* Remove NCOLS from tqdm
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* update
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* reformat
* Single-line argparser argument
* Update README.md
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* Update README.md
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* Add feature map to save npy files
Add feature map to save npy files,export npy files with 32 feature maps per layer.
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* Update plots.py
* Update plots.py
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* Update plots.py
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* prune unused imports
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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
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* AutoBatch, AutoAnchor `LOGGER`
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* Update autoanchor.py
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* Improve plots.py robustness
Addresses issues #5374, #5395, #5611
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* Update __init__.py
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* notebook_init
* notebook_init
* notebook_init
* notebook_init
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* notebook_init
* Created using Colaboratory
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* Logger consolidation
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* Fix `save_one_box()`
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Resolves https://github.com/ultralytics/yolov5/pull/5341#issuecomment-961774729
Tests:
```python
import glob
import re
from pathlib import Path
def increment_path(path, exist_ok=False, sep='', mkdir=False):
# Increment file or directory path, i.e. runs/exp --> runs/exp{sep}2, runs/exp{sep}3, ... etc.
path = Path(path) # os-agnostic
if path.exists() and not exist_ok:
path, suffix = (path.with_suffix(''), path.suffix) if path.is_file() else (path, '')
dirs = glob.glob(f"{path}{sep}*") # similar paths
matches = [re.search(rf"%s{sep}(\d+)" % path.stem, d) for d in dirs]
i = [int(m.groups()[0]) for m in matches if m] # indices
n = max(i) + 1 if i else 2 # increment number
path = Path(f"{path}{sep}{n}{suffix}") # increment path
if mkdir:
path.mkdir(parents=True, exist_ok=True) # make directory
return path
print(increment_path('runs'))
print(increment_path('export.py'))
print(increment_path('abc.def.dir'))
print(increment_path('abc.def.file'))
```
* 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
* 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
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* 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
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* 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
