Upload utils.py
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utils.py
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import torch
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import torch.nn as nn
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from enum import Enum
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import base64
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import json
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from io import BytesIO
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from PIL import Image
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import requests
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import re
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class ImageType(Enum):
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REAL_UP_L = 0
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REAL_UP_R = 1
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REAL_DOWN_R = 2
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REAL_DOWN_L = 3
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FAKE = 4
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def crop_image_part(image: torch.Tensor,
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part: ImageType) -> torch.Tensor:
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size = image.shape[2] // 2
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if part == ImageType.REAL_UP_L:
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return image[:, :, :size, :size]
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elif part == ImageType.REAL_UP_R:
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return image[:, :, :size, size:]
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elif part == ImageType.REAL_DOWN_L:
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return image[:, :, size:, :size]
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elif part == ImageType.REAL_DOWN_R:
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return image[:, :, size:, size:]
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else:
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raise ValueError('invalid part')
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def init_weights(module: nn.Module):
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if isinstance(module, nn.Conv2d):
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torch.nn.init.normal_(module.weight, 0.0, 0.02)
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if isinstance(module, nn.BatchNorm2d):
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torch.nn.init.normal_(module.weight, 1.0, 0.02)
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module.bias.data.fill_(0)
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def load_image_from_local(image_path, image_resize=None):
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image = Image.open(image_path)
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if isinstance(image_resize, tuple):
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image = image.resize(image_resize)
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return image
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def load_image_from_url(image_url, rgba_mode=False, image_resize=None, default_image=None):
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try:
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image = Image.open(requests.get(image_url, stream=True).raw)
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if rgba_mode:
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image = image.convert("RGBA")
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if isinstance(image_resize, tuple):
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image = image.resize(image_resize)
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except Exception as e:
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image = None
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if default_image:
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image = load_image_from_local(default_image, image_resize=image_resize)
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return image
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def image_to_base64(image_array):
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buffered = BytesIO()
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image_array.save(buffered, format="PNG")
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image_b64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
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return f"data:image/png;base64, {image_b64}"
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