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| # -------------------------------------------------------- | |
| # X-Decoder -- Generalized Decoding for Pixel, Image, and Language | |
| # Copyright (c) 2022 Microsoft | |
| # Licensed under The MIT License [see LICENSE for details] | |
| # Written by Xueyan Zou (xueyan@cs.wisc.edu) | |
| # -------------------------------------------------------- | |
| import cv2 | |
| import torch | |
| import numpy as np | |
| from PIL import Image | |
| from torchvision import transforms | |
| t = [] | |
| t.append(transforms.Resize(224, interpolation=Image.BICUBIC)) | |
| transform = transforms.Compose(t) | |
| t = [] | |
| t.append(transforms.Resize(512, interpolation=Image.BICUBIC)) | |
| transform_v = transforms.Compose(t) | |
| def image_captioning(model, image, texts, inpainting_text, *args, **kwargs): | |
| with torch.no_grad(): | |
| image_ori = transform_v(image) | |
| width = image_ori.size[0] | |
| height = image_ori.size[1] | |
| image_ori = np.asarray(image_ori) | |
| image = transform(image) | |
| image = np.asarray(image) | |
| images = torch.from_numpy(image.copy()).permute(2,0,1).cuda() | |
| batch_inputs = [{'image': images, 'height': height, 'width': width, 'image_id': 0}] | |
| outputs = model.model.evaluate_captioning(batch_inputs) | |
| text = outputs[-1]['captioning_text'] | |
| image_ori = image_ori.copy() | |
| cv2.rectangle(image_ori, (0, height-60), (width, height), (0,0,0), -1) | |
| font = cv2.FONT_HERSHEY_DUPLEX | |
| fontScale = 1.2 | |
| thickness = 2 | |
| lineType = 2 | |
| bottomLeftCornerOfText = (10, height-20) | |
| fontColor = [255,255,255] | |
| cv2.putText(image_ori, text, | |
| bottomLeftCornerOfText, | |
| font, | |
| fontScale, | |
| fontColor, | |
| thickness, | |
| lineType) | |
| torch.cuda.empty_cache() | |
| return Image.fromarray(image_ori), text, None | |