BigQuery -> FCNet geo-prior pipeline#80
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Initial commit of the global geo-prior (FCNet) pipeline as used for the geoprior-fcnet-global-12317cls-v1 run: - src/dataset_tools/build_geoprior_json.py: BigQuery -> COCO-style train/val/test JSON for geo-prior training. - research/geoprior/train_geoprior.py: FCNet training wrapper around fagner-lepsAI/geo_prior, with wandb logging + per-epoch checkpoints. - research/geoprior/predict_geoprior.py: per-occurrence prior generation. - research/geoprior/fusion_eval_top5.py: geo-prior + classifier top-5 fusion evaluation. Scripts committed as-is; cleanup and reproducibility work (category-map builder, vendored geo_prior modules, README, pinned deps, .gitignore) to follow in subsequent commits. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The species->class_id map is the frozen class-space contract for the geo-prior FCNet model (output indices are bound to this alphabetical ordering). Commit it as a versioned artifact and add a builder that regenerates+verifies it from BigQuery rather than blindly overwriting. - research/geoprior/geoprior_categ_map.json: frozen 12,317-class map (snapshot public_gbif_2026-05; 6,864,466 geocoded occurrences). - research/geoprior/geoprior_categ_map.PROVENANCE.md: source BQ tables, definition, and regenerate/verify commands. - src/dataset_tools/build_geoprior_categ_map.py: rebuilds the map (and label_map/metadata/master lists) from leps-ai BQ tables; verifies against the frozen artifact and refuses to overwrite on drift. Verified: the builder reproduces the committed map exactly (12,317 entries identical) and its BQ count query matches master_species_with_counts. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Move the geo-prior scripts and frozen artifacts out of the shared src/dataset_tools/ (BQ/vision pipeline) and research/ into a dedicated src/geoprior/ package. Pure relocation — no content changes. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- geoprior_fagner/: the geo-prior FCNet network (FCNet, losses, dataloader) kept in-tree, frozen at upstream commit ff4ccd1 (Apache-2.0). Removes the dependency on an external clone. - config.py: central configuration read from environment / src/geoprior/.env. No machine-specific paths or secrets in code. - .env.sample: annotated configuration template (real .env is gitignored). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
…rdcoded paths - All scripts now import the in-tree geoprior_fagner network and read paths, BigQuery project/dataset, and W&B settings from config (no /mnt or /home paths, no sys.path hack, no secrets in code). - build_geoprior_json now reads the in-repo frozen category map (was /mnt). - Fix stale docstring: MIN_OCC_PER_SPECIES default is 0 (keep all species). - .gitignore: ignore model checkpoints (*.pth). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- README.md: end-to-end documentation (layout, .env config, each pipeline stage, inputs, model details, reproducibility). - requirements.txt: pinned dependencies for the build and training stages. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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mohamedelabbas1996
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mohamedelabbas1996
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Run the repo's pinned pre-commit hooks (black 23.3.0, isort 5.12.0 with the black profile, flake8 6.0.0) over src/geoprior/. Changes are formatting-only: line reflow, double-quote normalization, import ordering, plus dropping a stray f-prefix on a non-interpolated string (F541) in fusion_eval_top5.py. No logic changes. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Summary
Adds a self-contained geographic-prior package at
src/geoprior/. The geo-prior is a SINR-style FCNet that modelsp(species | latitude, longitude, date), no images, just coordinates/dates/labels, used to re-rank or gate the image classifier's predictions. The package covers the whole path from BigQuery occurrence data to a trained model and a top-5 fusion evaluation, with all configuration in.envand the network code vendored in-tree.Pure addition: 18 files, +1,799 / -0. No existing code is modified (aside from two
.gitignorelines).Pipeline stages
build_geoprior_categ_map.pyspecies -> class_idmap (regenerate/verify, never silent-overwrite)build_geoprior_json.pytrain/val/test.json(excludes vision val/test gbif_ids to prevent leakage)train_geoprior.pypredict_geoprior.pyfusion_eval_top5.pyChanges
Pipeline scripts: the 5 stage scripts above, run as modules from repo root (
python -m src.geoprior.<script>).Frozen artifact + provenance
geoprior_categ_map.json: frozen class-space contract, 12,317 species (snapshot 2026-05, 6,864,466 geocoded occurrences). Model output indices are bound to this alphabetical ordering, so it must not change while a model trained against it is in use.geoprior_categ_map.PROVENANCE.md: records the exact BigQuery tables + query and how to regenerate/verify.In-tree network:
geoprior_fagner/(models.py,losses.py,dataloader.py) frozen at the upstream commit, replacing the previous hardcoded external path so the package is portable.Config & reproducibility
config.py+.env.sample: every path/identifier/secret lives in.env(gitignored). Nothing hardcoded;WANDB_API_KEYandGOOGLE_APPLICATION_CREDENTIALSnever committed.requirements.txt: pinned dependency lower bounds (BigQuery build stage + Torch/timm/wandb train stage).README.md: full setup, per-stage commands, and config table..gitignore: ignore geo-prior checkpoints (*.pth).Notes for reviewers
feature/bq-squashfs-pipeline(Stage 1 sourcesgbif_occurrence_locationproduced by that branch), notmain.MIN_OCC_PER_SPECIES = 0: all species kept, no occurrence-count threshold filter.