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import dnnlib |
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import numpy as np |
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import PIL.Image |
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import torch |
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import legacy |
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import pickle |
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import torchvision.transforms as transforms |
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from PIL import Image |
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network_pkl = '/home/rahul/Downloads/network-snapshot-003200.pkl' |
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with open(network_pkl, 'rb') as f: |
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G = pickle.load(f)['G_ema'].cpu() |
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z = torch.randn([1, G.z_dim]).cpu() |
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c = None |
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img = G(z, c) |
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img = (img.permute(0, 2, 3, 1) * 127.5 + 128).clamp(0, 255).to(torch.uint8) |
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image=PIL.Image.fromarray(img[0].cpu().numpy(), 'RGB') |
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transform = transforms.Resize((image.height * 2, image.width * 2), interpolation=transforms.InterpolationMode.BILINEAR) |
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upscaled_image = transform(image) |
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upscaled_image.save('/home/rahul/Downloads/seed1.png') |
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