feat: integrates carbon estimation into API and resolves Issue #14#27
feat: integrates carbon estimation into API and resolves Issue #14#27grunffindor wants to merge 68 commits into
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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
…lufemi-improvements 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.
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>
…iddleware-audit Merging Olufemi's API middleware and auth modules
…tics-statistics Merging Francis's analytics statistics and reporting modules
Defines responsibilities, deliverables, and collaboration guidelines for the Carbon Analytics & Validation role. Co-Authored-By: Francis Umo <francis.umo@climatevision.org>
Defines responsibilities, deliverables, and collaboration guidelines for the API Development & Integration role. Co-Authored-By: Olufemi Taiwo <olufemi.taiwo@climatevision.org>
…role-document Merged by Mary Oshadare
…e-document Merged by Mary Oshadare
…mate-Vision#7) * 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 (Climate-Vision#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
- Add DONE/PENDING task list for April 2026 sprint - Include actual .github/workflows/ci.yml code in role doc - Update local CI check commands to match current workflow
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Thanks for tackling #14 @grunffindor — wiring the new analytics.carbon.CarbonEstimator into the inference path is genuinely useful work and the feature flag (enable_carbon) is the right shape. There are a few real issues to address before this can land though, and one of them is a security regression.
Blockers
1. 🚨 Auth on POST /api/organizations is commented out.
@app.post("/api/organizations", response_model=OrganizationWithKeyResponse)
def create_org(
body: CreateOrganizationRequest,
# org: dict[str, Any] = Depends(require_api_key), <-- this PR
) -> dict[str, Any]:This can't merge. The require_api_key dependency is what prevents anonymous callers from creating organizations and minting new API keys. With it disabled, anyone on the open internet can POST /api/organizations and walk away with a fresh API key for a free organization, which then bypasses every other key-gated endpoint we have. Please drop this hunk entirely — auth on create_org is intentional. If you ran into a test setup issue with the dependency (e.g. local tests failing because there's no bootstrap key), let me know and we can sort it out separately.
2. Stray indentation / whitespace edits unrelated to the feature. A few hunks have accidental trailing whitespace and an extra blank indented line inside predict_upload's exception branch (the + \n line). Please clean these up — they'll make every future blame on those lines point at this PR.
3. The branch is behind main and needs a rebase. The diff context for create_org doesn't match current main (which already does not have the require_api_key dep on that function — main and this branch have diverged). Please git fetch origin && git rebase origin/main and re-push. After the rebase, blocker #1 may resolve itself naturally (the line you're commenting out won't be there).
Should-fix
4. /api/reports/{run_id} overlaps the existing /api/reports (PR #42) namespace. That one is admin-scoped data-quality KPIs; yours is per-run impact. They can coexist because of the path parameter, but the naming will confuse callers reading the OpenAPI spec. Consider:
/api/runs/{run_id}/impact-report(RESTful, scoped under runs)- or
/api/impact-reports/{run_id}(clearly distinct from admin reports)
5. The new endpoint should probably be auth-gated too. create_org notwithstanding, /api/reports/{run_id} exposes hectares/carbon estimates for a run. If runs are tied to organizations, we should at least require an API key. Add org: dict = Depends(require_api_key) and (eventually) verify the run belongs to the caller's org.
6. enable_carbon defaults to False everywhere — please document the trade-off. Add a one-liner in the OpenAPI description= field explaining that carbon estimation adds ~N ms of post-processing per inference. Helps API consumers decide.
7. Defensive double-check on the conversion. In pipeline.py:
mask_np = (predictions == 1).squeeze(0).cpu().numpy()This assumes predictions is shape (1, H, W). If batched inference ever returns (N, H, W) you'll silently produce an (H, W) mask from only the first sample. Either assert the batch dim or iterate. @franchaise — can you confirm CarbonEstimator.estimate_from_mask is fine taking a single 2-D mask only? If batching is in the roadmap we should plumb through.
Nits
- The carbon-estimation block has
#Begin fix issue #14/#End fix issue #14sentinel comments. Drop these — git history is the record. Same for# Forwarding feature flag (Issue #14)inline tags; the PR description is the place to link the issue. - The new
ImpactReportResponseschema is declared but the endpoint returns adict, not the model. Annotate the endpoint with-> ImpactReportResponseandresponse_model=ImpactReportResponseon the decorator so FastAPI validates and the OpenAPI matches. enable_carbon:bool→enable_carbon: bool(PEP 8 spacing).
Let's get the auth hunk reverted and the rebase done; the carbon wiring itself is solid and I want this to land.
cc @franchaise for the carbon-math side.
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📢 Heads-up: repo history was rewritten today (2026-05-18) We force-pushed a cleaned history across all branches to remove an internal directory from past commits. Your code and this PR are unaffected — only the commit SHAs underneath have shifted. GitHub will re-render the diff against the new base automatically. If you have a local clone, please bring it back in sync before pushing anything else: # Option A (simplest): fresh start
git clone https://github.com/Climate-Vision/ClimateVision.git
# Option B: rebase the existing PR branch in your fork
git fetch origin
git checkout <your-branch>
git rebase origin/main # likely no conflicts
git push --force-with-leaseDo not Apologies for the interruption — really appreciate your patience here. If anything looks off after rebasing, leave a comment and I'll help unblock right away. Thanks for contributing 🙏 |
This PR resolves Issue #14 by integrating the carbon stock estimation module into the main API pipeline with graceful degradation.
Key Changes:
pipeline.pyto execute carbon math during deforestation analysis.enable_carbonfeature flag to request schemas and forwarded it through the inference endpoints.GET /api/reports/{run_id}to return structured impact reports (hectares_lost,carbon_tonnes, and confidence intervals).test_carbon.pyto validate the carbon math against expected IPCC factors.Resolves #14