[GitHub] dwSun opened a new issue #10906: transforms.Compose not working as expected.

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

dwSun opened a new issue #10906: transforms.Compose not working as expected.
URL: https://github.com/apache/incubator-mxnet/issues/10906
 
 
   ```py
   #!/usr/bin/env python3
   # %% import libs
   import mxnet as mx
   from mxnet.gluon.data.vision import transforms
   
   # %% set random seed
   mx.random.seed(123)
   
   # %% the image
   img = mx.nd.random_uniform(0,255,(1024,1024,3))
   img.shape #(1024, 1024, 3)
   img.mean().asscalar() # 127.47173
   
   # %%
   transforms.Resize((224,320))(img).shape#(320, 224, 3)
   transforms.Resize((224,320))(img).mean().asscalar()#127.2181
   
   transforms.ToTensor()(img).shape#(3, 1024, 1024)
   transforms.ToTensor()(img).mean().asscalar()#0.49988914
   
   # %% This is confusing...
   transform1 = transforms.Compose(
       [transforms.ToTensor(), # should be (1024, 1024, 3) => (3, 1024, 1024)
       transforms.Resize((224, 320))]) # should be (3, 1024, 1024) => (320, 224, 1024)
   
   # I am confused with this 2 lines
   transform1(img).shape # got (1024, 320, 224) with mxnet-mkl-1.1.0; got (320, 224, 1024) with mxnet-mkl-1.2.0b20180508
   transform1(img).mean().asscalar() #got 0.00097802561 with mxnet-mkl-1.1.0;  got 0.24939652 with mxnet-mkl-1.2.0b20180508
   
   # %% This is the one works as expected.
   transform2 = transforms.Compose(
       [transforms.Resize((224, 320)),
       transforms.ToTensor()])
   
   transform2(img).shape#(3, 320, 224)
   transform2(img).mean().asscalar() # 0.49889451
   
   # %% Guess there is a ToTensor at the end implicitly.
   transform3 = transforms.Compose(
       [transforms.Resize((224, 320))])
   
   # Actually not!
   transform3(img).shape#(320, 224, 3)
   transform3(img).mean().asscalar() # 127.2181
   
   # %% those lines works exactlly as transform1 with mxnet-mkl-1.1.0, why?
   img_mod = transforms.ToTensor()(img)
   img_mod = transforms.Resize((224, 320))(img_mod)
   img_mod = transforms.ToTensor()(img_mod)
   
   img_mod.shape#(1024, 320, 224)
   img_mod.mean().asscalar() # 0.00097802561
   
   
   ```
   tested both with opencv-python            3.4.0.12 from pypi.

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