* Try to fix DDP mAP drop by setting generator's seed to RANK
* Fix default activation bug
* Update dataloaders.py
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Update dataloaders.py
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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* Detect() and Segment() fixes for CoreML and Paddle
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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* [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 min_wh
* Resolve precommit utils/segment/plots
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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>
* Add DWConvTranspose2d() module
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* Add DWConvTranspose2d() module
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* Fix
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* Fix
* Fix
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* New TensorFlow `TFCrossConv()` module
* Move from experimental to common
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* Add C3x
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* Add to C3x to yolo.py
* Add to C3x to tf.py
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* TFC3x bug fix
* TFC3x bug fix
* TFC3x bug fix
* Add TFDWConv g==c1==c2 check
* Add comment
* Update tf.py
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* [pre-commit.ci] pre-commit suggestions
updates:
- [github.com/asottile/pyupgrade: v2.31.0 → v2.31.1](https://github.com/asottile/pyupgrade/compare/v2.31.0...v2.31.1)
- [github.com/pre-commit/mirrors-yapf: v0.31.0 → v0.32.0](https://github.com/pre-commit/mirrors-yapf/compare/v0.31.0...v0.32.0)
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* Update yolo.py
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* Update
* Update
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* precommit: yapf
* align isort
* fix
# Conflicts:
# utils/plots.py
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* Update setup.cfg
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* Update wandb_utils.py
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* Update val.py
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* simplify colorstr
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* val run fix
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* Update hubconf.py
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* PyTorch Hub tuple fix
* PyTorch Hub tuple fix2
* PyTorch Hub tuple fix3
* Update setup
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* yolo.py profiling updates
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* Sidestep os.path.relpath() Windows bug
os.path.relpath() seems to have a major bug on Windows due to Windows horrible path handling. This fix attempts to sidestep the issue.
```
File "C:\Users\mkokg/.cache\torch\hub\ultralytics_yolov5_master\export.py", line 64, in
ROOT = Path(os.path.relpath(ROOT, Path.cwd())) # relative
File "C:\Users\mkokg\AppData\Local\Programs\Python\Python310\lib\ntpath.py", line 718, in relpath
raise ValueError("path is on mount %r, start on mount %r" % (
ValueError: path is on mount 'C:', start on mount 'D:'
```
* Update yolo.py
* Update yolo.py
* Update yolo.py
* Update export.py
Fix for Colab hub error:
```python
import yaml
with open('yolov5s.yaml', errors='ignore') as f:
d = yaml.safe_load(f) # model dict
print(d)
---------------------------------------------------------------------------
ReaderError Traceback (most recent call last)
<ipython-input-8-1150b5143073> in <module>()
2
3 with open('yolov5s.yaml', errors='ignore') as f:
----> 4 d = yaml.safe_load(f) # model dict
5
6 print(d)
6 frames
/usr/local/lib/python3.7/dist-packages/yaml/reader.py in check_printable(self, data)
142 position = self.index+(len(self.buffer)-self.pointer)+match.start()
143 raise ReaderError(self.name, position, ord(character),
--> 144 'unicode', "special characters are not allowed")
145
146 def update(self, length):
ReaderError: unacceptable character #x1f680: special characters are not allowed
in "yolov5s.yaml", position 9
```
Checking for `onnx_dynamic` first should suppress the warning:
```log
TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs!
if self.grid[i].shape[2:4] != x[i].shape[2:4] or self.onnx_dynamic
```
* precommit: isort
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* Update isort config
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* Update name
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* Meshgrid `indexing='ij'` for PyTorch 1.10
Will not merge currently as breaks backwards compatibility.
* Meshgrid `indexing='ij'` for PyTorch 1.10
Will not merge currently as breaks backwards compatibility.
* Add check_version hard argument
* Update comment
* fix different devices bug
* extend _apply() instead of to() for a general fix
* Only apply if Detect() is last layer
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* Indent fix
* Add comment to yolo.py
* Add comment to common.py
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Forever518
Glenn Jocher
Ayush Chaurasia
tcmyxc
pre-commit-ci[bot]
Jirka Borovec
Deep Patel
Jebastin Nadar
Zhiqiang Wang