import cv2

import numpy as np

import os.path

import copy

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

def noiseing(img):

#img = cv2.cvtColor(rgbimg, cv2.COLOR_BGR2GRAY)

param = 30

grayscale = 256

w = img.shape[1]

h = img.shape[0]

newimg = np.zeros((h, w, 3), np.uint8)

#row and col

for x in xrange(0, h):

for y in xrange(0, w, 2): #Avoid exceeding boundaries

r1 = np.random.random_sample()

r2 = np.random.random_sample()

z1 = param * np.cos(2 * np.pi * r2) * np.sqrt((-2) * np.log(r1))

z2 = param * np.sin(2 * np.pi * r2) * np.sqrt((-2) * np.log(r1))

fxy_0 = int(img[x, y, 0] + z1)

fxy_1 = int(img[x, y, 1] + z1)

fxy_2 = int(img[x, y, 2] + z1)

fxy1_0 = int(img[x, y + 1, 0] + z2)

fxy1_1 = int(img[x, y + 1, 1] + z2)

fxy1_2 = int(img[x, y + 1, 2] + z2)

# f(x,y)

if fxy_0 < 0:

fxy_val_0 = 0

elif fxy_0 > grayscale - 1:

fxy_val_0 = grayscale - 1

else:

fxy_val_0 = fxy_0

if fxy_1 < 0:

fxy_val_1 = 0

elif fxy_1 > grayscale - 1:

fxy_val_1 = grayscale - 1

else:

fxy_val_1 = fxy_1

if fxy_2 < 0:

fxy_val_2 = 0

elif fxy_2 > grayscale - 1:

fxy_val_2 = grayscale - 1

else:

fxy_val_2 = fxy_2

# f(x,y+1)

if fxy1_0 < 0:

fxy1_val_0 = 0

elif fxy1_0 > grayscale - 1:

fxy1_val_0 = grayscale - 1

else:

fxy1_val_0 = fxy1_0

if fxy1_1 < 0:

fxy1_val_1 = 0

elif fxy1_1 > grayscale - 1:

fxy1_val_1 = grayscale - 1

else:

fxy1_val_1 = fxy1_1

if fxy1_2 < 0:

fxy1_val_2 = 0

elif fxy1_2 > grayscale - 1:

fxy1_val_2 = grayscale - 1

else:

fxy1_val_2 = fxy1_2

newimg[x, y, 0] = fxy_val_0

newimg[x, y, 1] = fxy_val_1

newimg[x, y, 2] = fxy_val_2

newimg[x, y + 1, 0] = fxy1_val_0

newimg[x, y + 1, 1] = fxy1_val_1

newimg[x, y + 1, 2] = fxy1_val_2

#newimg = cv2.cvtColor(newimg, cv2.COLOR_GRAY2RGB)

cv2.destroyAllWindows()

return newimg

#i = 0

file_dir = "/home/xn/caffe/examples/facetestquestions/ImageDatainc/"

for class_name in os.listdir(file_dir):

#for index,name in enumerate(classes):

class_path = file_dir+class_name+"/"

for img_name in os.listdir(class_path):

img_path = class_path + img_name

image = cv2.imread(img_path)

#Simple rotation 90 degrees

rotated = rotate(image, 90)

cv2.imwrite(class_path + '/' + img_name[0:7] +'_ro90.jpg', rotated)

#Rotate 180 degrees and add Gaussian noise

rotated = rotate(image, 180)

# if __name__ == '__main__':

#print 'load %s ...' % fn

#img = cv2.imread(rotated)

# coutn = 100000

# for k in xrange(0, coutn):

# get the random point

# xi = int(np.random.uniform(0, rotated.shape[1]))

# xj = int(np.random.uniform(0, rotated.shape[0]))

# # add noise

# if rotated.ndim == 2:

# rotated[xj, xi] = 255

# elif rotated.ndim == 3:

# rotated[xj, xi, 0] = 25

# rotated[xj, xi, 1] = 20

# rotated[xj, xi, 2] = 20

#cv2.namedWindow('img')

#cv2.imshow('img', img)

#cv2.waitKey()

# cv2.destroyAllWindows()

#newimg = skimage.util.random_noise(rotated, mode='salt', seed=None, clip=False)

newimg = noiseing(rotated)

#newimg = cv2.cvtColor(newing, cv2.COLOR_GRAY2BGR)

cv2.imwrite(class_path + '/' + img_name[0:7] + '_rono.jpg', newimg)

#Image processing

size = image.shape

#Get an image that is the same as the original image, note this to use deep copy

iLR = copy.deepcopy(image)

h = size[0]

w = size[1]

for i in range(h): # row and col

for j in range(w):

iLR[i, w - 1 - j] = image[i, j] # Mirror formula

cv2.imwrite(class_path + '/' + img_name[0:7] + '_mirr.jpg', iLR)