fcc43d79d2ea107c789d53424825ec9ffe8788f8,vgg.py,,load_net,#,22

Before Change

def load_net(data_path):
    data = scipy.io.loadmat(data_path)
    if not all(i in data for i in ("layers", "classes", "normalization")):
        raise ValueError("You"re using the wrong VGG19 data. Please follow the instructions in the README to download the correct data.")
    mean = data["normalization"][0][0][0]
    mean_pixel = np.mean(mean, axis=(0, 1))

After Change

def load_net(data_path):
    data = scipy.io.loadmat(data_path)
    if "normalization" in data:
        // old format, for data where
        // MD5(imagenet-vgg-verydeep-19.mat) = 8ee3263992981a1d26e73b3ca028a123
        mean_pixel = np.mean(data["normalization"][0][0][0], axis=(0, 1))
    else:
        // new format, for data where
        // MD5(imagenet-vgg-verydeep-19.mat) = 106118b7cf60435e6d8e04f6a6dc3657
        mean_pixel = data["meta"]["normalization"][0][0][0][0][2][0][0]
    weights = data["layers"][0]
    return weights, mean_pixel

def net_preloaded(weights, input_image, pooling):

Instances