50 lines
1.8 KiB
Python
Executable File
50 lines
1.8 KiB
Python
Executable File
import os
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from PIL import Image
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import matplotlib.pyplot as plt
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import numpy as np
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#from scipy.misc import imread,imresize
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import cv2,argparse
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parser1 = argparse.ArgumentParser(description="CUI")
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parser1.add_argument("root", default='/data1/Hatcher/model/project/data_MPKFNet/rawdata/竹林嘴-3月3日候鸟视频.mp4', type=str,
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help='root.')
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parser1.add_argument("imgsize", default='640', type=str,
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help='imgsize')
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args = parser1.parse_args()
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filepath = args.root
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imageSize = int(args.imgsize)
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pathDir = os.listdir(filepath)
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R_channel = 0
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G_channel = 0
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B_channel = 0
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for idx in range(len(pathDir)):
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filename = pathDir[idx]
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print(filename)
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img = cv2.imread(os.path.join(filepath, filename))
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img = cv2.resize(img,(imageSize,imageSize))/ 255.0
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R_channel = R_channel + np.sum(img[:, :, 0])
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G_channel = G_channel + np.sum(img[:, :, 1])
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B_channel = B_channel + np.sum(img[:, :, 2])
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num = len(pathDir) * 512 * 512 # 这里（512,512）是每幅图片的大小，所有图片尺寸都一样
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R_mean = R_channel / num
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G_mean = G_channel / num
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B_mean = B_channel / num
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R_channel = 0
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G_channel = 0
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B_channel = 0
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for idx in range(len(pathDir)):
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filename = pathDir[idx]
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print(filename)
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img = cv2.imread(os.path.join(filepath, filename))
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img = cv2.resize(img, (imageSize, imageSize)) / 255.0
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R_channel = R_channel + np.sum((img[:, :, 0] - R_mean) ** 2)
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G_channel = G_channel + np.sum((img[:, :, 1] - G_mean) ** 2)
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B_channel = B_channel + np.sum((img[:, :, 2] - B_mean) ** 2)
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R_var = np.sqrt(R_channel / num)
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G_var = np.sqrt(G_channel / num)
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B_var = np.sqrt(B_channel / num)
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print("R_mean is %f, G_mean is %f, B_mean is %f" % (R_mean, G_mean, B_mean))
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print("R_var is %f, G_var is %f, B_var is %f" % (R_var, G_var, B_var)) |