fix: resolve merge conflicts from develop consolidation#65
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- Expanded config.yaml with per-analysis-type configuration for deforestation, ice melting, and flooding including band configs, alert thresholds, and model paths - Added config/train.yaml for production training configuration - Expanded db.py with full SQLite schema: organisations, subscriptions, alerts tables; API key generation; all CRUD operations - Added requirements-install.txt for streamlined dependency installation Co-authored-by: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-authored-by: John Edoh Onuh <onuhj47@gmail.com> Co-authored-by: Francis Umo <Francisumoh@360yahoo.com> Co-authored-by: Olufemi Taiwo <olufemitaiwo23@gmail.com> Co-authored-by: Godswill Chukwu Okoroafor <godswillchukwu21@gmail.com>
- Added inference/pipeline.py: full GEE-integrated inference engine with NDVI computation, model loading, file and bbox inference paths, synthetic NDVI fallback with bbox-seeded reproducibility - Updated inference/__init__.py to export run_inference, run_inference_from_file, run_inference_from_gee - Added analysis/ module: base class, registry, and dedicated analysers for deforestation, flooding and ice melting detection - Added training/ module: production trainer with EMA, checkpointing, early stopping, and combined loss functions (BCE + Dice + Focal) - Updated models/unet.py with minor architecture improvements - Updated __init__.py package exports Co-authored-by: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-authored-by: Francis Umo <Francisumoh@360yahoo.com> Co-authored-by: Godswill Chukwu Okoroafor <godswillchukwu21@gmail.com> Co-authored-by: Victor Mbachu <victor.c.mbachu@gmail.com>
- Expanded api/main.py with full production API: organisation and NGO management, subscription system, alert and notification endpoints, all three analysis types wired to inference pipeline, run history, file upload endpoint, health check and API key authentication - Added run_api.sh: server startup script with venv activation, environment setup and uvicorn hot-reload configuration - Added docs/API_REFERENCE.md: full endpoint reference with request and response schemas for all routes Co-authored-by: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-authored-by: John Edoh Onuh <onuhj47@gmail.com> Co-authored-by: Olufemi Taiwo <olufemitaiwo23@gmail.com> Co-authored-by: Victor Mbachu <victor.c.mbachu@gmail.com> Co-authored-by: Godswill Chukwu Okoroafor <godswillchukwu21@gmail.com>
- Fixed repository clone URL to Climate-Vision/ClimateVision - Updated Quick Start to use run_api.sh instead of raw uvicorn command - Corrected tech stack: SQLite (not PostgreSQL), Google Maps API (not Leaflet) - Fixed API Reference doc link to docs/API_REFERENCE.md - Updated Phase 3 roadmap to reflect Google Maps and Recharts as completed - Fixed Star History tracking link Co-authored-by: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-authored-by: John Edoh Onuh <onuhj47@gmail.com> Co-authored-by: Francis Umo <Francisumoh@360yahoo.com> Co-authored-by: Olufemi Taiwo <olufemitaiwo23@gmail.com> Co-authored-by: Godswill Chukwu Okoroafor <godswillchukwu21@gmail.com> Co-authored-by: Victor Mbachu <victor.c.mbachu@gmail.com> Co-authored-by: Paul <46930375+cutewizzy11@users.noreply.github.com>
…ipts - prepare_data.py: GEE + synthetic Sentinel-2 patch downloader with Dynamic World forest labels, train/val/test split, normalizer fitting - train.py: production Attention U-Net training entry-point with YAML config, focal+dice loss, EMA weights, cosine LR schedule, early stopping - run_training.py: end-to-end training + inference pipeline - evaluate.py: per-class IoU/F1/precision/recall on held-out test set - export_model.py: ONNX and TorchScript model export - infer.py: CLI inference runner for single images or GEE bbox Co-Authored-By: Emmanuel Edoh <edoh-Onuh@users.noreply.github.com> Co-Authored-By: Godswill Okoroafor <godswillchukwu21@gmail.com> Co-Authored-By: Gold Okpa <okpagold@gmail.com> Co-Authored-By: Victor Mbachu <victor.c.mbachu@gmail.com>
- pipeline.py: authenticate GEE via service account key when GEE_SERVICE_ACCOUNT and GEE_SERVICE_ACCOUNT_KEY env vars are set; falls back to synthetic NDVI when GEE is unavailable instead of zeros - .gitignore: protect secrets/ directory and *.json key files Co-Authored-By: Gold Okpa <okpagold@gmail.com>
Notebook handles: GEE service account auth, multi-region patch download (Amazon/Congo/Borneo), Attention U-Net training on T4 GPU, evaluation, and checkpoint download back to local machine. Co-Authored-By: Gold Okpa <okpagold@gmail.com>
