Update app.py

app.py

@@ -21,7 +21,7 @@ device="cpu"
 img_pipe = StableDiffusionImg2ImgPipeline.from_pretrained("AkiKagura/mkgen-diffusion", use_auth_token=YOUR_TOKEN)
 img_pipe.to(device)
 
-source_img = gr.Image(source="canvas", type="filepath", tool='color-sketch', shape=[512, 512], label="new gradio color sketch")
+source_img = gr.Image(source="canvas", type="filepath", tool='color-sketch', label="new gradio color sketch")
 
 gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[1], height="auto")
 
@@ -50,6 +50,7 @@ print("done")
 
 title="Marco Generation Sketch"
 description="<p style='text-align: center;'>Draw and use 'mkmk woman' to get Marco pics. <br />Warning: Slow process... about 10 min inference time.</p>" 
+custom_css = "style.css"
 
 
 gr.Interface(fn=infer, inputs=[source_img,
@@ -57,4 +58,4 @@ gr.Interface(fn=infer, inputs=[source_img,
     gr.Slider(2, 15, value = 7, label = 'Guidence Scale'),
     gr.Slider(10, 50, value = 25, step = 1, label = 'Number of Iterations'),
     gr.Slider(label = "Seed", minimum = 0, maximum = 2147483647, step = 1, randomize = True),
-    gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .75)], outputs=gallery,title=title,description=description).queue(max_size=100).launch(enable_queue=True)
+    gr.Slider(label='Strength', minimum = 0, maximum = 1, step = .05, value = .75)], outputs=gallery,title=title,description=description,css=custom_css).queue(max_size=100).launch(enable_queue=True)