43 lines
1.3 KiB
Python
43 lines
1.3 KiB
Python
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import cv2
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import numpy as np
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def template_matching_visualization(original_image_path, template_image_path):
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# 读取原始图像和模板图像
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img = cv2.imread(original_image_path)
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template = cv2.imread(template_image_path)
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# 确认模板大小为64x64，如果不是请调整
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if template.shape[0] != 64 or template.shape[1] != 64:
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print("警告：模板图像尺寸不是64x64")
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# 执行模板匹配，采用的方法是平方差匹配 method=cv2.TM_SQDIFF
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result = cv2.matchTemplate(img, template, cv2.TM_SQDIFF_NORMED)
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# 寻找最匹配的位置
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min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
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# 获取匹配位置的左上角坐标
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top_left = min_loc
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h, w = template.shape[:2]
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# 计算右下角坐标
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bottom_right = (top_left[0] + w, top_left[1] + h)
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# 在原图上绘制矩形框显示匹配到的位置
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cv2.rectangle(img, top_left, bottom_right, (0, 255, 0), 2)
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# 显示结果图像
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cv2.imshow("Matched Image", img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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return top_left, bottom_right
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# 调用函数并传入原图和子图路径
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original_image_path = '1.jpg'
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template_image_path = '12.jpg'
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position = template_matching_visualization(original_image_path, template_image_path)
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print("匹配位置的左上角坐标: ", position)
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