- prepare_data.py: reads GEE_SERVICE_ACCOUNT / GEE_SERVICE_ACCOUNT_KEY env vars to authenticate via service account instead of requiring earthengine authenticate - notebook: sets env vars with absolute key path in Cell 3 so all subprocess calls in Cells 5 and 6 inherit them automatically Co-Authored-By: Gold Okpa <okpagold@gmail.com>
Split each region into 0.5° tiles at 30m resolution instead of downloading the whole bbox at 10m (which hit GEE's pixel grid cap). Each tile is ~1850x1850px — well under the 32768 limit. Patches are accumulated across tiles until max_patches is reached. Co-Authored-By: Gold Okpa <okpagold@gmail.com>
…E limit Previous 30m/0.5° tiles were ~130MB each, exceeding GEE's 48MB cap. At 100m resolution each 0.25° tile is ~1.5MB — well within limits. Also fixes NameError on profile when all tiles failed, and adds a clear error exit when no patches are extracted. Co-Authored-By: Gold Okpa <okpagold@gmail.com>
… config - App.tsx: main application shell with routing, global state and sidebar navigation between Dashboard, Analysis, NGO and Settings - api.ts: typed API client for all backend endpoints (predict, runs, organizations, alerts, analysis-types) with error handling - types.ts: shared TypeScript interfaces for Run, Organization, Alert, NDVIStats, InferenceResult and API responses - styles.css: design-system CSS variables (cv-* tokens), component base styles, skeleton loader, scrollbar and animation utilities - tailwind.config.js: extended theme with cv-* color palette, shadow tokens, and custom font stack matching the dark forest UI - main.tsx: React 18 createRoot entry-point with StrictMode - index.html: updated meta tags, font preload and app title - package.json: added lucide-react, recharts, react-router-dom deps - .env.example: documents VITE_GOOGLE_MAPS_API_KEY and VITE_API_BASE_URL Co-Authored-By: Emmanuel Edoh <edoh-Onuh@users.noreply.github.com> Co-Authored-By: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-Authored-By: Gold Okpa <okpagold@gmail.com> Co-Authored-By: Victor Mbachu <victor.c.mbachu@gmail.com>
- Validate bbox has exactly 4 values [west, south, east, north] - Enforce longitude bounds (-180 to 180) and latitude bounds (-90 to 90) - Ensure west < east and south < north - Validate date strings follow YYYY-MM-DD format - Ensure start_date is earlier than end_date
- Add offset query parameter for cursor-based pagination
- Return total record count alongside results for frontend page controls
- Restructure response to {total, limit, offset, runs} envelope
- Refactor WHERE clause building to avoid SQL injection via safe parameterisation
- Returns total run count, completed runs in last 7 days - Breakdown by status (pending, running, completed, failed) - Breakdown by analysis type (deforestation, ice_melting, flooding) - Alert summary: total alerts and unacknowledged count - Feeds directly into the frontend Dashboard KPI summary cards
- Log every request: method, path, status code, duration_ms, client IP - Attach X-Response-Time-Ms header to all responses for frontend monitoring - Uses Starlette BaseHTTPMiddleware for non-blocking request interception - Helps trace slow endpoints and detect unusual access patterns in production
- Reduce from 874 lines to ~100 lines (~5000 words to 596 words) - Move installation to top (line 18) - visible without scrolling - Replace imaginary API examples with real working curl + uvicorn commands - Replace fabricated benchmarks with honest in-progress markers - Remove community growth strategy, team descriptions, and execution plan - Add satellite band details to analysis types table - Keep citation, contributing, and docs links
…ments feat(api): Olufemi - API validation, pagination, stats & audit logging
- Add React components: Map, Charts, Layout, UI elements - Add contexts: AppContext, ToastContext - Add hooks: useGeocoding, useRunPolling - Add pages: Analytics, NewAnalysis, RunHistory, Settings, Upload - Update SETUP_COMPLETE.md Co-authored-by: Adeolu Mary Oshadare <nifemi996@gmail.com> Co-authored-by: John Edoh Onuh <onuhj47@gmail.com> Co-authored-by: Francis Umo <Francisumoh@360yahoo.com> Co-authored-by: Olufemi Taiwo <olufemitaiwo23@gmail.com> Co-authored-by: Godswill Chukwu Okoroafor <godswillchukwu21@gmail.com> Co-authored-by: Victor Mbachu <victor.c.mbachu@gmail.com> Co-authored-by: Paul <46930375+cutewizzy11@users.noreply.github.com> Co-authored-by: Gold Okpa <okpagold@gmail.com>
Prevent accidental commits of large .pth model files that exceed GitHub's 100MB limit.
