fix: valid HF Space card colorTo

README.md

@@ -2,50 +2,154 @@
 title: AsteroidNET
 emoji: ☄️
 colorFrom: blue
-colorTo: indigo
+colorTo: blue
 sdk: docker
 pinned: false
 license: mit
-short_description: Automated NEO detection pipeline — interactive demo
+short_description: Automated NEO detection — IASC/Pan-STARRS/ZTF pipeline
 ---
 
-# ☄️ AsteroidNET
+# ☄️ AsteroidNET v0.2
 
-**Automated Near-Earth Object Detection System** — Interactive Demo
+**Automated Near-Earth Object Detection System**  
+Dr. Matheus Machado Rech · IASC / Pan-STARRS / ZTF
 
-Built by **Dr. Matheus Machado Rech** using Spec-Driven Development (Spec-Kit) + Denario research pipeline.
+[![CI](https://github.com/mmrech/asteroidnet/actions/workflows/ci.yml/badge.svg)](https://github.com/mmrech/asteroidnet/actions/workflows/ci.yml)
+[![Deploy](https://github.com/mmrech/asteroidnet/actions/workflows/deploy-hf.yml/badge.svg)](https://github.com/mmrech/asteroidnet/actions/workflows/deploy-hf.yml)
+[![HuggingFace](https://img.shields.io/badge/HuggingFace-Space-yellow)](https://huggingface.co/spaces/mmrech/asteroidnet)
 
-## What This App Does
+---
+
+## What it does
+
+AsteroidNET is a 6-stage automated pipeline for detecting moving solar system objects in multi-epoch FITS imaging data, compatible with IASC campaign packages from the **Caça Asteroides MCTI** program.
+
+```
+FITS Frames (4×, ~30 min cadence)
+  ↓  Stage 1: Ingest + validate (TAI/UTC corrected, byte-swapped)
+  ↓  Stage 2: Preprocess (two-pass background, cosmic-ray rejection, alignment)
+  ↓  Stage 3: Source extraction (two-pass DAOStarFinder, aperture photometry)
+  ↓  Stage 4: Catalog matching (Gaia DR3 stars + SkyBoT known SSOs removed)
+  ↓  Stage 5: Tracklet linking (Hough-transform + KD-tree, kinematic validation)
+  ↓  Stage 6: Classification (RF → CNN two-stage) + Orbit determination
+  ↓  Output: MPC 80-column astrometric records, ready for submission
+```
+
+## New in v0.2
 
-AsteroidNET is a full 6-stage astronomical pipeline for detecting previously unknown asteroids and near-Earth objects (NEOs) from time-series FITS imaging data.
+| Feature | Details |
+|---------|---------|
+| **Real FITS support** | Upload IASC campaign packages directly in the UI |
+| **TAI/UTC correction** | PS1 `MJD-OBS` is TAI; ZTF is UTC — 37-second offset handled correctly |
+| **Byte-order fix** | FITS big-endian data converted to `float32` native before `Background2D` (silent `bottleneck` bug prevented) |
+| **Two-pass background** | Source masking for unbiased sky estimation in crowded fields |
+| **SkyBoT integration** | IMCCE cone-search removes all known solar system objects from candidates |
+| **PS1 header fixes** | Missing `TIMESYS=TAI` and `RADESYS=FK5` added defensively |
+| **ZTF data access** | IRSA IBE API for multi-epoch science images |
+| **Training data builder** | Mine PS1/ZTF archives with MPC/SkyBoT labels for classifier training |
+| **GitHub Actions CI/CD** | Tests run on every PR; auto-deploys to HF Spaces on push to `main` |
 
-### Tabs
+## Gradio UI Tabs
 
-| Tab | Description |
-|-----|-------------|
-| **Pipeline Runner** | Simulate a full pipeline run — configure frame count, SNR, velocity range, detection threshold. See live stats, sky motion charts, completeness curves, and a detection table. |
-| **MPC Formatter** | Generate a Minor Planet Center 80-column astrometric observation record. |
-| **Tracklet Visualizer** | Inspect multi-frame tracklet motion: sky plane, ΔRA/ΔDec vs time, linear residuals. |
-| **Orbit Inspector** | Visualise Keplerian orbital elements (Gauss method) with uncertainty bars. |
-| **About** | Full pipeline docs, performance targets, and tech stack. |
+1. **Processar Imagens IASC** — Upload real FITS files, run full pipeline, get MPC records
+2. **Pipeline Simulator** — Simulate on synthetic data with configurable parameters
+3. **MPC Formatter** — Generate exact 80-column MPC astrometric records
+4. **Tracklet Visualizer** — Inspect sky motion, ΔRA/ΔDec, and residuals
+5. **About** — Documentation and usage guide
 
