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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
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