def __call__(self, img):
"""
Args:
img (numpy ndarray): Image to be scaled.
Returns:
numpy ndarray: Rescaled image.
"""
return F.resize(img, self.size, self.interpolation)
def __call__(self, img):
"""
Args:
img (numpy ndarray): Image to be scaled.
Returns:
numpy ndarray: Rescaled image.
"""
percent = float(self.size) / min(img.shape[0], img.shape[1])
resized_width = int(round(img.shape[1] * percent))
resized_height = int(round(img.shape[0] * percent))
return F.resize(img, (resized_height, resized_width),
self.interpolation)
def __call__(self, imgs):
"""
Args:
imgs (numpy ndarray): Image sequence (time*height*width*channel) to be scaled.
Returns:
numpy ndarray: Rescaled image sequence.
"""
# Apply to all images
output_imgs = []
for I in imgs:
output_imgs.append(F.resize(I, self.size, self.interpolation))
return np.array(output_imgs)