chenge to english version
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@@ -3,12 +3,12 @@ from .transforms import SobelTransform
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def get_transform():
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"""
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获取统一的图像预处理管道。
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确保训练、评估和推理使用完全相同的预处理。
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Get unified image preprocessing pipeline.
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Ensure training, evaluation, and inference use exactly the same preprocessing.
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"""
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return transforms.Compose([
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SobelTransform(), # 应用 Sobel 边缘检测
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SobelTransform(), # Apply Sobel edge detection
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transforms.ToTensor(),
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transforms.Lambda(lambda x: x.repeat(3, 1, 1)), # 适配 VGG 的三通道输入
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transforms.Lambda(lambda x: x.repeat(3, 1, 1)), # Adapt to VGG's three-channel input
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transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])
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])
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@@ -5,13 +5,13 @@ from PIL import Image
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class SobelTransform:
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def __call__(self, image):
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"""
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应用 Sobel 边缘检测,增强 IC 版图的几何边界。
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Apply Sobel edge detection to enhance geometric boundaries of IC layouts.
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参数:
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image (PIL.Image): 输入图像(灰度图)。
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Args:
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image (PIL.Image): Input image (grayscale).
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返回:
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PIL.Image: 边缘增强后的图像。
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Returns:
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PIL.Image: Edge-enhanced image.
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"""
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img_np = np.array(image)
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sobelx = cv2.Sobel(img_np, cv2.CV_64F, 1, 0, ksize=3)
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