个人使用记录：数据增强

import cv2
import numpy as np
import os.path
import copy


# 椒盐噪声
def SaltAndPepper(src, percetage):
    SP_NoiseImg = src.copy()
    SP_NoiseNum = int(percetage * src.shape[0] * src.shape[1])
    for i in range(SP_NoiseNum):
        randR = np.random.randint(0, src.shape[0] - 1)
        randG = np.random.randint(0, src.shape[1] - 1)
        randB = np.random.randint(0, 3)
        if np.random.randint(0, 1) == 0:
            SP_NoiseImg[randR, randG, randB] = 0
        else:
            SP_NoiseImg[randR, randG, randB] = 255
    return SP_NoiseImg


# 高斯噪声
def addGaussianNoise(image, percetage):
    G_Noiseimg = image.copy()
    w = image.shape[1]
    h = image.shape[0]
    G_NoiseNum = int(percetage * image.shape[0] * image.shape[1])
    for i in range(G_NoiseNum):
        temp_x = np.random.randint(0, h)
        temp_y = np.random.randint(0, w)
        G_Noiseimg[temp_x][temp_y][np.random.randint(3)] = np.random.randn(1)[0]
    return G_Noiseimg


# 昏暗
def darker(image, percetage=0.9):
    image_copy = image.copy()
    w = image.shape[1]
    h = image.shape[0]
    # get darker
    for xi in range(0, w):
        for xj in range(0, h):
            image_copy[xj, xi, 0] = int(image[xj, xi, 0] * percetage)
            image_copy[xj, xi, 1] = int(image[xj, xi, 1] * percetage)
            image_copy[xj, xi, 2] = int(image[xj, xi, 2] * percetage)
    return image_copy


# 亮度
def brighter(image, percetage=1.5):
    image_copy = image.copy()
    w = image.shape[1]
    h = image.shape[0]
    # get brighter
    for xi in range(0, w):
        for xj in range(0, h):
            image_copy[xj, xi, 0] = np.clip(int(image[xj, xi, 0] * percetage), a_max=255, a_min=0)
            image_copy[xj, xi, 1] = np.clip(int(image[xj, xi, 1] * percetage), a_max=255, a_min=0)
            image_copy[xj, xi, 2] = np.clip(int(image[xj, xi, 2] * percetage), a_max=255, a_min=0)
    return image_copy


# 旋转
def rotate(image, angle, center=None, scale=1.0):
    (h, w) = image.shape[:2]
    # If no rotation center is specified, the center of the image is set as the rotation center
    if center is None:
        center = (w / 2, h / 2)
    m = cv2.getRotationMatrix2D(center, angle, scale)
    rotated = cv2.warpAffine(image, m, (w, h))
    return rotated


# 翻转
def flip(image):
    flipped_image = np.fliplr(image)
    return flipped_image


# 图片文件夹路径
file_dir = r'/mnt/sdb1/fenghaixia/DeepGlobe-Road-Extraction-link34-py3_test_all/dataset/train3/'
save_dir_Rotate = '/mnt/sdb1/fenghaixia/DeepGlobe-Road-Extraction-link34-py3_test_all/dataset/tmp/'
for img_name in os.listdir(file_dir):
    img_path = file_dir + img_name
    img = cv2.imread(img_path)
    # cv2.imshow("1",img)
    # cv2.waitKey(5000)
    # 旋转
    rotated_90 = rotate(img, 90)
    if img_name[-3:]=='tif':
        cv2.imwrite(save_dir_Rotate + img_name[0:-7] + 'r90_sat.tif', rotated_90)
    else:
        cv2.imwrite(save_dir_Rotate + img_name[0:-8] + 'r90_mask.png', rotated_90)
    rotated_180 = rotate(img, 180)
    if img_name[-3:]=='tif':
        cv2.imwrite(save_dir_Rotate + img_name[0:-7] + 'r180_sat.tif', rotated_180)
    else:
        cv2.imwrite(save_dir_Rotate + img_name[0:-8] + 'r180_mask.png', rotated_180)
    print(img_name)

save_dir_flip = '/mnt/sdb1/fenghaixia/DeepGlobe-Road-Extraction-link34-py3/dataset/tmp/'
for img_name in os.listdir(file_dir):
    img_path = file_dir + img_name
    img = cv2.imread(img_path)
    # cv2.imshow("1",img)
    # cv2.waitKey(5000)
    # 
    flipped_img = flip(img)
    if img_name[-3:]=='tif':
        cv2.imwrite(save_dir_flip + img_name[0:-7] + 'fli_sat.tif', flipped_img)
    else:
        cv2.imwrite(save_dir_flip + img_name[0:-8] + 'fli_mask.png', flipped_img)
    # rotated_180 = rotate(img, 180)
    print(img_name)

save_dir_noise = '/mnt/sdb1/fenghaixia/DeepGlobe-Road-Extraction-link34-py3/dataset/tmp/'
for img_name in os.listdir(file_dir):
    img_path = file_dir + img_name
    img = cv2.imread(img_path)
    # cv2.imshow("1",img)
    # cv2.waitKey(5000)
    # # 增加噪声
    
    if img_name[-3:]=='tif':
        img_gauss = addGaussianNoise(img, 0.3)
        cv2.imwrite(save_dir_noise + img_name[0:-7] + 'noise_sat.tif', img_gauss)
    else:
        cv2.imwrite(save_dir_noise + img_name[0:-8] + 'noise_mask.png', img)
    print(img_name)

    
save_dir_dabr = '/mnt/sdb1/fenghaixia/DeepGlobe-Road-Extraction-link34-py3/dataset/tmp/'
for img_name in os.listdir(file_dir):
    img_path = file_dir + img_name
    img = cv2.imread(img_path)
    # cv2.imshow("1",img)
    # cv2.waitKey(5000)
    # 变亮、变暗

    if img_name[-3:] == 'tif':
        img_darker = darker(img)
        cv2.imwrite(save_dir_dabr + img_name[0:-7] + 'dar_sat.tif', img_darker)
        img_brighter = brighter(img)
        cv2.imwrite(save_dir_dabr + img_name[0:-7] + 'bri_sat.tif', img_brighter)
    else:
        cv2.imwrite(save_dir_dabr + img_name[0:-8] + 'dar_mask.png', img)
        cv2.imwrite(save_dir_dabr + img_name[0:-8] + 'bri_mask.png', img)
    print(img_name)