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import os | |
os.system("pip install gradio==2.4.6") | |
import torch | |
import gradio as gr | |
import numpy as np | |
import torchvision.utils as vutils | |
import torchvision.transforms as transforms | |
from PIL import Image | |
from torch.autograd import Variable | |
from network.Transformer import Transformer | |
LOAD_SIZE = 1280 | |
STYLE = "shinkai_makoto" | |
MODEL_PATH = "models" | |
COLOUR_MODEL = "RGB" | |
# model = Transformer() | |
# model.load_state_dict(torch.load(os.path.join(MODEL_PATH, f"{STYLE}.pth"))) | |
# model.eval() | |
# disable_gpu = torch.cuda.is_available() | |
def inference(img): | |
# # load image | |
# input_image = img.convert(COLOUR_MODEL) | |
# input_image = np.asarray(input_image) | |
# # RGB -> BGR | |
# input_image = input_image[:, :, [2, 1, 0]] | |
# input_image = transforms.ToTensor()(input_image).unsqueeze(0) | |
# # preprocess, (-1, 1) | |
# input_image = -1 + 2 * input_image | |
# if disable_gpu: | |
# input_image = Variable(input_image).float() | |
# else: | |
# input_image = Variable(input_image).cuda() | |
# # forward | |
# output_image = model(input_image) | |
# output_image = output_image[0] | |
# # BGR -> RGB | |
# output_image = output_image[[2, 1, 0], :, :] | |
# output_image = output_image.data.cpu().float() * 0.5 + 0.5 | |
# return output_image | |
return "" | |
title = "AnimeBackgroundGAN" | |
description = "CartoonGAN from [Chen et.al](http://openaccess.thecvf.com/content_cvpr_2018/CameraReady/2205.pdf) based on [Yijunmaverick's implementation](https://github.com/Yijunmaverick/CartoonGAN-Test-Pytorch-Torch)" | |
article = "<p style='text-align: center'><a href='https://github.com/venture-anime/cartoongan-pytorch' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=akiyamasho' alt='visitor badge'></center></p>" | |
examples = [ | |
["examples/garden_in.jpeg", "examples/garden_out.jpg"], | |
["examples/library_in.jpeg", "examples/library_out.jpg"], | |
] | |
gr.Interface( | |
fn=inference, | |
inputs=gr.inputs.Textbox( | |
lines=1, placeholder=None, default="", label=None | |
), | |
outputs=gr.outputs.Textbox(type="auto", label=None), | |
title=title, | |
description=description, | |
article=None, | |
examples=None, | |
allow_flagging=False, | |
allow_screenshot=False, | |
enable_queue=True, | |
).launch() | |