randaugment

an personal implementation about google's Randaugment (testing accuracy in cifar-10) in computer vision.

This repo a partly copy from https://github.com/DeepVoltaire/AutoAugment ,it a implemetation about autoaugment published by google . I just change some code about operations selected way.

I must say a very important point here , there is no need to set the param magnitude as same as google's , there is different best max magnitude for different dataset , so I wrote a test fun for you to test every single operation with different magnitude.

1： if you want to just call this class ,write like above , this is for call the whole function

img_augment = Rand_Augment()
img_origal = Image.open(r'0a38b552372d.png')
img_final = img_augment(img_origal)
plt.imshow(img_final)
plt.show()
print('how to call')

2: if you want to test a single function,write like above

img_augment = Rand_Augment()
img_origal = Image.open(r'0a38b552372d.png')
img_final = img_augment.test_single_operation(img_origal, 'shearX')
plt.imshow(img_final)
plt.show()
print('how to test')

Actually ,this is my first time to write a reposity in Github , if there is some bug here , just point it directly. I'm almost in the internet every day :)