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)
个人使用记录:数据增强
猜你喜欢
转载自blog.csdn.net/weixin_61235989/article/details/130194020
今日推荐
周排行