Note
to active Office without crack, just follow https://github.com/WindowsAddict/IDM-Activation-Script,
you wiil only need to run
irm https://massgrave.dev/ias | iex
#################### MS_SSIM Loss ##################### | |
## ref code: https://stackoverflow.com/questions/39051451/ssim-ms-ssim-for-tensorflow | |
def _tf_fspecial_gauss(size, sigma): | |
"""Function to mimic the 'fspecial' gaussian MATLAB function | |
""" | |
x_data, y_data = np.mgrid[-size//2 + 1:size//2 + 1, -size//2 + 1:size//2 + 1] | |
x_data = np.expand_dims(x_data, axis=-1) | |
x_data = np.expand_dims(x_data, axis=-1) |
Note
to active Office without crack, just follow https://github.com/WindowsAddict/IDM-Activation-Script,
you wiil only need to run
irm https://massgrave.dev/ias | iex
{0: u'__background__', | |
1: u'person', | |
2: u'bicycle', | |
3: u'car', | |
4: u'motorcycle', | |
5: u'airplane', | |
6: u'bus', | |
7: u'train', | |
8: u'truck', | |
9: u'boat', |
import torch | |
import torch.nn as nn | |
import torch.nn.init as init | |
class MinibatchDiscrimination(nn.Module): | |
def __init__(self, in_features, out_features, kernel_dims, mean=False): | |
super().__init__() | |
self.in_features = in_features | |
self.out_features = out_features | |
self.kernel_dims = kernel_dims |
n02119789 1 kit_fox | |
n02100735 2 English_setter | |
n02110185 3 Siberian_husky | |
n02096294 4 Australian_terrier | |
n02102040 5 English_springer | |
n02066245 6 grey_whale | |
n02509815 7 lesser_panda | |
n02124075 8 Egyptian_cat | |
n02417914 9 ibex | |
n02123394 10 Persian_cat |
{0: 'tench, Tinca tinca', | |
1: 'goldfish, Carassius auratus', | |
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias', | |
3: 'tiger shark, Galeocerdo cuvieri', | |
4: 'hammerhead, hammerhead shark', | |
5: 'electric ray, crampfish, numbfish, torpedo', | |
6: 'stingray', | |
7: 'cock', | |
8: 'hen', | |
9: 'ostrich, Struthio camelus', |