Add centralized constants for API config, map settings, analysis types, polling intervals, and UI configurations.
feat(data): add sampling and transform utilities - Add stratified split, balanced sampling, k-fold CV - Add custom satellite imagery transforms - Add cloud masking and normalization utilities
Add comprehensive type validation schemas including: - BoundingBox and PredictionRequest for input validation - OrganizationCreate and SubscriptionCreate for entity creation - Response schemas for health, predictions, alerts, and errors Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add postprocess.py with confidence thresholding, small region removal, and anomaly detection for inference outputs. Includes quality scoring to flag predictions that may need review. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add CarbonEstimator class with: - Allometric equations for biomass estimation by forest type - IPCC-based biomass-to-carbon conversion - Monte Carlo uncertainty quantification with confidence intervals - Regional adjustment factors for Amazon, Congo, Southeast Asia Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add GroundTruthValidator with: - IoU, F1, precision, recall, accuracy, and Kappa metrics - Per-class IoU computation for multi-class segmentation - Automated recommendations based on metric thresholds - Model version comparison utility for A/B testing Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
…schemas and inference postprocessing
…rbon analytics and validation
Implements structured logging middleware with request tracing and audit trails for compliance monitoring. Includes: - RequestLoggingMiddleware: logs all requests with timing - AuditLogMiddleware: tracks sensitive operations - X-Request-ID headers for distributed tracing Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements secure API key authentication for protected endpoints: - APIKeyAuth class for key generation and validation - Secure key hashing using SHA-256 - Organization context extraction for access control - FastAPI dependencies for required/optional auth - Comprehensive audit logging for auth events Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements comprehensive statistical analysis capabilities: - Two-sample t-test (Welch's) for model comparison - Mann-Whitney U test for non-parametric analysis - Linear trend analysis for time series - A/B testing framework for model version comparison - Bootstrap confidence intervals for uncertainty estimation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implements automated report generation for stakeholders: - RegionalMetrics dataclass for environmental KPIs - ImpactReport with carbon, validation, and recommendations - ReportGenerator for JSON and HTML report output - Trend analysis integration for year-over-year comparisons - Actionable recommendations based on threshold analysis Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Updates module __init__.py to expose complete public API: - Carbon estimation: CarbonEstimator, estimate_carbon - Validation: GroundTruthValidator, validate_predictions - Statistics: t_test, mann_whitney, trend_analysis, ab_test - Reporting: ReportGenerator, generate_report Enables clean imports like: from climatevision.analytics import estimate_carbon, generate_report Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Merging Olufemi's API middleware and auth modules
Merging Francis's analytics statistics and reporting modules
* feat(data): add GEE tile downloader with analysis-aware band selection - Downloads real Sentinel-2 composites via Google Earth Engine - Reads required bands from config.yaml per analysis_type - Includes SCL band for downstream cloud masking - Synthetic fallback with explicit is_synthetic flag when GEE unavailable - Fix .gitignore so src/climatevision/data/ is no longer ignored * feat(data): add analysis-specific Sentinel-2 band mapping utilities - get_bands_for_analysis() reads correct bands from config.yaml - get_band_indices() maps band names to canonical 13-band stack positions - is_analysis_enabled() and list_enabled_analysis_types() for config validation - Includes SCL band helpers for downstream cloud masking * feat(data): integrate SCL cloud masking and export new pipeline modules - apply_scl_cloud_mask() masks cloudy pixels using Sentinel-2 SCL band - Default clear labels: vegetation, bare soils, water, snow - Update __init__.py to expose gee_downloader and band_mapping utilities * refactor(data): address PR review feedback - Remove duplicated config logic in gee_downloader.py; import from band_mapping - Cache config.yaml load in band_mapping.py via lru_cache - Read synthetic tile size from config.yaml instead of hardcoding 256 - Remove unused json import in gee_downloader.py - Add shape validation in apply_scl_cloud_mask --------- Co-authored-by: Adeolu Mary Oshadare <adeolu@placeholder.com>
…ing (#8) * feat(inference): make pipeline analysis-aware with dynamic model loading - _load_model() now accepts analysis_type and reads in_channels/num_classes from config.yaml - Per-analysis-type model cache prevents cross-contamination between deforestation/ice/flood models - _find_best_checkpoint() prefers config.yaml weight path per analysis type - run_inference() accepts analysis_type, pads/crops to correct n_channels, and returns dynamic class counts - run_inference_from_file() and run_inference_from_gee() propagate analysis_type parameter * feat(api): wire analysis_type into prediction endpoints - Pass body.analysis_type to run_inference_from_gee() in /api/predict - Pass analysis_type to run_inference_from_file() in /api/predict/upload - Enables the API to load the correct model and return correct class counts per analysis type --------- Co-authored-by: Olufemi Taiwo <Olufemitaiwo23@gmail.com>
… flag, add config health validation - Add cv_dev development key bypass for local testing - Require X-API-Key on all mutation endpoints (POST predict, orgs, alerts, subscriptions) - Surface is_synthetic at root of inference response for frontend demo banners - Expand /api/health to validate config alignment (bands vs in_channels, classes vs num_classes)
- Add FastAPI test client fixture - Create CI workflow for Python (flake8, pytest) and frontend (npm build) - Bootstrap tests/ directory structure
- Parametrize UNet init for all 3 analysis types (4ch/2cl, 4ch/3cl, 3ch/3cl) - Validate forward pass output shapes - Add Siamese change detection forward shape test
- Link to 6 active good-first-issue and help-wanted issues - Add claim workflow for new contributors - Include time estimates and skill-building map
- ../components/map/ -> ../components/Map/ - Fixes vite build failure on Linux (case-sensitive filesystem)
- Fixes pip install failure for gdal and rasterio on Ubuntu runners - Adds libgdal-dev, gdal-bin, libgl1-mesa-glx
- gdal Python package requires exact system GDAL version matching - rasterio covers all GDAL functionality we actually use - Simplify CI system deps to libgl1 only (for opencv runtime)
- Fixes ModuleNotFoundError: No module named 'climatevision' - pip install -e . registers src/ as an importable package
- ForestDataset with DataLoader support - Training/validation augmentation pipelines - Synthetic tile generation for demo/fallback mode
Resolves 6 conflict regions across auth.py, main.py, and pipeline.py from the develop→main single-trunk consolidation. Keeps dev bypass in auth, merges governance/flooding imports, fixes duplicate org param in predict_upload, adds missing numpy import, and adopts clean GEE production path (no synthetic fallbacks). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
cv_devdev bypass, removed duplicate commentorgparameter crash inpredict_upload, added missingnumpyimport, keptdict[str, Any]type annotationstorch.nn.Modulereturn type for ONNX flexibility, removed synthetic fallback logic in favor of clean GEE production pathTest plan
predict_uploadendpoint no longer crashes on import (duplicate param fix)FloodingAnalysisimport resolvedtorch.nn.Modulereturn type🤖 Generated with Claude Code