Upload app.py

app.py

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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)