saliency.py 文件源码

def get_saliency_ft(img):

    # Saliency map calculation based on:

    if isinstance(img, str):
        img = skimage.io.imread(img)

    img_rgb = img_as_float(img)

    img_lab = skimage.color.rgb2lab(img_rgb)

    mean_val = np.mean(img_rgb, axis=(0, 1))

    kernel_h = (1.0 / 16.0) * np.array([[1, 4, 6, 4, 1]])
    kernel_w = kernel_h.transpose()

    blurred_l = scipy.signal.convolve2d(img_lab[:, :, 0], kernel_h, mode='same')
    blurred_a = scipy.signal.convolve2d(img_lab[:, :, 1], kernel_h, mode='same')
    blurred_b = scipy.signal.convolve2d(img_lab[:, :, 2], kernel_h, mode='same')

    blurred_l = scipy.signal.convolve2d(blurred_l, kernel_w, mode='same')
    blurred_a = scipy.signal.convolve2d(blurred_a, kernel_w, mode='same')
    blurred_b = scipy.signal.convolve2d(blurred_b, kernel_w, mode='same')

    im_blurred = np.dstack([blurred_l, blurred_a, blurred_b])

    sal = np.linalg.norm(mean_val - im_blurred, axis=2)
    sal_max = np.max(sal)
    sal_min = np.min(sal)
    sal = 255 * ((sal - sal_min) / (sal_max - sal_min))
    return sal