123 lines
3.3 KiB
Python
123 lines
3.3 KiB
Python
import datetime, math, os, sys, logging
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import cv2
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import numpy as np
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def f1(image_path):
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# Load an image
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img = cv2.imread(image_path)
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# img = cv2.imread(image_path, 0) # Load an image in grayscale
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b, g, r = cv2.split(img)
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cloud = r / b
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ret, cloud_BINARY = cv2.threshold(cloud, 0.6, 255, cv2.THRESH_BINARY) # 文献中推荐阈值为0.6
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cloudage = cloud_BINARY.sum() / (cloud_BINARY.size * 255)
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print("r/b算法，云量为%f\n" % cloudage)
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tmp = image_path.split('.')
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out = tmp[0] + "_r_b." + tmp[1]
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cv2.imwrite(out, cloud_BINARY)
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# cv2.imshow('image', cloud_BINARY)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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def f2(image_path):
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img = cv2.imread(image_path)
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b, g, r = cv2.split(img)
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cloud = (b-r) / (b+r)
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ret, cloud_BINARY = cv2.threshold(cloud, 0.2, 255, cv2.THRESH_BINARY_INV)
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cloudage = cloud_BINARY.sum() / (cloud_BINARY.size * 255)
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print("(b-r) / (b+r)算法，云量为%f\n" % cloudage)
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tmp = image_path.split('.')
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out = tmp[0] + "_(b-r)_(b+r)." + tmp[1]
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cv2.imwrite(out, cloud_BINARY)
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# cv2.imshow('image', cloud_BINARY)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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def f3(image_path):
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img = cv2.imread(image_path)
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b, g, r = cv2.split(img)
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# 自己计算饱和度-----> 失败：计算的饱和度不对，是负值
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ones = np.ones_like(b)
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sum = b + g + r
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min_b_g_r = np.zeros_like(b)
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for x in range(b.shape[0]):
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for y in range(b.shape[1]):
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minValue = min(b[x, y], g[x, y], r[x, y])
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min_b_g_r[x, y] = minValue
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tmp = (3/sum)*min_b_g_r
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s_tc = ones - tmp
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# 转到HSV空间
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hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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h1, s1, v1 = cv2.split(hsv)
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# 转到HLS空间
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hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS) # 这就是ihs颜色空间：
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h, l, s = cv2.split(hls)
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μ_Clouds = 12.7
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σ_Clouds = 3.7
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μ_sky = 45.3
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σ_sky = 4.4
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# np.where用法：https://www.zhihu.com/question/62844162
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clouds_loc = np.where(s < μ_Clouds + 3 * σ_Clouds) # 厚云
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sky_loc = np.where(s > μ_sky - 3 * σ_sky) # 天空
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unknow_loc = np.where((μ_Clouds + 3 * σ_Clouds <= s) & (s <= μ_sky - 3 * σ_sky)) # 薄云
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s[sky_loc] = 1
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s[clouds_loc] = 2
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s[unknow_loc] = 3
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tmp = image_path.split('.')
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out = tmp[0] + "_saturation." + tmp[1]
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cv2.imwrite(out, s)
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# cv2.imshow('image', cloud_BINARY)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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def jisuan(image_path):
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img = cv2.imread(image_path)
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hls = cv2.cvtColor(img, cv2.COLOR_BGR2HLS) # 这就是ihs颜色空间：
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h, l, s = cv2.split(hls)
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mean = np.mean(s)
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var = np.var(s)
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print("均值为：%f\n" % mean)
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print("方差为：%f\n" % var)
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if __name__ == '__main__':
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train_image_path1 = r'D:\PycharmProjects\cloudage\train\sky.jpg'
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train_image_path2 = r'D:\PycharmProjects\cloudage\train\cloude.jpg'
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train_image_path3 = r'D:\PycharmProjects\cloudage\train\light cloud.jpg'
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jisuan(train_image_path1)
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jisuan(train_image_path2)
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jisuan(train_image_path3)
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# image_path = r'D:\PycharmProjects\cloudage\photo\photo12.jpg'
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# # image_path = r'D:\PycharmProjects\cloudage\photo\cloud1_perfect.jpg' # f3全为天空
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# # f1(image_path)
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# # f2(image_path)
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# f3(image_path)
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