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app.py

@@ -11,54 +11,41 @@ if torch.cuda.is_available():
     pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=torch.float16).to("cuda")
 else:
     pipe = StableDiffusion3Pipeline.from_pretrained(repo)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1344
-
-
-@spaces.GPU
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
-    
-    return image, seed
-
+max_seed = np.iinfo(np.int32).max
+max_image_size = 1344
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
     "An astronaut riding a green horse",
     "A delicious ceviche cheesecake slice",
 ]
-
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 580px;
 }
 """
 
+
+@spaces.GPU
+def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
+    if randomize_seed:
+        seed = random.randint(0, max_seed)
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
+        generator=torch.Generator().manual_seed(seed)
+    ).images[0]
+    return image, seed
+
+
 with gr.Blocks(css=css) as demo:
-    
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)
-        Learn more about the [Stable Diffusion 3 series](https://stability.ai/news/stable-diffusion-3). Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), [Stable Assistant](https://stability.ai/stable-assistant), or on Discord via [Stable Artisan](https://stability.ai/stable-artisan). Run locally with [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [diffusers](https://github.com/huggingface/diffusers)
-        """)
-        
+        gr.Markdown("# Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)")
         with gr.Row():
-            
             prompt = gr.Text(
                 label="Prompt",
                 show_label=False,
@@ -66,57 +53,45 @@ with gr.Blocks(css=css) as demo:
                 placeholder="Enter your prompt",
                 container=False,
             )
-            
             run_button = gr.Button("Run", scale=0)
-        
         result = gr.Image(label="Result", show_label=False)
-
         with gr.Accordion("Advanced Settings", open=False):
-            
             negative_prompt = gr.Text(
-                label="Negative prompt",
+                label="Negative Prompt",
                 max_lines=1,
                 placeholder="Enter a negative prompt",
             )
-            
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,
-                maximum=MAX_SEED,
+                maximum=max_seed,
                 step=1,
                 value=0,
             )
-            
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
             with gr.Row():
-                
                 width = gr.Slider(
                     label="Width",
                     minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
+                    maximum=max_image_size,
                     step=64,
                     value=1024,
                 )
-                
                 height = gr.Slider(
                     label="Height",
                     minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
+                    maximum=max_image_size,
                     step=64,
                     value=1024,
                 )
-            
             with gr.Row():
-                
                 guidance_scale = gr.Slider(
                     label="Guidance scale",
                     minimum=0.0,
                     maximum=10.0,
                     step=0.1,
-                    value=5.0,
+                    value=7.5,
                 )
-                
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
                     minimum=1,
@@ -124,16 +99,14 @@ with gr.Blocks(css=css) as demo:
                     step=1,
                     value=5,
                 )
-        
         gr.Examples(
-            examples = examples,
-            inputs = [prompt]
+            examples=examples,
+            inputs=[prompt]
         )
     gr.on(
         triggers=[run_button.click, prompt.submit, negative_prompt.submit],
-        fn = infer,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs = [result, seed]
+        fn=infer,
+        inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        outputs=[result, seed]
     )
-
-demo.launch()
+demo.launch()