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| import torch | |
| from PIL import Image | |
| import numpy as np | |
| import os | |
| import cv2 | |
| def resize_sofa(img): | |
| img = Image.fromarray(img) | |
| width, height = img.size | |
| idx = np.argmin([width,height]) | |
| if idx==0: | |
| img1 = Image.new(img.mode, (height, height), (255, 255, 255)) | |
| img1.paste(img, ((height-width)//2, 0)) | |
| else: | |
| img1 = Image.new(img.mode, (width, width), (255, 255, 255)) | |
| img1.paste(img, (0, (width-height)//2)) | |
| newsize = (640, 640) # parameters from test script | |
| im1 = img1.resize(newsize) | |
| return im1 | |
| def resize_style(img): | |
| #img = Image.open(path)#"../style5.jpg") | |
| img = Image.fromarray(img) | |
| width, height = img.size | |
| idx = np.argmin([width,height]) | |
| #print(width,height) | |
| if idx==0: | |
| top= (height-width)//2 | |
| bottom= height-(height-width)//2 | |
| left = 0 | |
| right= width | |
| else: | |
| left = (width-height)//2 | |
| right = width - (width-height)//2 | |
| top = 0 | |
| bottom = height | |
| newsize = (640, 640) # parameters from test script | |
| im1 = img.crop((left, top, right, bottom)) | |
| copies = 8 | |
| resize = (newsize[0]//copies,newsize[1]//copies) | |
| dst = Image.new('RGB', (resize[0]*copies,resize[1]*copies)) | |
| im2 = im1.resize((resize)) | |
| for row in range(copies): | |
| im2 = im2.transpose(Image.FLIP_LEFT_RIGHT) | |
| for column in range(copies): | |
| im2 = im2.transpose(Image.FLIP_TOP_BOTTOM) | |
| dst.paste(im2, (resize[0]*row, resize[1]*column)) | |
| dst = dst.resize((newsize)) | |
| return dst | |
| def create_styledSofa(sofa,style): | |
| path_sofa,path_style = 'sofa.jpg','style.jpg' | |
| sofa.save(path_sofa) | |
| style.save(path_style) | |
| #newpath_sofa = resize_sofa(path_sofa) | |
| #newpath_style = resize_style(path_style) | |
| os.system("time python3 test.py --content "+path_sofa+" \ | |
| --style "+path_style+" \ | |
| --output . \ | |
| --vgg vgg_normalised.pth \ | |
| --decoder_path decoder_iter_160000.pth \ | |
| --Trans_path transformer_iter_160000.pth \ | |
| --embedding_path embedding_iter_160000.pth") | |
| styled_sofa = cv2.imread('sofa_stylized_style.jpg') | |
| return styled_sofa | |
| # image = Image.open('input/sofa.jpg') | |
| # image = np.array(image)[:,:600] | |
| # image = resize_sofa(image) |