-## Pipeline Architecture
+## Using with IASC / Caça Asteroides MCTI
 
+1. Register at [iasc.cosmosearch.org](https://iasc.cosmosearch.org)
+2. Download a campaign FITS package (4 frames, ~30 min cadence, same sky field)
+3. Upload all 4 `.fits` files in the **Processar Imagens IASC** tab
+4. Enter your MPC observatory code (`F51` for Pan-STARRS; use `500` if unknown)
+5. Click **Run Pipeline** — candidate tracklets are detected and MPC records generated
+6. Copy the MPC records and submit to IASC for verification
+
+## Installation (local)
+
+```bash
+git clone https://github.com/mmrech/asteroidnet
+cd asteroidnet
+pip install -r requirements-dev.txt
+pip install -e .
+pytest tests/ -v
+python app.py
 ```
-FITS Files → [Ingestion] → [Preprocessing] → [Source Extraction]
-           → [Star Removal] → [Tracklet Linking] → [ML Classification]
-           → [Orbit Determination] → MPC 80-column Format
+
+## Data Sources
+
+| Source | Type | URL |
+|--------|------|-----|
+| Pan-STARRS DR2 | Single-epoch warp FITS images (0.25″/px) | [ps1images.stsci.edu](https://ps1images.stsci.edu) |
+| ZTF DR8 | Science + difference images (1.012″/px) | [irsa.ipac.caltech.edu](https://irsa.ipac.caltech.edu) |
+| IMCCE SkyBoT | Known SSO cone-search (1889–2060) | [ssp.imcce.fr/webservices/skybot](https://ssp.imcce.fr/webservices/skybot/) |
+| MPC MPCORB | Orbital elements for all known minor planets | [minorplanetcenter.net](https://www.minorplanetcenter.net/iau/MPCORB.html) |
+| JPL Horizons | High-precision ephemerides via `astroquery` | [ssd.jpl.nasa.gov](https://ssd.jpl.nasa.gov/horizons/) |
+
+## Critical Implementation Notes
+
+### TAI vs UTC (the most important gotcha)
+Pan-STARRS `MJD-OBS` is in **TAI** (International Atomic Time), which is 37 seconds ahead of UTC. ZTF uses **UTC**. A 37-second error corresponds to 0.5–2 arcseconds of apparent asteroid motion — enough to place a predicted position outside the detection aperture.
+
+```python
+# Pan-STARRS: MJD-OBS is TAI
+t_ps1 = Time(header["MJD-OBS"], format="mjd", scale="tai").utc
+
+# ZTF: OBSMJD is UTC
+t_ztf = Time(header["OBSMJD"], format="mjd", scale="utc")
+```
+
+### Byte-order and bottleneck
+FITS data is stored big-endian. The `bottleneck` library (used by `Background2D` for speed) silently falls back to slower numpy when given non-native-endian arrays — but with **different numerical results** due to different summation order. Fix: always call `.astype(np.float32)` after reading FITS data.
+
+### Two-pass background subtraction
+Sources bias the background estimate upward if not masked. Always:
+1. Rough background → detect sources → build mask
+2. Refined background with masked sources → final subtraction
+
+## Architecture
+
+```
+asteroidnet/
+├── config/           loader.py, defaults.yaml
+├── data_access/      ps1_client.py, ztf_client.py, skybot_client.py
+├── fits_ingestor/    ingestor.py
+├── image_preprocessor/ preprocessor.py
+├── source_extractor/ detector.py
+├── catalog_matcher/  matcher.py
+├── tracklet_linker/  linker.py
+├── candidate_classifier/ classifier.py
+├── orbit_determination/  gauss_method.py
+├── reporting/        mpc_formatter.py
+├── training/         dataset_builder.py
+├── pipeline/         runner.py
+└── utils/            time_utils.py, synthetic.py
 ```
 
 ## Performance Targets
 
-- Detection completeness ≥ 90% at SNR ≥ 5  
-- False positive rate < 1%  
-- 500+ FITS frames processed in < 4 hours  
-- Star removal completeness > 99.5% (Gaia DR3)  
-- MPC format output: exactly 80 columns  
+| Metric | Target | Notes |
+|--------|--------|-------|
+| Recovery rate (SNR ≥ 5) | ≥ 90% | SC-001 |
+| False positive rate | < 1% | SC-002 |
+| Star removal completeness | > 99.5% | Gaia DR3 |
+| Astrometric residual RMS | < 1 arcsec | Per tracklet |
+| Processing time (4 frames) | < 5 min | On CPU |
+
+## License
 
-## Technology Stack
+MIT — see [LICENSE](LICENSE)
 
-`astropy` · `photutils` · `astroquery` · `reproject` · `astroscrappy` · `sbpy`  
-`scikit-learn` · `PyTorch` · `SQLAlchemy` · `Celery` · `FastAPI` · `PostgreSQL+PostGIS`
+## Citation
+
+If you use AsteroidNET in your research, please cite:
+
+```bibtex
+@software{rech2026asteroidnet,
+  author = {Rech, Matheus Machado},
+  title  = {AsteroidNET: Automated Near-Earth Object Detection System},
+  year   = {2026},
+  url    = {https://github.com/mmrech/asteroidnet}
+}
+```