* Autobatch

* fix mem

* fix mem2

* Update

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* Update train.py

* print result

* Cleanup print result

* swap fix in call

* to 64

* use total

* fix

* fix

* fix

* fix

* fix

* Update

* Update

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* Update

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* Update

* Cleanup printing

* Update final printout

* Update autobatch.py

* Update autobatch.py

* Update autobatch.py

* Minor fixes of the git checkout new branch

* Use em dash to quote

* Revert the change of git checkout

* Maybe we should up-to-date with the upstream/master?

* Add nano model to the download list

* Add possibility to also download the "*6" models

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

* take EXIF orientation tags into account when fixing corrupt images

* fit 120 char

* sort imports

* Update local exif_transpose comment

We have a local inplace version that is faster than the official as the image is not copied. AutoShape() uses this for Hub models, but here it is not important as the datasets.py usage is infrequent (AutoShape() it is applied every image).

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

* take image files with uppercase extensions into account in autosplit

* case fix

* Refactor implementation

Removes additional variable (capital variable names are also only for global variables), and uses the same methodology as implemented earlier in datasets.py L409.

* Remove redundant rglob characters
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Update token with workflows permissions

Bumps [actions/stale](https://github.com/actions/stale) from 3 to 4.
- [Release notes](https://github.com/actions/stale/releases)
- [Changelog](https://github.com/actions/stale/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/stale/compare/v3...v4)

---
updated-dependencies:
- dependency-name: actions/stale
  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>

Bumps [actions/cache](https://github.com/actions/cache) from 1 to 2.1.6.
- [Release notes](https://github.com/actions/cache/releases)
- [Commits](https://github.com/actions/cache/compare/v1...v2.1.6)

---
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>

Bumps [cirrus-actions/rebase](https://github.com/cirrus-actions/rebase) from 1.4 to 1.5.
- [Release notes](https://github.com/cirrus-actions/rebase/releases)
- [Commits](https://github.com/cirrus-actions/rebase/compare/1.4...1.5)

---
updated-dependencies:
- dependency-name: cirrus-actions/rebase
  dependency-type: direct:production
  update-type: version-update:semver-minor
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

* Add `on_fit_epoch_end` callback

* Add results to train

* Update __init__.py

* Clip Objects365 autodownload labels (#5214)

Fixes out of bounds labels that seem to affect ~10% of images in dataset.

* Inplace ops

* Autofix duplicate labels

PR changes duplicate label handling from report error and ignore image-label pair to report warning and autofix image-label pair. 

This should fix this common issue for users and allow everyone to get started and get a model trained faster and easier than before.

* sign fix

* Cleanup

* Increment cache version

* all to any fix

* Update Objects365.yaml

Download the official Objects365 validation set and convert the labels

* Enforce 4-space indent, reformat and cleanup

* shorten list comprehension
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add hyp.scratch-med.yaml

* Update hyp.scratch-med.yaml

* Highlight contributors in README

* Adjust Contact section

* Update README.md

* Improved check_suffix() robustness to `''` and `""`

* Cleanup

* legend-labels Adjust legend labels for classes without instances.

* #5158 Re-indexed series names: only classes containing data.

* #5158 Re-indexed series names: only classes containing data.

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

* fix dpp with wandb disabled

* PyCharm reformat

* Fix

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

* fix dpp with wandb disabled

* PyCharm reformat
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Add train class filter feature to datasets.py

Allows for training on a subset of total classes if `include_class` list is defined on datasets.py L448:
```python
        include_class = []  # filter labels to include only these classes (optional)
```

* segments fix

* Check `'onnxruntime-gpu' if torch.has_cuda`

* fix indent

* fix `tf` conversion in new v6 (#5147)

* sort imports
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update P5 models

* Update P6 models

* Update with GFLOPs and Params

* Update with GFLOPs and Params

* Update README

* Update

* Update README

* Update

* Update

* Add times

* Update README

* Update results

* Update results

* Update results

* Update hyps

* Update plots

* Update plots

* Update README.md

* Add nano models to hubconf.py

* update detect.py in order to support torch script

This change assumes the torchscrip file was previously saved with `export.py`

* update `detect.py` for torchscript support

Simple update for torchscript support. Assumes the torchscript file has been generated with `export.py`

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

* Add OpenCV DNN option for ONNX inference

Usage:

```bash
python detect.py --weights yolov5s.onnx  # ONNX Runtime inference
python detect.py --weights yolov5s.onnx -dnn  # OpenCV DNN inference
```

* DNN prediction to tensor

* Update detect.py

* refactor anchors and anchor_grid in Detect Layer

* fix CI failures by adding compatibility

* fix tf failure

* fix different devices errors

* Cleanup

* fix anchors overwriting issue

* better refactoring

* Remove self.anchor_grid shape check (redundant with self.grid check)

Also PEP8 / 120 line width

* Convert _make_grid() from static to dynamic method

* Remove anchor_grid.to(device)

clone() should already clone to same device as self.anchors

* fix different devices error
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* use os.path.relpath instead of relative_to

* use os.path.relpath instead of relative_to

* Remove os.path from val.py

* Remove os.path from train.py

* Update detect.py import to os

* Update export.py import to os
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update val.py `pad = 0.0 if task == speed else 0.5`

* Cleanup