pracheer commented on a change in pull request #9030: Fix Gan URL: https://github.com/apache/incubator-mxnet/pull/9030#discussion_r156490895
########## File path: docs/tutorials/unsupervised_learning/gan.md ########## @@ -86,25 +86,25 @@ Since the DCGAN that we're creating takes in a 64x64 image as the input, we'll u import cv2 X = np.asarray([cv2.resize(x, (64,64)) for x in X]) ``` -Each pixel in our 64x64 image is represented by a number between 0-255, that represents the intensity of the pixel. However, we want to input numbers between -1 and 1 into our DCGAN, as suggested by the research paper. To rescale our pixels to be in the range of -1 to 1, we'll divide each pixel by (255/2). This put our images on a scale of 0-2. We can then subtract by 1, to get them in the range of -1 to 1. +Each pixel in the 64x64 image is represented by a number between 0-255, that represents the intensity of the pixel. However, we want to input numbers between -1 and 1 into the DCGAN, as suggested by the research paper. To rescale the pixels to be in the range of -1 to 1, we'll divide each pixel by (255/2). This put the images on a scale of 0-2. We can then subtract by 1, to get them in the range of -1 to 1. ```python X = X.astype(np.float32)/(255.0/2) - 1.0 ``` -Ultimately, images are inputted into our neural net from a 70000x3x64x64 array, and they are currently in a 70000x64x64 array. We need to add 3 channels to our images. Typically when we are working with images, the 3 channels represent the red, green, and blue components of each image. Since the MNIST dataset is grayscale, we only need 1 channel to represent our dataset. We will pad the other channels with 0's: +Ultimately, images are inputted into the neural net from a 70000x3x64x64 array, and they are currently in a 70000x64x64 array. We need to add 3 channels to the images. Typically when we are working with images, the 3 channels represent the red, green, and blue components of each image. Since the MNIST dataset is grayscale, we only need 1 channel to represent the dataset. We will pad the other channels with 0's: Review comment: I had to convince myself by reading [this](https://www.merriam-webster.com/words-at-play/is-inputted-a-word) that _inputted_ is actually a word :). May be paraphrasing it this way sounds better: "Ultimately, images are _**fed**_ into the neural net _**through**_ a 70000x3x64x64 array _**but**_ they are currently in a 70000x64x64 array. We need to add 3 channels to the images. ". ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
