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update #2

Merged
merged 31 commits into from
Apr 1, 2022
Merged

update #2

merged 31 commits into from
Apr 1, 2022

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yeshanliu
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glenn-jocher and others added 30 commits March 21, 2022 09:33
* Update loss.py with `if self.gr < 1:`

* Update loss.py
* Update loss.py

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* Update loss.py

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Stems not working correctly for YOLOv5l with current .rstrip() implementation. After fix:
```
YOLOv5l summary: 468 layers, 46563709 parameters, 46563709 gradients, 109.3 GFLOPs
```
* Remove named arguments where possible

Speed improvements.

* Update yolo.py

* Update yolo.py

* Update yolo.py
* Multi-threaded VOC download

* Update VOC.yaml

* Update

* Update general.py

* Update general.py
* 🎉 🆕 now can read Chinese image path. 

use "cv2.imdecode(np.fromfile(f, np.uint8), cv2.IMREAD_COLOR)" instead of "cv2.imread(f)" for Chinese image path.

* Update datasets.py

* Update __init__.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Fix imwrite on non-ASCII paths

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* Update general.py

* Update __init__.py

* Update __init__.py

* Update datasets.py

* Update hubconf.py

* Update detect.py

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* Update general.py

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Update detect.py

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* Update general.py

* Update detect.py

* Update general.py

* Update general.py

* Update general.py

* Update general.py

* Update general.py

* Update general.py

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* Update general.py

* Update general.py

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Add Architecture Summary to README Tutorials

Per #6998 (comment)

* Update README.md
* 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
* NMS unused variable fix

* Update general.py
Bumps [actions/cache](https://github.com/actions/cache) from 2.1.7 to 3.
- [Release notes](https://github.com/actions/cache/releases)
- [Commits](actions/cache@v2.1.7...v3)

---
updated-dependencies:
- dependency-name: actions/cache
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
* yolo.py profiling updates

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Automatically names run as --cfg argument
* precommit: yapf

* align isort

* fix

# Conflicts:
#	utils/plots.py

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* Update setup.cfg

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* Update setup.cfg

* Update setup.cfg

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* Update wandb_utils.py

* Update augmentations.py

* Update setup.cfg

* Update yolo.py

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* Update val.py

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* simplify colorstr

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* val run fix

* export.py last comma

* Update export.py

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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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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* CLI fire prep updates

* revert unintentional TF export change
* SavedModel TF Serve Fix

Fix for #7205 proposed by @tylertroy

* Update export.py
@yeshanliu yeshanliu merged commit dfcd9eb into yeshanliu:master Apr 1, 2022
yeshanliu pushed a commit that referenced this pull request Oct 10, 2022
* Improve mAP0.5-0.95

Two changes provided
1. Added limit on the maximum number of detections for each image likewise pycocotools
2. Rework process_batch function

Changes #2 solved issue ultralytics#4251
I also independently encountered the problem described in issue ultralytics#4251 that the values for the same thresholds do not match when changing the limits in the torch.linspace function.
These changes solve this problem.

Currently during validation yolov5x.pt model the following results were obtained:
from yolov5 validation
               Class     Images     Labels          P          R     mAP@.5 mAP@.5:.95: 100%|██████████| 157/157 [01:07<00:00,  2.33it/s]
                 all       5000      36335      0.743      0.626      0.682      0.506
from pycocotools
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.505
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.685

These results are very close, although not completely pass the competition issue ultralytics#2258.
I think it's problem with false positive bboxes matched ignored criteria, but this is not actual for custom datasets and does not require an additional solution.

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* Remove line to retain pycocotools results

* Update val.py

* Update val.py

* Remove to device op

* Higher precision int conversion

* Update val.py

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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5 participants