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| # -*- coding: utf-8 -*- | |
| """app.ipynb | |
| Automatically generated by Colaboratory. | |
| Original file is located at | |
| https://colab.research.google.com/drive/13tu6v1reMxLATyBwle-BgpQrql9p4nqn | |
| """ | |
| from fastai.vision.all import * | |
| from fastai.basics import * | |
| from upit.models.cyclegan import * | |
| from upit.train.cyclegan import * | |
| from upit.data.unpaired import * | |
| import torchvision | |
| import gradio as gr | |
| #dls = get_dls_from_hf("huggan/horse2zebra", load_size=286) | |
| cycle_gan = CycleGAN.from_pretrained('mehdiabruee/HW4_1') | |
| totensor = torchvision.transforms.ToTensor() | |
| normalize_fn = torchvision.transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) | |
| topilimage = torchvision.transforms.ToPILImage() | |
| #model = cycle_gan.G_B.cpu().eval() | |
| model = cycle_gan.G_B.cpu().eval() | |
| def predict(input): | |
| im = normalize_fn(totensor(input)) | |
| print(im.shape) | |
| preds = model(im.unsqueeze(0))/2 + 0.5 | |
| print(preds.shape) | |
| return topilimage(preds.squeeze(0).detach()) | |
| gr_interface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(256, 256)), outputs="image", title='Horse-to-Zebra CycleGAN with UPIT', description='[This](https://huggingface.co/tmabraham/horse2zebra_cyclegan) CycleGAN model trained on [this dataset](https://huggingface.co/datasets/huggan/horse2zebra), using the [UPIT package](https://github.com/tmabraham/UPIT)', examples=['horse.jpg']) | |
| gr_interface.launch(inline=False,share=False) |