Exemple #1
0
#####################################################################

# 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)
Exemple #3
0
 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]]
Exemple #4
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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)