Upload app.py

app.py

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+import os
+os.system("git clone https://github.com/bryandlee/animegan2-pytorch")
+os.system("gdown https://drive.google.com/uc?id=1WK5Mdt6mwlcsqCZMHkCUSDJxN1UyFi0-")
+os.system("gdown https://drive.google.com/uc?id=18H3iK09_d54qEDoWIc82SyWB2xun4gjU")
+import sys
+sys.path.append("animegan2-pytorch")
+
+import torch
+torch.set_grad_enabled(False)
+
+from model import Generator
+
+device = "cpu"
+
+model = Generator().eval().to(device)
+model.load_state_dict(torch.load("face_paint_512_v2_0.pt"))
+
+from PIL import Image
+from torchvision.transforms.functional import to_tensor, to_pil_image
+import gradio as gr
+
+def face2paint(
+    img: Image.Image,
+    size: int,
+    side_by_side: bool = False,
+) -> Image.Image:
+
+
+    input = to_tensor(img).unsqueeze(0) * 2 - 1
+    output = model(input.to(device)).cpu()[0]
+
+    if side_by_side:
+        output = torch.cat([input[0], output], dim=2)
+
+    output = (output * 0.5 + 0.5).clip(0, 1)
+
+    return to_pil_image(output)
+    
+
+
+
+import os
+import collections
+from typing import Union, List
+import numpy as np
+from PIL import Image
+
+
+import PIL.Image
+import PIL.ImageFile
+import numpy as np
+import scipy.ndimage
+    
+
+import requests
+
+def inference(img):
+    out = face2paint(img, 512)
+    return out
+      
+  
+title = "Animeganv2"
+description = "Gradio demo for AnimeGanv2 Face Portrait v2. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://github.com/bryandlee/animegan2-pytorch' target='_blank'>Github Repo</a></p>"
+
+examples=[['groot.jpeg']]
+gr.Interface(inference, gr.inputs.Image(type="pil",shape=(512,512)), gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,enable_queue=True).launch()