New 160-image MNIST subset composed of first 8 examples of each class. Suitable for fast CI.
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Fix duplicate plots.py
* Fix check_font()
* # torch.use_deterministic_algorithms(True)
* update doc detect->predict
* Resolve precommit for segment/train and segment/val
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* Resolve precommit for utils/segment
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* Resolve precommit utils/segment/general
* Align NMS-seg closer to NMS
* restore deterministic init_seeds code
* remove easydict dependency
* update
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* restore output_to_target mask
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* update
* cleanup
* Remove unused ImageFont import
* Unified NMS
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* DetectMultiBackend compatibility
* segment/predict.py update
* update plot colors
* fix bbox shifted
* sort bbox by confidence
* enable overlap by default
* Merge detect/segment output_to_target() function
* Start segmentation CI
* fix plots
* Update ci-testing.yml
* fix training whitespace
* optimize process mask functions (can we merge both?)
* Update predict/detect
* Update plot_images
* Update plot_images_and_masks
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* fix
* Add train to CI
* fix precommit
* fix precommit CI
* fix precommit pycocotools
* fix val float issues
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* fix masks float float issues
* suppress errors
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* fix no-predictions plotting bug
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* Add CSV Logger
* fix val len(plot_masks)
* speed up evaluation
* fix process_mask
* fix plots
* update segment/utils build_targets
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* optimize utils/segment/general crop()
* optimize utils/segment/general crop() 2
* minor updates
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* torch.where revert
* downsample only if different shape
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* loss cleanup
* loss cleanup 2
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* loss cleanup 3
* update project names
* Rename -seg yamls from _underscore to -dash
* prepare for yolov5n-seg.pt
* precommit space fix
* add coco128-seg.yaml
* update coco128-seg comments
* cleanup val.py
* Major val.py cleanup
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* precommit fix
* precommit fix
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* optional pycocotools
* remove CI pip install pycocotools (auto-installed now)
* seg yaml fix
* optimize mask_iou() and masks_iou()
* threaded fix
* Major train.py update
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* Major segments/val/process_batch() update
* yolov5/val updates from segment
* process_batch numpy/tensor fix
* opt-in to pycocotools with --save-json
* threaded pycocotools ops for 2x speed increase
* Avoid permute contiguous if possible
* Add max_det=300 argument to both val.py and segment/val.py
* fix onnx_dynamic
* speed up pycocotools ops
* faster process_mask(upsample=True) for predict
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* eliminate permutations for process_mask(upsample=True)
* eliminate permute-contiguous in crop(), use native dimension order
* cleanup comment
* Add Proto() module
* fix class count
* fix anchor order
* broadcast mask_gti in loss for speed
* Cleanup seg loss
* faster indexing
* faster indexing fix
* faster indexing fix2
* revert faster indexing
* fix validation plotting
* Loss cleanup and mxyxy simplification
* Loss cleanup and mxyxy simplification 2
* revert validation plotting
* replace missing tanh
* Eliminate last permutation
* delete unneeded .float()
* Remove MaskIOULoss and crop(if HWC)
* Final v6.3 SegmentationModel architecture updates
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* Add support for TF export
* remove debugger trace
* add call
* update
* update
* Merge master
* Merge master
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* Update dataloaders.py
* Restore CI
* Update dataloaders.py
* Fix TF/TFLite export for segmentation model
* Merge master
* Cleanup predict.py mask plotting
* cleanup scale_masks()
* rename scale_masks to scale_image
* cleanup/optimize plot_masks
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* Add Annotator.masks()
* Annotator.masks() fix
* Update plots.py
* Annotator mask optimization
* Rename crop() to crop_mask()
* Do not crop in predict.py
* crop always
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* Merge master
* Add vid-stride from master PR
* Update seg model outputs
* Update seg model outputs
* Add segmentation benchmarks
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* Add segmentation benchmarks
* Add segmentation benchmarks
* Add segmentation benchmarks
* Fix DetectMultiBackend for OpenVINO
* update Annotator.masks
* fix val plot
* revert val plot
* clean up
* revert pil
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* Fix CI error
* fix predict log
* remove upsample
* update interpolate
* fix validation plot logging
* Annotator.masks() cleanup
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* Remove segmentation_model definition
* Restore 0.99999 decimals
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Laughing-q <1185102784@qq.com>
Co-authored-by: Jiacong Fang <zldrobit@126.com>
* Temporarily remove macos-latest from CI
macos-latest causing many failed CI runs that resolve after manually re-running 2 or 3 times. I don't know what the cause is. Will replace at a later date.
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update ci-testing.yml
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Add PyTorch Hub classification CI checks
Add PyTorch Hub loading of official and custom trained classification models to CI checks.
May help resolve https://github.com/ultralytics/yolov5/issues/8790#issuecomment-1219840718
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update hubconf.py
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Add `--hard-fail` list argument to benchmarks for CI
Will cause CI to fail on a benchmark failure for given indices.
* Update ci-testing.yml
* Attempt Failure (CI should fail)
* Update benchmarks.py
* Update export.py
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* Update benchmarks.py
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* Update ci-testing.yml
* Update benchmarks.py
* Update benchmarks.py
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* Update and rename ci-testing.yml to ci.yml
* Update ci.yml
* Update ci.yml
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* Update and rename ci.yml to ci-tests.yml
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* Rename ci-tests.yml to ci-testing.yml
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* handle exceptions| attempt CI
* update
* Pre-commit manual run
* yaml one-liner
* Update ci-testing.yml
* Comment W&B CI
Leave as example for future separate CI
* Update ci-testing.yml
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Temporarily reverts https://github.com/ultralytics/yolov5/pull/4978 until torch 1.10 is released, which should resolve `urllib.error.HTTPError: HTTP Error 403: rate limit exceeded` errors generated by torch hub from GitHub actions runners.
