# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np from PIL import Image def tensor2img(input_image, min_max=(-1., 1.), imtype=np.uint8): """"Converts a Tensor array into a numpy image array. Parameters: input_image (tensor) -- the input image tensor array imtype (type) -- the desired type of the converted numpy array """ if not isinstance(input_image, np.ndarray): image_numpy = input_image.numpy() # convert it into a numpy array if len(image_numpy.shape) == 4: image_numpy = image_numpy[0] if image_numpy.shape[0] == 1: # grayscale to RGB image_numpy = np.tile(image_numpy, (3, 1, 1)) image_numpy = image_numpy.clip(min_max[0], min_max[1]) image_numpy = (image_numpy - min_max[0]) / (min_max[1] - min_max[0]) image_numpy = (np.transpose( image_numpy, (1, 2, 0))) * 255.0 # post-processing: tranpose and scaling else: # if it is a numpy array, do nothing image_numpy = input_image return image_numpy.astype(imtype) def save_image(image_numpy, image_path, aspect_ratio=1.0): """Save a numpy image to the disk Parameters: image_numpy (numpy array) -- input numpy array image_path (str) -- the path of the image """ image_pil = Image.fromarray(image_numpy) h, w, _ = image_numpy.shape if aspect_ratio > 1.0: image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC) if aspect_ratio < 1.0: image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC) image_pil.save(image_path)