Mltu

Latest version: v1.2.5

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0.1.5

Changed
- seperated `CWERMetric` to `CER` and `WER` Metrics in `mltu.metrics`, Character/word rate was calculatted in a wrong way
- created setter for augmentors and transformers in DataProvider, to properlly add augmentors and transformers to the pipeline
- augmentors and transformers must inherit from `mltu.augmentors.base.Augmentor` and `mltu.transformers.base.Transformer` respectively
- updated ImageShowCV2 transformer documentation
- fixed OnnxInferenceModel in `mltu.inferenceModels` to use CPU even if GPU is available with force_cpu=True flag

Added:
- added RandomSharpen to mltu.augmentors, used for simple image augmentation;
- added ImageShowCV2 to mltu.transformers, used to show image with cv2 for debugging purposes;
- added better explained documentation
- created unittests for CER and WER in mltu.utils.text_utils and TensorFlow verion of CER and WER mltu.metrics

0.1.4

Added:
- added mltu.augmentors (RandomBrightness, RandomRotate, RandomErodeDilate) - used for simple image augmentation;

0.1.3

Initial release of mltu (Machine Learning Training Utilities)

- Project to help with training machine learning models

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