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added cyclegan model
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images/cyclegan_cezanne.png

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nicolalandro_cyclegan.md

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---
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layout: hub_detail
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background-class: hub-background
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body-class: hub
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category: researchers
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title: cyclegan
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summary: generate pictures as famous artis from photos
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image: cyclegan_cezanne.png
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author: Nicola Landro
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tags: [vision, generative]
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github-link: https://github.com/nicolalandro/cyclegan-pretrained
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github-id: nicolalandro/cyclegan-pretrained
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featured_image_1: cyclegan_cezanne.png
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featured_image_2: no-image
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accelerator: "cuda-optional"
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---
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```python
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import torch
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model = torch.hub.load('nicolalandro/cyclegan-pretrained', 'cyclegan', pretrained='img2cezanne', device='cpu')
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print(model.trained_models_list)
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```
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### Example Usage
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```python
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from torchvision import transforms
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import torch
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import urllib
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from PIL import Image
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from torchvision.utils import save_image
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model = torch.hub.load('nicolalandro/cyclegan-pretrained', 'cyclegan', pretrained='img2cezanne', device='cpu')
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model.eval()
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url = 'https://raw.githubusercontent.com/nicolalandro/cyclegan-pretrained/main/images/scala_madonnina_del_mare.jpeg'
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img = Image.open(urllib.request.urlopen(url))
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scale_factor = 0.8
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shape = [int(x * scale_factor) for x in img.size]
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transform = transforms.Compose([
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transforms.Resize(size=(shape[0], shape[1])),
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transforms.ToTensor(),
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transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
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])
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scaled_img = transform(img)
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torch_images = scaled_img.unsqueeze(0)
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with torch.no_grad():
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fake_A = 0.5 * (model(torch_images).data + 1.0)
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save_image(fake_A, 'cezanne_generated.png')
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```
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### Model Description
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This is a cyclegan, a generative model that is trained on an image style and can trasnform the generic images into images with that particular style.
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