Upload app.py

app.py

@@ -41,7 +41,7 @@ with gr.Blocks() as app:
     gr.Markdown("""
 # HINet (or INR-Harmonization) - A novel image Harmonization method based on Implicit neural Networks
 ## Harmonize any image you want! Arbitrary resolution, and arbitrary aspect ratio! 
-### Official Gradio Demo
+### Official Gradio Demo. See here for [**How to play with this Space**](https://github.com/WindVChen/INR-Harmonization/blob/main/assets/demo.gif)
 **Since Gradio Space only support CPU, the speed may kind of slow. You may better download the code to run locally with a GPU.**
 <a href="https://huggingface.co/spaces/WindVChen/INR-Harmon?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
 <img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for no queue on your own hardware.</p>
@@ -198,7 +198,7 @@ with gr.Blocks() as app:
             opt.split_resolution = form_split_res
             opt.save_path = None
             opt.workers = 0
-            opt.device = "cuda" if torch.cuda.is_available() else "cpu"
+            opt.device = "cpu"
 
             composite_image = np.asarray(form_composite_image)
             mask = np.asarray(form_mask_image)
@@ -219,7 +219,7 @@ with gr.Blocks() as app:
             opt.split_num = int(form_split_num)
             opt.save_path = None
             opt.workers = 0
-            opt.device = "cuda" if torch.cuda.is_available() else "cpu"
+            opt.device = "cpu"
 
             composite_image = np.asarray(form_composite_image)
             mask = np.asarray(form_mask_image)
@@ -276,4 +276,4 @@ gr.close_all()
 
 app.queue(concurrency_count=1, max_size=200, api_open=False)
 
-app.launch(show_api=False)
+app.launch(show_api=False)