* add fp16 for coreml using --half
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* fix
* Cleanup
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* Update export.py
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* Update `git_describe()`
Add .git path check to avoid `fatal: not a git repository (or any of the parent directories): .git` printout
* Update general.py
* add version warning
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* Cleanup
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* Update __init__.py
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* Add support for different normalization layers.
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* Cleanup
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* set common default stride as 32
* restore default stride, and set it on argument optional
* fix wrong use of opt
* fix missing parameter of stride
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* fix format of parameters
* Update val.py
* Update common.py
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* Print dataset scan only `if RANK in (-1, 0)`
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* Simplify callbacks.py return
* Indent args (pytorch convention)
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* Copy wandb param dict before training to avoid overwrites.
Copy the hyperparameter dict retrieved from wandb configuration before passing it to `train()`. Training overwrites parameters in the dictionary (eg scaling obj/box/cls gains), which causes the values reported in wandb to not match the input values. This is confusing as it makes it hard to reproduce a run, and also throws off wandb's Bayesian sweep algorithm.
* Cleanup
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* Update export.py
Simplify code.
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* fix: disable usage of root logger
`logging.basicConfig` configures Python's root logger. This prohibits
fine control of logging, overwrites logging configuration done outside
the package, and is not best practice. Instead, the used logger is now
configured directly, and the root logger is untouched.
Example:
If yolov5 is used as part of another project with some sophisticated
logging, the internal `logging.basicConfig` call overwrites all the
external configuration.
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* Update general.py
* Update general.py
* Comment kaggle
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* enable TensorFlow ops if flag --nms or --agnostic-nms is used
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* Update
* Update
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Glenn Jocher