#####################################################################
# 获得图像矩阵
if __name__ == "__main__":
# img = imread('/home/qiujiayu/图片/10_lena.jpg')
csvfile = file('/home/qiujiayu/文档/3_lena.csv', 'rb')
img = []
for line in csvfile:
img.append(line.split(','))
img = [[float(y) for y in x]for x in img]
img = np.array(img)
noise_img = sp_noise(img, 0.05)
# raw_input("================================")
img_matlab = imread('/home/qiujiayu/图片/untitled.jpg')
# 将图像矩阵归一化
# img_normalized = np.array([[[float(rgb/255.0) for rgb in y_axis] for y_axis in x_axis] for x_axis in img])
# img_nor = np.array([[float(axis/255.0) for axis in line]for line in img])
p=Pcnn_class()
img_out = p.PCNN(img_arr=img, iteration_num=30)
# img_out = img_out * 255.0
# print img_out
# raw_input("===========================================")
print "done!"
import cv2
import noise
import skfuzzy as fuzz
image = cv2.imread('lena.jpg')
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
noise_image = noise.sp_noise(gray_image,0.02)
cv2.imwrite('noiseimg.png',noise_image)
fuzz_image = fuzz.filters.fire2d(noise_image, 0, 260,1)
cv2.imwrite('fireimg.png',fuzz_image)
resize = random.uniform(0.999, 1)
dw = np.random.randint(-300, 300)
dh = np.random.randint(-300, 300)
img, boxs = rotate(os.path.join(path, name),
os.path.join(path, name[:-4] + '.txt'),
r=r,
save_name=os.path.join('save', name),
resize=resize,
dw=dw,
dh=dh)
if random.random() > 0.8:
img = gasuss_noise(img, random.uniform(0, 0.05),
random.uniform(0, 0.05))
if random.random() > 0.8:
img = sp_noise(
img,
random.uniform(0, 0.05),
)
if random.random() > 0.8:
num = np.random.randint(3, 5)
img = cv2.blur(img, (num, num))
# if random.random() > 0.8:
# contrast = random.randint(50, 100) # 对比度
# brightness = random.randint(50, 100) # 亮度
# img = cv2.addWeighted(img, contrast, img, 0, brightness)
cv2.imwrite(
os.path.join(
output, name[:-4] + '_noise_blur_' +
str(_).zfill(5) + '.jpg'), img)
# 判断异常的bbox
boxs = np.array(boxs).reshape(-1, 2)
shape = [img.shape[1], img.shape[0]]
import cv2
import noise
import skfuzzy as fuzz
image = cv2.imread('lena.jpg')
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
noise_image = noise.sp_noise(gray_image, 0.02)
cv2.imwrite('noiseimg.png', noise_image)
fuzz_image = fuzz.filters.fire2d(noise_image, 0, 260, 1)
cv2.imwrite('fireimg.png', fuzz_image)
import cv2
import noise
import scipy.ndimage
image = cv2.imread('lena.jpg')
noise_image = noise.sp_noise(image,0.02)
cv2.imwrite('noiseimg.png',noise_image)
gauss_image = scipy.ndimage.filters.gaussian_filter(noise_image, sigma=2, order=0, output=None, mode='reflect', cval=0.0)
cv2.imwrite('gaussimg.png',gauss_image)
