data.py 文件源码

def read_images(filenames, domain=None, image_size=64):

    images = []
    for fn in filenames:
        image = cv2.imread(fn)
        if image is None:
            continue

        if domain == 'A':
            kernel = np.ones((3,3), np.uint8)
            image = image[:, :256, :]
            image = 255. - image
            image = cv2.dilate( image, kernel, iterations=1 )
            image = 255. - image
        elif domain == 'B':
            image = image[:, 256:, :]

        image = cv2.resize(image, (image_size,image_size))
        # Change the order of channels
        r,g,b = cv2.split(image)
        image = cv2.merge([b,g,r])
        # Scale from [0, 255] to [-1, 1]
        image = image.astype(np.float32) / 255.
        image -= 0.5
        image *= 2.0
        # TensorFlow shape (height, width, channels)
        #image = image.transpose(2,0,1)
        images.append( image )

    images = np.stack( images )
    return images