def default_mapper(sample):
img, label = sample
img = image.simple_transform(img,
256,
224,
True,
mean=[103.94, 116.78, 123.68])
return img.flatten().astype('float32'), label
def load_data(file):
img = load_image(file)
img = simple_transform(img,
256,
224,
is_train=False,
mean=[103.94, 116.78, 123.68])
img = img.astype('float32')
img = np.expand_dims(img, axis=0)
return img
def default_mapper(is_train, sample):
'''
map image bytes data to type needed by model input layer
'''
img, label = sample
img = load_image_bytes(img)
img = simple_transform(img,
256,
224,
is_train,
mean=[103.94, 116.78, 123.68])
return img.flatten().astype('float32'), label