[GitHub] [incubator-mxnet] dwSun opened a new issue #14500: Default parameters of gluon.data.vision.transforms.RandomColorJitter should be set to 0.5

[GitBox <gi...@apache.org>]

dwSun opened a new issue #14500: Default parameters of gluon.data.vision.transforms.RandomColorJitter should be set to 0.5
URL: https://github.com/apache/incubator-mxnet/issues/14500
 
 
   ## Description
   The default parameters of gluon.data.vision.transforms.RandomColorJitter are (brightness=0, contrast=0, saturation=0, hue=0).
   According to mxnet api docs,
   ```
   
   Parameters: 
   - brightness (float) – How much to jitter brightness. brightness factor is randomly chosen from [max(0, 1 - brightness), 1 + brightness].
   - contrast (float) – How much to jitter contrast. contrast factor is randomly chosen from [max(0, 1 - contrast), 1 + contrast].
   - saturation (float) – How much to jitter saturation. saturation factor is randomly chosen from [max(0, 1 - saturation), 1 + saturation].
   -hue (float) – How much to jitter hue. hue factor is randomly chosen from [max(0, 1 - hue), 1 + hue].
   ```
   Those parametes will be choosen from [max(0, 1 - 0), 1 + 0], that is [1, 1].
   This will cause problmes.
   
   Try this script:
   ```py
   #!/usr/bin/env python3
   """Doc."""
   import mxnet as mx
   from matplotlib import pyplot as plt
   from mxnet.gluon.data.vision.transforms import Compose
   
   # %% main
   
   img = mx.image.imread('1.png')
   
   aug1 = mx.gluon.data.vision.transforms.RandomFlipLeftRight()
   aug2 = mx.gluon.data.vision.transforms.RandomResizedCrop(
       (200, 200), scale=(0.5, 1.0))
   aug3 = mx.gluon.data.vision.transforms.RandomColorJitter()
   aug4 = mx.gluon.data.vision.transforms.RandomColorJitter(
       brightness=0.5, contrast=0.5, saturation=0.5, hue=0.5)
   
   
   def show_images(imgs, num_rows, num_cols, scale=2):
       figsize = (num_cols * scale, num_rows * scale)
       _, axes = plt.subplots(num_rows, num_cols, figsize=figsize)
       for i in range(num_rows):
           for j in range(num_cols):
               axes[i][j].imshow(imgs[i * num_cols + j].asnumpy())
               axes[i][j].axes.get_xaxis().set_visible(False)
               axes[i][j].axes.get_yaxis().set_visible(False)
       return axes
   
   
   def apply(img, aug, num_rows=2, num_cols=2, scale=1.5, filename='test.png'):
       Y = [aug(img) for _ in range(num_rows * num_cols)]
       show_images(Y, num_rows, num_cols, scale)
       plt.savefig(filename)
   
   
   apply(img, Compose([aug1, aug2, aug3]), scale=8,
         filename='test-{}.png'.format('1-2-3'))
   apply(img, Compose([aug1, aug2, aug4]), scale=8,
         filename='test-{}.png'.format('1-2-4'))
   ```
   
   ## test-1-2-3.png, weird ouput.
   
   ![test-1-2-3](https://user-images.githubusercontent.com/5899962/54799441-36d24280-4c98-11e9-84fe-13db33c6feb8.png)
   
   
   ## test-1-2-4.png, this is OK
   
   ![test-1-2-4](https://user-images.githubusercontent.com/5899962/54799447-42256e00-4c98-11e9-82e3-2b6a224039e5.png)
   
   
   
   

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