- segmentation-plan.html: the plan for panoptic segmentation of images, per library folder, stored
in .mcap chunks (no file version bump), in six phases.
- tools/export_mask2former.py: exports facebook/mask2former-swin-base-coco-panoptic to ONNX (opset 17,
dynamic batch, 384 x 384 input) and checks it against PyTorch: on 25 images, all 180 segments
identical (IoU 1.000). Writes the class list with names for people ("sky-other-merged" is "sky"),
and PyTorch's own segmentations for segment-probe -check.
- modules/Segment: runs the model with onnxruntime (CUDA, else the CPU) and makes segments of its
outputs as transformers' post_process_panoptic_segmentation does: a segment id map (longest side at
most 1024) and each segment's class, score, area and bounds. Matches PyTorch on 99.8% of pixels,
every segment scored 0.6 or more found. 57 ms an image at batch 4 on an RTX 5080 laptop.
- tools/segment_probe.jai (jai first.jai - segment_probe): segments image files; -out draws them,
-check compares with PyTorch, -dump-input writes the model's input.
- modules/onnxruntime: ort_run_float_outputs, for a model with several outputs.
- first.jai copies the model to bin/segment-models. The model itself is not in git
(modules/Segment/models, 462 MB); tools/export_mask2former.py makes it.
30 lines
761 B
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30 lines
761 B
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# Build output: binaries, copied assets and logs go to bin/, intermediates to .build/ (the
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# binding generators in modules/ make their own).
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/bin/
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/bin-headless/
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.build/
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# Debuggers and editors
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*.rdi
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.vs/
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.vscode/
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*.10x
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# fork.jai writes one with this machine's paths
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*.focus-config
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# OS and sync clutter
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.DS_Store
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Thumbs.db
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.stfolder
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# OCR: downloaded, not committed (modules/onnxruntime/fetch.jai, modules/OCR/fetch_models.jai)
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/modules/onnxruntime/windows/
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/modules/onnxruntime/linux/
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/modules/onnxruntime/macos/
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/modules/onnxruntime/download/
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/modules/OCR/models/
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# Labels: downloaded, not committed (modules/Labels/fetch_models.jai)
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/modules/Labels/models/
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# Segmentation: exported by tools/export_mask2former.py, not committed
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/modules/Segment/models/
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