Update readme.md and script for image generating
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import Augmentor
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def main():
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import Augmentor
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p = [Augmentor.Pipeline("Images/TrainingImages/glass"),
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Augmentor.Pipeline("Images/TrainingImages/metal"),
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Augmentor.Pipeline("Images/TrainingImages/paper"),
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Augmentor.Pipeline("Images/TrainingImages/plastic")]
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for i in range(len(p)):
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# Setting rotate values
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p[i].rotate(probability=0.7, max_left_rotation=10, max_right_rotation=10)
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p = [Augmentor.Pipeline("Images/TrainingImages/glass"),
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Augmentor.Pipeline("Images/TrainingImages/metal"),
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Augmentor.Pipeline("Images/TrainingImages/paper"),
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Augmentor.Pipeline("Images/TrainingImages/plastic")]
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# Setting zoom values
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p[i].zoom(probability=0.5, min_factor=1.1, max_factor=1.5)
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# Size of training sample
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p[i].sample(1000)
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p[i].process()
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for i in range(len(p)):
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p[i].rotate(probability=0.7, max_left_rotation=10, max_right_rotation=10)
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p[i].zoom(probability=0.5, min_factor=1.1, max_factor=1.5)
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p[i].sample(1000)
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p[i].process()
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if __name__ == "__main__":
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main()
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@ -11,7 +11,7 @@
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- [NumPy](http://www.numpy.org/)
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- [PyQt5](https://pypi.org/project/PyQt5/)
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- [TensorFlow](https://www.tensorflow.org/)
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- [Augmentor](https://github.com/mdbloice/Augmentor)
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- [Augmentor](https://augmentor.readthedocs.io)
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**Credits**
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- As a learning set of images I used images from [this](https://github.com/garythung/trashnet) project.
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