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from PIL import Image |
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import torch |
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import torchvision.transforms as transforms |
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def preprocess_img_from_path(path_to_image, img_size): |
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img = Image.open(path_to_image) |
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return preprocess_img(img, img_size) |
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def preprocess_img(img: Image, img_size): |
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original_size = img.size |
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transform = transforms.Compose([ |
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transforms.Resize((img_size, img_size)), |
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transforms.ToTensor(), |
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transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) |
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]) |
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img = transform(img).unsqueeze(0) |
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return img, original_size |
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def postprocess_img(img, original_size): |
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img = img.detach().cpu().squeeze(0) |
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mean = torch.tensor([0.485, 0.456, 0.406]).view(3, 1, 1) |
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std = torch.tensor([0.229, 0.224, 0.225]).view(3, 1, 1) |
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img = img * std + mean |
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img = torch.clamp(img, 0, 1) |
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img = transforms.ToPILImage()(img) |
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img = img.resize(original_size, Image.Resampling.LANCZOS) |
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return img |
