Update app.py

app.py

@@ -48,15 +48,17 @@ def generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_s
 
     torch.cuda.empty_cache()
 
-    return image, seed
+    metadata_text = f"{prompt}\nNegative prompt: {negative_prompt}\nSteps: {num_inference_steps}, Size: {width}x{height}, Seed: {seed}, CFG scale: {guidance_scale}"
+
+    return image, seed, metadata_text
 
 # 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 = generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress)
-    return image, seed, gr.update(value=seed)
+    image, seed, metadata_text = generate_image(prompt, negative_prompt, use_defaults, resolution, guidance_scale, num_inference_steps, seed, randomize_seed, progress)
+    return image, seed, gr.update(value=metadata_text)
 
 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)
+    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(value='')
 
 with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/miku@1.2.1") as demo:
     gr.HTML(
@@ -85,6 +87,7 @@ with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/miku@1.2.1") as d
 
         with gr.Column():
             output_image = gr.Image(type="pil", label="Generated Image")
+            metadata_textbox = gr.Textbox(lines=6, label="Metadata", interactive=False)
             gr.Markdown(
                 """
                 ### Recommended prompt formatting:
@@ -103,15 +106,15 @@ with gr.Blocks(title="UrangDiffusion 1.0 Demo", theme="NoCrypt/miku@1.2.1") 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]
+        outputs=[output_image, seed_input, metadata_textbox]
     )
     
     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
+            prompt_input, negative_prompt_input, use_defaults_input, resolution_input, guidance_scale_input, num_inference_steps_input, seed_input, randomize_seed_input, metadata_textbox
         ]
     )
 
-demo.queue(max_size=20).launch(share=False)
+demo.queue(max_size=20).launch(share=False)