40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import numpy as np
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import cv2
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def compute(img, min_percentile, max_percentile):
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"""计算分位点，目的是去掉图的直方图两头的异常情况"""
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max_percentile_pixel = np.percentile(img, max_percentile)
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min_percentile_pixel = np.percentile(img, min_percentile)
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return max_percentile_pixel, min_percentile_pixel
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def aug(src):
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"""图像亮度增强"""
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if get_lightness(src) > 130:
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print("图片亮度足够，不做增强")
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# 先计算分位点，去掉像素值中少数异常值，这个分位点可以自己配置。
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max_percentile_pixel, min_percentile_pixel = compute(src, 1, 99)
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# 去掉分位值区间之外的值
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src[src >= max_percentile_pixel] = max_percentile_pixel
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src[src <= min_percentile_pixel] = min_percentile_pixel
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# 将分位值区间拉伸到0到255，这里取了255*0.1与255*0.9是因为可能会出现像素值溢出的情况，所以最好不要设置为0到255。
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out = np.zeros(src.shape, src.dtype)
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cv2.normalize(src, out, 255 * 0.1, 255 * 0.9, cv2.NORM_MINMAX)
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return out
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def get_lightness(src):
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# 计算亮度
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hsv_image = cv2.cvtColor(src, cv2.COLOR_BGR2HSV)
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lightness = hsv_image[:, :, 2].mean()
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return lightness
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