update

app.py

@@ -38,104 +38,97 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     return image
 
 examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
 
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
+]
 
 if torch.cuda.is_available():
     power_device = "GPU"
 else:
     power_device = "CPU"
 
-with gr.Blocks(css=css) as demo:
+with gr.Blocks() as demo:
     
-    with gr.Column(elem_id="col-container"):
+    with gr.Row():
         gr.Markdown(f"""
         # Text-to-Image Gradio Template
         Currently running on {power_device}.
         """)
         
-        with gr.Row():
-            
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                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",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
+    with gr.Row():
+        with gr.Column(elem_id="col-container"):
             with gr.Row():
-                
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
+                ip_adapter_image = gr.Image(label="IP-Adapter Image", type="pil")
+                ip_adapter_scale = gr.Slider(
+                    label="Image influence scale",
+                    info="Use 1 for creating variations",
+                    minimum=0.0,
+                    maximum=1.0,
+                    step=0.05,
+                    value=0.5,
                 )
-            
             with gr.Row():
-                
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,
+                prompt = gr.Text(
+                    label="Prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
                 )
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=12,
+                run_button = gr.Button("Run", scale=0)
+            with gr.Accordion("Advanced Settings", open=False):
+                negative_prompt = gr.Text(
+                    label="Negative prompt",
+                    max_lines=1,
+                    placeholder="Enter a negative prompt",
+                    visible=True,
+                )
+                seed = gr.Slider(
+                    label="Seed",
+                    minimum=0,
+                    maximum=MAX_SEED,
                     step=1,
-                    value=2,
+                    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,
+                        step=32,
+                        value=512,
+                    )
+                    height = gr.Slider(
+                        label="Height",
+                        minimum=256,
+                        maximum=MAX_IMAGE_SIZE,
+                        step=32,
+                        value=512,
+                    )
+                with gr.Row():
+                    guidance_scale = gr.Slider(
+                        label="Guidance scale",
+                        minimum=0.0,
+                        maximum=10.0,
+                        step=0.1,
+                        value=0.0,
+                    )
+                    num_inference_steps = gr.Slider(
+                        label="Number of inference steps",
+                        minimum=10,
+                        maximum=50,
+                        step=1,
+                        value=25,
+                    )
+            
+        with gr.Column(elem_id="col-container"):
+            result = gr.Image(label="Result", show_label=False)
+    
+    with gr.Row():
         gr.Examples(
-            examples = examples,
-            inputs = [prompt]
-        )
+                examples = examples,
+                inputs = [prompt]
+            )
 
     run_button.click(
         fn = infer,