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I can not for the life of me figure out how to switch the image ordering. images are read in (x,x,3) format, theano requires it to be in (3,x,x) format. I tried changing the order with numpy.array([img[:,:,i] for i in range(3)])
which i guess gets the job done, but it is both ugly and i can't figure out how to reverse it to get the original image back.
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Try img. transpose(2,0,1) or img. transpose(2,1,0) .
There are two ways to represent the image data as a three dimensional array. The first involves having the channels as the last or third dimension in the array. This is called “channels last“. The second involves having the channels as the first dimension in the array, called “channels first“.
Channels first means that in a specific tensor (consider a photo), you would have (Number_Of_Channels, Height , Width) .
An RGB image has three channels: red, green, and blue. RGB channels roughly follow the color receptors in the human eye, and are used in computer displays and image scanners.
I agree with @Qualia 's comment, np.moveaxis(a, source, destination) is easier to understand. This does the job:
x = np.zeros((12, 12, 3)) x.shape #yields: (12, 12, 3) x = np.moveaxis(x, -1, 0) x.shape #yields: (3, 12, 12) You can use numpy.rollaxis to roll the axis 3 to position 1 (considering you have the batch size as dimension 0).
np.rollaxis(imagesArray, 3, 1) But, if you're using keras, you might want to change its configuration or define it per layer. Theano doesn't require anything from you if you're using Keras.
Keras can be configured with channels first or channels last, besides allowing you to define it in every individual layer, so you don't have to change your data.
Find the keras.json file and change it. The file is usually installed in C:\Users\yourusername\.keras or ~/.keras depending on your OS.
Change "image_data_format": "channels_last" to "channels_first" or vice-versa, as you wish.
Usually, working with "channels_last" is less troublesome because of a great amount of other (non convolutional) functions that work only on the last axis.
The Keras documentation has all information about parameters for layers, including the data_format parameter.
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