Create app.py

app.py

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+transforms2 = A.Compose(
+    [
+        A.Resize(width=256, height=256),
+        A.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5], max_pixel_value=255),
+        ToTensorV2(),
+    ],
+    is_check_shapes=False
+)
+def style_transfer(img_file):
+    img = np.array(Image.open(img_file))
+    transform_img = transforms2(image=img)
+    input_img = transform_img["image"]
+    input_img = input_img.to(DEVICE)
+    output_img = genA(input_img)
+    return postprocess_and_show(output_img)
+    #save_image(output_img*0.5 + 0.5, f"/kaggle/working/output.png")
+
+
+image_input = gr.Image(type="filepath")
+image_output = gr.Image()
+
+demo = gr.Interface(fn=style_transfer, inputs=image_input, outputs=image_output, title="Style Transfer with CycleGAN")
+
+if __name__ == "__main__":
+    demo.launch()