Create app.py

app.py

@@ -0,0 +1,24 @@
+import os
+os.system("hub install stylepro_artistic==1.0.1")
+import gradio as gr
+import paddlehub as hub
+import numpy as np
+from PIL import Image
+import cv2 
+
+stylepro_artistic = hub.Module(name="stylepro_artistic")
+
+def inference(content,style):
+    result = stylepro_artistic.style_transfer(
+    images=[{
+        'content': cv2.imread(content.name),
+        'styles': [cv2.imread(style.name)]
+    }])
+    return Image.fromarray(np.uint8(result[0]['data'])[:,:,::-1]).convert('RGB')
+    
+title = " StyleProNet"
+description = "Gradio demo for Parameter-Free Style Projection for Arbitrary Style Transfer. 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://arxiv.org/abs/2003.07694'target='_blank'>Parameter-Free Style Projection for Arbitrary Style Transfer</a> | <a href='https://github.com/PaddlePaddle/PaddleHub' target='_blank'>Github Repo</a></p>"
+examples=[['mona1.jpeg','starry.jpeg']]
+iface = gr.Interface(inference, inputs=[gr.inputs.Image(type="file",label='content'),gr.inputs.Image(type="file",label='style')], outputs=gr.outputs.Image(type="pil"),enable_queue=True,title=title,article=article,description=description,examples=examples)
+iface.launch()