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Automatic Data Augmentation for Deep Learning techniques

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AlessandroMinervini/Data_Augmentation_for_Deep_Learning

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Automatic Data Augmentation for Deep Learning techniques.

Goal

You can generate new data to train neural networks. This is an easy way to prevent the model overfitting.

Features

  • Crop
  • Rotate
  • Noise (Gaussian Noise added)
  • Flip-up
  • Change brightness

Examples

OriginalCropRotate
NoiseFlip-upChange brightness

Requirements

SoftwareVersionRequired
Python>= 3.5Yes
Numpy>= 1.13Yes
opencv-python>= 3.4.2.17Yes
os-Yes
logging-Yes
imageio>= 2.9.0Yes

Credits

Thanks to Alex Turner

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