feat: add species classifier training pipeline#69
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mihow wants to merge 1 commit intocopilot/migrate-poetry-to-uvfrom
Open
feat: add species classifier training pipeline#69mihow wants to merge 1 commit intocopilot/migrate-poetry-to-uvfrom
mihow wants to merge 1 commit intocopilot/migrate-poetry-to-uvfrom
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Add two scripts that orchestrate the full flow from a GBIF Darwin Core Archive (DwC-A) to a trained ConvNeXt-Tiny species classification model: - scripts/build_species_list.py: Bridge script that reads verbatimScientificName from a DwC-A (not included in load_dwca_data()), joins it onto the clean-dataset annotations CSV, and builds a category map JSON. - scripts/train_species_classifier.sh: Single bash script running all 7 pipeline steps with uv run: fetch-images, verify-images, clean-dataset, build_species_list.py, split-dataset, create-webdataset, train-model. Supports resuming (skips steps with existing outputs) and computes num_classes dynamically from the category map. No modifications to existing src/ code. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
scripts/build_species_list.py, a bridge script that readsverbatimScientificNamefrom a DwC-A file (not included inload_dwca_data()) and joins it onto the clean-dataset annotations CSV. Also prints DwC-A summary stats and builds acategory_map.json.scripts/train_species_classifier.sh, a single bash script that orchestrates all 7 pipeline steps from DwC-A to trained ConvNeXt-Tiny model usinguv run. Each step checks for existing outputs to support resuming interrupted runs.src/code. The bridge script works aroundload_dwca_data()not includingverbatimScientificNamein its column selection.Pipeline steps:
fetch-images->verify-images->clean-dataset->build_species_list.py->split-dataset->create-webdataset->train-modelTest plan
category_map.jsoncontains correct species-to-ID mappingMIN_INSTANCES=3and default val/test fractions apply🤖 Generated with Claude Code