearchHeader with bell (notifications) and settings icons - Add MapScreen placeholder - Extract SearchHeader component from HomeScreen - Switch to lucide-react-native icons for bottom tab bar - Fix react-dom version mismatch (19.2.4 → 19.1.0) - Clean up unused imports in homeheader.tsx - Update navigation types, deep links, and i18n keys Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
66 lines
2.8 KiB
Markdown
66 lines
2.8 KiB
Markdown
# Repository Guidelines
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Monorepo with two components: a **Python/TensorFlow CNN** for grapevine disease detection and a **React Native (Expo) mobile app** (VinEye) that runs the model on-device via TFLite.
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## Project Structure & Module Organization
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```
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venv/src/ # Python ML pipeline (training, evaluation, attribution)
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venv/models/ # Trained model artifacts (.keras, .tflite)
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docs/images/ # Dataset & results visualizations
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VinEye/ # Expo React Native mobile app
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src/screens/ # 6 screens: Splash, Home, Scanner, Result, History, Profile
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src/components/ # UI grouped by feature (gamification/, scanner/, history/, ui/)
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src/services/ # TFLite inference, AsyncStorage, haptics
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src/hooks/ # useDetection, useGameProgress, useHistory
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src/navigation/ # React Navigation v7 (BottomTabs + NativeStack)
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src/i18n/ # FR + EN translations (i18next)
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src/theme/ # Design tokens (primary #2D6A4F, accent #7C3AED)
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```
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The ML model currently uses a mock TFLite detector in the mobile app (weighted random: 70% vine / 20% uncertain / 10% not_vine). The CNN trains on 9027 images (256x256) across 4 classes: Black Rot, ESCA, Healthy, Leaf Blight.
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## Build, Test, and Development Commands
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### VinEye (Mobile)
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```bash
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cd VinEye
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pnpm install # Install dependencies (pnpm only, never npm/yarn)
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pnpm start # Start Expo dev server
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pnpm android # Run on Android
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pnpm ios # Run on iOS
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pnpm web # Run on web
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```
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### Python ML Pipeline
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```bash
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cd venv/src
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python data_split.py # Split raw data into train/val/test (80/10/10)
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python data_explore.py # EDA: class distribution, sample visualization
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python model_train.py # Train CNN, exports .keras + .tflite to venv/models/
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python evaluate_model.py # Accuracy/loss curves, confusion matrix, top-k predictions
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python gradient.py # Integrated gradients attribution masks
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```
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Scripts must be run from `venv/src/` — paths are derived relative to that directory.
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## Coding Style & Naming Conventions
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**TypeScript (VinEye):**
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- Strict mode enabled, path alias `@/*` maps to `src/*`
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- Max 300 lines per file
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- NativeWind (TailwindCSS) for styling — no inline styles
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- `useEffect` must be imported from `react`, never from `react-native-reanimated`
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- React Navigation v7 only (Expo Router is forbidden)
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- RN-native UI components only (no web-based component libraries)
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**Python:** TensorFlow/Keras Sequential API, scripts use `from module import *` pattern.
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No linter or formatter configs are enforced.
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## Commit Guidelines
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Commit messages are informal, descriptive, lowercase. No conventional commits format is enforced. Examples from history: `add VinEye frontend app + fix hardcoded paths + gitignore`, `update`, `maj`.
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