Revert lagi.

app.py

@@ -48,39 +48,15 @@ def generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_s
 
     torch.cuda.empty_cache()
 
-    return image, seed, prompt, negative_prompt, guidance_scale, num_inference_steps, resolution
+    return image, seed
 
 # Define Gradio interface
 def interface_fn(prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress=gr.Progress()):
-    image, seed, prompt, negative_prompt, guidance_scale, num_inference_steps, resolution = generate_image(
-        prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress
-    )
-    
-    generation_details = (
-        f"{prompt}\n"
-        f"Negative Prompt: {negative_prompt}\n"
-        f"Steps: {num_inference_steps}\n"
-        f"Sampler: Euler a\n"
-        f"CFG scale: {guidance_scale}\n"
-        f"Seed: {seed}\n"
-        f"Size: {resolution}"
-    )
-    
-    return image, seed, gr.update(value=seed), gr.update(visible=True), generation_details
+    image, seed = generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress)
+    return image, seed, gr.update(value=seed)
 
 def reset_inputs():
-    return (
-        gr.update(value=''), 
-        gr.update(value=''), 
-        gr.update(value=True), 
-        gr.update(value='832x1216'), 
-        gr.update(value=7), 
-        gr.update(value=28), 
-        gr.update(value=0), 
-        gr.update(value=True),
-        gr.update(visible=False),
-        ""
-    )
+    return gr.update(value=''), gr.update(value=''), gr.update(value=True), gr.update(value='832x1216'), gr.update(value=7), gr.update(value=28), gr.update(value=0), gr.update(value=True)
 
 with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/[email protected]") as demo:
     gr.HTML(
@@ -109,7 +85,6 @@ with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/[email protected]") as d
 
         with gr.Column():
             output_image = gr.Image(type="pil", label="Generated Image")
-            generation_details_output = gr.Markdown("", visible=False)
             gr.Markdown(
                 """
                 ### Recommended prompt formatting:
@@ -128,15 +103,15 @@ with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/[email protected]") as d
         inputs=[
             prompt_input, negative_prompt_input, use_defaults_input, resolution_input, guidance_scale_input, num_inference_steps_input, seed_input, randomize_seed_input
         ],
-        outputs=[output_image, seed_input, gr.update(value=seed), generation_details_output]
+        outputs=[output_image, seed_input]
     )
     
     reset_button.click(
         reset_inputs,
         inputs=[],
         outputs=[
-            prompt_input, negative_prompt_input, use_defaults_input, resolution_input, guidance_scale_input, num_inference_steps_input, seed_input, randomize_seed_input, generation_details_output, gr.update(value="")
+            prompt_input, negative_prompt_input, use_defaults_input, resolution_input, guidance_scale_input, num_inference_steps_input, seed_input, randomize_seed_input
         ]
     )
 
-demo.queue(max_size=20).launch(share=False)
+demo.queue(max_size=20).launch(share=False)