Last active
February 26, 2021 03:52
-
-
Save Crazz-Zaac/961f9f6b4950133a29966d09a4d2cd80 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
###content cost | |
# Assign the content image to be the input of the VGG model. | |
sess.run(model['input'].assign(content_image)) | |
# Select the output tensor of layer conv4_2 | |
out = model['conv4_2'] | |
# Set a_C to be the hidden layer activation from the layer we have selected | |
a_C = sess.run(out) | |
# Set a_G to be the hidden layer activation from same layer. Here, a_G references model['conv4_2'] | |
# and isn't evaluated yet. Later in the code, we'll assign the image G as the model input, so that | |
# when we run the session, this will be the activations drawn from the appropriate layer, with G as input. | |
a_G = out | |
# Compute the content cost | |
J_content = compute_content_cost(a_C, a_G) | |
###style cost | |
# Assign the input of the model to be the "style" image | |
sess.run(model['input'].assign(style_image)) | |
# Compute the style cost | |
J_style = compute_style_cost(model, STYLE_LAYERS) | |
###total cost | |
### START CODE HERE ### (1 line) | |
J = total_cost(J_content, J_style, alpha = 10, beta = 40) | |
### END CODE HERE ### |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment