資料增強-亮度-對比度-色彩飽和度-色調-銳度 不改變圖像大小

• # coding=utf-8

• import os

• import os

• import cv2

• import math

• import numpy as np

• from PIL import Image

• from PIL import ImageEnhance

• """

• 1、對比度：白色畫面(最亮時)下的亮度除以黑色畫面(最暗時)下的亮度；

• 2、色彩飽和度：：彩度除以明度，指色彩的鮮豔程度，也稱色彩的純度；

• 3、色調：向負方向調節會顯現紅色，正方向調節則增加黃色。适合對膚色對象進行微調；

• 4、銳度：是反映圖像平面清晰度和圖像邊緣銳利程度的一個名額。

• """

• def compute(img):

• per_image_Rmean = []

• per_image_Gmean = []

• per_image_Bmean = []

• per_image_Bmean.append(np.mean(img[:, :, 0]))

• per_image_Gmean.append(np.mean(img[:, :, 1]))

• per_image_Rmean.append(np.mean(img[:, :, 2]))

• R_mean = np.mean(per_image_Rmean)

• G_mean = np.mean(per_image_Gmean)

• B_mean = np.mean(per_image_Bmean)

• return math.sqrt(0.241 * (R_mean ** 2) + 0.691 * (G_mean ** 2) + 0.068 * (B_mean ** 2))

• def fun_color(image, coefficient, path_save):

• # 色度,增強因子為1.0是原始圖像

• # 色度增強 1.5

• # 色度減弱 0.8

• enh_col = ImageEnhance.Color(image)

• image_colored1 = enh_col.enhance(coefficient)

• image_colored1.save(path_save)

• def fun_Contrast(image, coefficient, path_save):

• # 對比度，增強因子為1.0是原始圖檔

• # 對比度增強 1.5

• # 對比度減弱 0.8

• enh_con = ImageEnhance.Contrast(image)

• image_contrasted1 = enh_con.enhance(coefficient)

• image_contrasted1.save(path_save)

• def fun_Sharpness(image, coefficient, path_save):

• # 銳度，增強因子為1.0是原始圖檔

• # 銳度增強 3

• # 銳度減弱 0.8

• enh_sha = ImageEnhance.Sharpness(image)

• image_sharped1 = enh_sha.enhance(coefficient)

• image_sharped1.save(path_save)

• def fun_bright(image, coefficient, path_save):

• # 變亮 1.5

• # 變暗 0.8

• # 亮度增強,增強因子為0.0将産生黑色圖像； 為1.0将保持原始圖像。

• enh_bri = ImageEnhance.Brightness(image)

• image_brightened1 = enh_bri.enhance(coefficient)

• image_brightened1.save(path_save)

• def show_all():

• file_root = "/media/data_1/data/images/"

• save_root = "/media/py/save/"

• list_file = os.listdir(file_root)

• cnt = 0

• for img_name in list_file:

• cnt += 1

• print("cnt=%d,img_name=%s" % (cnt, img_name))

• path = file_root + img_name

• name = img_name.replace(".jpg", "")

• image = Image.open(path)

• list_coe = [0.5,1,3]

• for val in list_coe:

• path_save_bright = save_root + name + "_bri_" + str(val) + ".jpg"

• fun_bright(image, val, path_save_bright)

• path_save_color = save_root + name + "_color_" + str(val) + ".jpg"

• fun_color(image, val, path_save_color)

• path_save_contra = save_root + name + "_contra_" + str(val) + ".jpg"

• fun_Contrast(image, val, path_save_contra)

• path_save_sharp = save_root + name + "_sharp_" + str(val) + ".jpg"

• fun_Sharpness(image, val, path_save_sharp)

• def my_aug():

• file_root = "/media/data_1/data/images/"

• save_root = "/media/data_2/ret/img_aug/"

• list_file = os.listdir(file_root)

• cnt = 0

• for img_name in list_file:

• cnt += 1

• print("cnt=%d,img_name=%s" % (cnt, img_name))

• path = file_root + img_name

• name = img_name.replace(".jpg", "")

• image = Image.open(path)

• img = cv2.imread(path)

• mean_1 = compute(img)

• cof = 0.0

• if mean_1 < 40:

• cof = 3.5

• elif mean_1 < 60:

• cof = 3

• elif mean_1 < 80:

• cof = 2

• elif mean_1 < 90:

• cof = 1.5

• elif mean_1 < 110:

• cof = 1.1

• elif mean_1 > 130:

• cof = 0.5

• else:

• cof = 0.75

• cof_contrast = 0.0

• if cof>1:

• cof_contrast = 1.5

• else:

• cof_contrast = 0.8

• path_save_bright = save_root + name + "_bri_" + str(cof) + '.jpg'

• fun_bright(image, cof, path_save_bright)

• path_save_sharp = save_root + name + "_sharp_" + str(2) + '.jpg'

• fun_Sharpness(image, 2, path_save_sharp)

• path_save_contra = save_root + name + "_contra_" + str(cof_contrast) + ".jpg"

• fun_Contrast(image, cof_contrast, path_save_contra)

• path_save_color = save_root + name + "_color_" + str(1.5) + ".jpg"

• fun_color(image, 1.5, path_save_color)

• if __name__ == "__main__":

• #show_all()

• my_aug()