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Fix discriminator

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This commit is contained in:
James Betker 2020-12-01 17:45:56 -07:00
parent c963e5f2ce
commit edf408508c
2 changed files with 4 additions and 4 deletions
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2
codes/models/archs/discriminator_vgg_arch.py
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@ -118,7 +118,7 @@ class Discriminator_VGG_128_GN(nn.Module):
self.bn5_0 = nn.GroupNorm(8, nf * 8, affine=True) self.bn5_0 = nn.GroupNorm(8, nf * 8, affine=True)
self.conv5_1 = nn.Conv2d(nf * 8, nf * 8, 4, 2, 1, bias=False) self.conv5_1 = nn.Conv2d(nf * 8, nf * 8, 4, 2, 1, bias=False)
self.bn5_1 = nn.GroupNorm(8, nf * 8, affine=True) self.bn5_1 = nn.GroupNorm(8, nf * 8, affine=True)
input_img_factor = input_img_factor // 2 input_img_factor = input_img_factor / 2
final_nf = nf * 8 final_nf = nf * 8
# activation function # activation function

6
codes/scripts/extract_subimages_with_ref.py
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@ -13,14 +13,14 @@ import torch
def main(): def main():
split_img = False split_img = False
opt = {} opt = {}
opt['n_thread'] = 8 opt['n_thread'] = 16
opt['compression_level'] = 90 # JPEG compression quality rating. opt['compression_level'] = 90 # JPEG compression quality rating.
# CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer # CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer
# compression time. If read raw images during training, use 0 for faster IO speed. # compression time. If read raw images during training, use 0 for faster IO speed.
opt['dest'] = 'file' opt['dest'] = 'file'
opt['input_folder'] = 'F:\\4k6k\\datasets\\ns_images\\fkaw\\images' opt['input_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\imgset2'
opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\vixen\\512_with_ref_and_fkaw' opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\vixen\\USELESS_DELETE_ME'
opt['crop_sz'] = [1024, 2048] # the size of each sub-image opt['crop_sz'] = [1024, 2048] # the size of each sub-image
opt['step'] = [1024, 2048] # step of the sliding crop window opt['step'] = [1024, 2048] # step of the sliding crop window
opt['thres_sz'] = 512 # size threshold opt['thres_sz'] = 512 # size threshold