63 lines
1.9 KiB
Python
63 lines
1.9 KiB
Python
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import cv2
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import numpy as np
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def simple_background_subtraction(background_path, foreground_path, output_path, threshold=30):
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"""
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使用前后两张图做差分，分离前景
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"""
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bg = cv2.imread(background_path)
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fg_img = cv2.imread(foreground_path)
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if bg is None or fg_img is None:
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raise FileNotFoundError("图片没找到！检查路径")
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# 确保两图大小一致
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if bg.shape != fg_img.shape:
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print("⚠️ 图片大小不一致，正在调整...")
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fg_img = cv2.resize(fg_img, (bg.shape[1], bg.shape[0]))
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# 转灰度 + 差分
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bg_gray = cv2.cvtColor(bg, cv2.COLOR_BGR2GRAY)
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fg_gray = cv2.cvtColor(fg_img, cv2.COLOR_BGR2GRAY)
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diff = cv2.absdiff(fg_gray, bg_gray)
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# 二值化
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_, mask = cv2.threshold(diff, threshold, 255, cv2.THRESH_BINARY)
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# 形态学去噪
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kernel = np.ones((5,5), np.uint8)
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mask = cv2.morphologyEx(mask, cv2.MORPH_CLOSE, kernel)
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mask = cv2.morphologyEx(mask, cv2.MORPH_OPEN, kernel)
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# 提取前景：背景变白
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result_white = fg_img.copy()
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result_white[mask == 0] = [255, 255, 255] # 背景白
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# 提取前景：背景透明（PNG）
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b, g, r = cv2.split(fg_img)
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alpha = np.where(mask > 0, 255, 0).astype(np.uint8)
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result_transparent = cv2.merge([b, g, r, alpha])
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# 保存
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cv2.imwrite(output_path + "_white.jpg", result_white)
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cv2.imwrite(output_path + "_transparent.png", result_transparent)
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print(f"✅ 保存成功：\n {output_path}_white.jpg\n {output_path}_transparent.png")
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# 显示（可选）
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cv2.imshow('Original', fg_img)
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cv2.imshow('Diff', diff)
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cv2.imshow('Mask', mask)
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cv2.imshow('Foreground', result_white)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# === 使用 ===
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if __name__ == '__main__':
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simple_background_subtraction(
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background_path='f.jpg',
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foreground_path='b.jpg',
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output_path='output/foreground',
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threshold=30
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)
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