change layout

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import numpy as np
 import random
 
-import spaces #[uncomment to use ZeroGPU]
+import spaces  # [uncomment to use ZeroGPU]
 from diffusers import DiffusionPipeline
 import torch
 
@@ -21,34 +21,14 @@ MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1024
 
 
-@spaces.GPU #[uncomment to use ZeroGPU]
-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
+@spaces.GPU  # [uncomment to use ZeroGPU]
+def generate_images(prompt, seed, steps, pipe, pruned_pipe):
+    # Run the model and return images directly
+    g_cpu = torch.Generator("cuda").manual_seed(seed)
+    original_image = pipe(prompt=prompt, generator=g_cpu, num_inference_steps=steps).images[0]
+    g_cpu = torch.Generator("cuda").manual_seed(seed)
+    ecodiff_image = pruned_pipe(prompt=prompt, generator=g_cpu, num_inference_steps=steps).images[0]
+    return original_image, ecodiff_image
 
 
 examples = [
@@ -63,91 +43,58 @@ css = """
     max-width: 640px;
 }
 """
+header = """
+# 🌱 Text-to-Image Generation with EcoDiff Pruned SD-XL (20% Pruning Ratio)
+# Under Construction!!!
+<div style="text-align: center; display: flex; justify-content: left; gap: 5px;">
+<a href="https://arxiv.org/abs/2412.02852"><img src="https://img.shields.io/badge/ariXv-Paper-A42C25.svg" alt="arXiv"></a>
+<a href="https://huggingface.co/zhangyang-0123/EcoDiffPrunedModels"><img src="https://img.shields.io/badge/🤗-Model-ffbd45.svg" alt="HuggingFace"></a>
+<a href="https://github.com/YaNgZhAnG-V5/EcoDiff"><img src="https://img.shields.io/badge/GitHub-Code-blue.svg?logo=github&" alt="GitHub"></a>
+</div>
+"""
 
 with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        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, variant="primary")
-
-        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():
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
-                )
-
-        gr.Examples(examples=examples, inputs=[prompt])
+    gr.Markdown(header)
+    with gr.Row():
+        prompt = gr.Textbox(
+            label="Prompt",
+            value="A clock tower floating in a sea of clouds",
+            scale=3,
+        )
+        seed = gr.Number(label="Seed", value=44, precision=0, scale=1)
+        steps = gr.Slider(
+            label="Number of Steps",
+            minimum=1,
+            maximum=100,
+            value=50,
+            step=1,
+            scale=1,
+        )
+        generate_btn = gr.Button("Generate Images")
+    gr.Examples(
+        examples=[
+            "A clock tower floating in a sea of clouds",
+            "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
+            "An astronaut riding a green horse",
+            "A delicious ceviche cheesecake slice",
+            "A sprawling cyberpunk metropolis at night, with towering skyscrapers emitting neon lights of every color, holographic billboards advertising alien languages",
+        ],
+        inputs=[prompt],
+    )
+    with gr.Row():
+        original_output = gr.Image(label="Original Output")
+        ecodiff_output = gr.Image(label="EcoDiff Output")
     gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
+        triggers=[generate_btn.click, prompt.submit],
+        fn=generate_images,
         inputs=[
             prompt,
-            negative_prompt,
             seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
+            steps,
+            pipe,
+            pipe,
         ],
-        outputs=[result, seed],
+        outputs=[original_output, ecodiff_output],
     )
 
 if __name__ == "__main__":