Update app.py

app.py

@@ -201,208 +201,4 @@ with gr.Blocks(css=css) as demo:
         outputs=[front_result, back_result]
     )
 
-demo.queue().launch()
-import gradio as gr
-import numpy as np
-import random
-from diffusers import DiffusionPipeline
-import torch
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
-
-if torch.cuda.is_available():
-    torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipe.enable_xformers_memory_efficient_attention()
-    pipe = pipe.to(device)
-else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
-    pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-def infer(prompt_part1, color, dress_type, front_design, back_design, prompt_part5, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
-    front_prompt = f"front view of {prompt_part1} {color} colored plain {dress_type} with {front_design} design, {prompt_part5}"
-    back_prompt = f"back view of {prompt_part1} {color} colored plain {dress_type} with {back_design} design, {prompt_part5}"
-    
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    front_image = pipe(
-        prompt=front_prompt, 
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale, 
-        num_inference_steps=num_inference_steps, 
-        width=width, 
-        height=height,
-        generator=generator
-    ).images[0]
-    
-    back_image = pipe(
-        prompt=back_prompt, 
-        negative_prompt=negative_prompt,
-        guidance_scale=guidance_scale, 
-        num_inference_steps=num_inference_steps, 
-        width=width, 
-        height=height,
-        generator=generator
-    ).images[0]
-    
-    return front_image, back_image
-
-examples = [
-    ["red", "t-shirt", "yellow stripes", "polka dots"],
-    ["blue", "hoodie", "minimalist", "abstract art"],
-    ["red", "sweat shirt", "geometric design", "plain"],
-]
-
-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.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Text-to-Image Gradio Template
-        Currently running on {power_device}.
-        """)
-        
-        with gr.Row():
-            
-            prompt_part1 = gr.Textbox(
-                value="a single", 
-                label="Prompt Part 1",
-                show_label=False,
-                interactive=False,
-                container=False,
-                elem_id="prompt_part1",
-                visible=False,
-            )
-            
-            prompt_part2 = gr.Textbox(
-                label="color",
-                show_label=False,
-                max_lines=1,
-                placeholder="color (e.g., color category)",
-                container=False,
-            )
-            
-            prompt_part3 = gr.Textbox(
-                label="dress_type",
-                show_label=False,
-                max_lines=1,
-                placeholder="dress_type (e.g., t-shirt, sweatshirt, shirt, hoodie)",
-                container=False,
-            )
-            
-            prompt_part4_front = gr.Textbox(
-                label="front design",
-                show_label=False,
-                max_lines=1,
-                placeholder="front design",
-                container=False,
-            )
-
-            prompt_part4_back = gr.Textbox(
-                label="back design",
-                show_label=False,
-                max_lines=1,
-                placeholder="back design",
-                container=False,
-            )
-            
-            prompt_part5 = gr.Textbox(
-                value="hanging on the plain wall", 
-                label="Prompt Part 5",
-                show_label=False,
-                interactive=False,
-                container=False,
-                elem_id="prompt_part5",
-                visible=False,
-            )
-            
-            
-            run_button = gr.Button("Run", scale=0)
-        
-        front_result = gr.Image(label="Front View Result", show_label=False)
-        back_result = gr.Image(label="Back View Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            negative_prompt = gr.Textbox(
-                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=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=1,
-                    maximum=12,
-                    step=1,
-                    value=2,
-                )
-        
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt_part2, prompt_part3, prompt_part4_front, prompt_part4_back]
-        )
-
-    run_button.click(
-        fn=infer,
-        inputs=[prompt_part1, prompt_part2, prompt_part3, prompt_part4_front, prompt_part4_back, prompt_part5, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs=[front_result, back_result]
-    )
-
-demo.queue().launch()
+demo.queue().launch()