Per-class saliency maps for M-RCNN#2227
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sovrasov merged 7 commits intoopen-edge-platform:developfrom Jun 16, 2023
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Overall LGTM, though a bit hacky
GalyaZalesskaya
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sovrasov
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* per class sal maps for maskrcnn * tiling support + test enablement/fix * resolve comments * enable xai detection e2e tests * comments + mrcnn xai api test * nested lists * linters, sorry for spamming :)
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* Per-class saliency maps for M-RCNN (#2227) * per class sal maps for maskrcnn * tiling support + test enablement/fix * resolve comments * enable xai detection e2e tests * comments + mrcnn xai api test * nested lists * linters, sorry for spamming :) * Bump-up release version 1.3.1 --> 1.3.2 * Update Changelog --------- Co-authored-by: Evgeny Tsykunov <evgeny.tsykunov@intel.com>
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* per class sal maps for maskrcnn * tiling support + test enablement/fix * resolve comments * enable xai detection e2e tests * comments + mrcnn xai api test * nested lists * linters, sorry for spamming :)
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Summary
Generate per-class saliency maps for maskrcnn model, by aggregating raw segmentation masks.
For OV IR model maps are getting generated from filtered raw model predictions of mask head (implemented as postprocessing in
OTXMaskRCNNModelwrapper).For Torch model maps are getting from unfiltered raw model predictions of mask head (implemented as
RecordingForwardHook).Resolves CVS-111726.
To be done in a separate PR: add e2e tests for maskrcnn
Some results (OV iR model, coco dataset):
How to test
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Feel free to contact the maintainers if that's a concern.