Instructions to use keras-io/CutMix_data_augmentation_for_image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/CutMix_data_augmentation_for_image_classification with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/CutMix_data_augmentation_for_image_classification") - Notebooks
- Google Colab
- Kaggle
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library_name: keras
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tags:
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- data-augmentation
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##
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More information needed
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## Training and evaluation data
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library_name: keras
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tags:
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- data-augmentation
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- image-classification
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# Tensorflow Keras implementation of : [CutMix data augmentation for image classification](https://keras.io/examples/vision/cutmix/)
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The full credit goes to: [Sayan Nath](https://twitter.com/sayannath2350)
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## The Data augmentation strategy
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CutMix is a data Augmentation strategy where some portion of the training example is removed and pasted with the content from other images in the training set. The labels are also mixed based on the proportion of the pixels that were combined. The full paper is at [https://arxiv.org/pdf/1905.04899.pdf](https://arxiv.org/pdf/1905.04899.pdf) by Yun et. al., 2019.
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# CutMix augmented examples from CIFAR-10
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## Training and evaluation data
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