* Update train.py
As see in #6463, modification on train in evolve process to allow custom save directory.
* fix val
* PEP8
whitespace around operator
* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* New flag 'stop_training' in util.callbacks.Callbacks class to prematurely stop training from callback handler
* Removed most of the new checks, leaving only the one after calling 'on_train_batch_end'
* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* 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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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* Logger consolidation
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* write date in checkpoint file
write date in checkpoint file
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* isoformat
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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
* precommit: isort
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* Update isort config
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* Update name
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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>
This PR adds a new training argument `--save-period` to save training checkpoints every `x` epochs. To save training every 50 epochs for example:
```
python train.py --save-period 50 # saves epoch50.pt, epoch100.pt, epoch150.pt, ... etc.
```
This saved checkpoints in addition to existing last.pt and best.pt checkpoints and does not affect their behavior. Default value is -1, i.e. disabled.
* Validate best.pt on train end
* 0.7 iou for COCO only
* pass callbacks
* active model.float() if not half
* print Validating best.pt...
* add newline