Update app.py

app.py

@@ -1,143 +1,132 @@
 import gradio as gr
 import numpy as np
 import random
-import spaces
 import torch
-from diffusers import DiffusionPipeline
+from diffusers import StableDiffusionPipeline
 from PIL import Image
-import io
-from PIL import ImageEnhance
+import os
+
+MAX_SEED = 10000
+MAX_IMAGE_SIZE = 1024
 
 def get_edge_color(image):
-    """
-    Get a random color from the edge of the image
-    """
-    # Convert to numpy array
+    """Get a random color from the edge of the image"""
     img_array = np.array(image)
-    
-    # Get pixels from all edges
     top_edge = img_array[0, :, :]
     bottom_edge = img_array[-1, :, :]
     left_edge = img_array[:, 0, :]
     right_edge = img_array[:, -1, :]
-    
-    # Combine all edge pixels
     edge_pixels = np.concatenate([top_edge, bottom_edge, left_edge, right_edge])
-    
-    # Pick a random edge pixel
     random_edge_color = tuple(edge_pixels[random.randint(0, len(edge_pixels)-1)])
-    
     return random_edge_color
 
 def color_match_tshirt(tshirt_image, target_color, threshold=30):
-    """
-    Change white/near-white areas of the t-shirt to the target color
-    """
-    # Convert to numpy array
+    """Change white/near-white areas of the t-shirt to the target color"""
     img_array = np.array(tshirt_image)
-    
-    # Create a mask for near-white pixels
     white_mask = np.all(np.abs(img_array - [255, 255, 255]) < threshold, axis=2)
-    
-    # Apply the new color to masked areas
     img_array[white_mask] = target_color
-    
     return Image.fromarray(img_array)
 
-def add_logo_watermark(image, logo_path='logo.png', size_percentage=0.2):
-    """
-    Add a logo watermark to the bottom right corner
-    """
-    # Open and resize logo
-    logo = Image.open(logo_path)
-    
-    # Calculate new logo size (20% of main image width)
-    new_width = int(image.size[0] * size_percentage)
-    new_height = int(new_width * logo.size[1] / logo.size[0])
-    logo = logo.resize((new_width, new_height), Image.Resampling.LANCZOS)
-    
-    # If logo has transparency, use it as mask
-    if logo.mode == 'RGBA':
-        mask = logo.split()[3]
-    else:
-        mask = None
-    
-    # Calculate position (bottom right corner with padding)
-    position = (image.size[0] - logo.size[0] - 10, 
-               image.size[1] - logo.size[1] - 10)
-    
-    # Create a copy of the image
-    result = image.copy()
-    result.paste(logo, position, mask)
-    
-    return result
+def add_watermark(image, logo_path, position='bottom-right', size_percentage=10):
+    """Add a watermark to an image"""
+    try:
+        if not os.path.exists(logo_path):
+            return image
+            
+        logo = Image.open(logo_path).convert('RGBA')
+        main_width, main_height = image.size
+        logo_width = int(main_width * size_percentage / 100)
+        logo_height = int(logo.size[1] * (logo_width / logo.size[0]))
+        logo = logo.resize((logo_width, logo_height), Image.Resampling.LANCZOS)
+        
+        if image.mode != 'RGBA':
+            image = image.convert('RGBA')
+        
+        watermarked = Image.new('RGBA', image.size, (0, 0, 0, 0))
+        watermarked.paste(image, (0, 0))
+        
+        if position == 'bottom-right':
+            pos = (main_width - logo_width - 10, main_height - logo_height - 10)
+        elif position == 'bottom-left':
+            pos = (10, main_height - logo_height - 10)
+        elif position == 'top-right':
+            pos = (main_width - logo_width - 10, 10)
+        else:  # top-left
+            pos = (10, 10)
+        
+        watermarked.paste(logo, pos, logo)
+        return watermarked.convert('RGB')
+    except Exception as e:
+        print(f"Failed to add watermark: {str(e)}")
+        return image
 
-def create_tshirt_preview(design_image, tshirt_color="white"):
-    """
-    Overlay the design onto the t-shirt template with color matching
-    """
-    # Load the template t-shirt image
-    tshirt = Image.open('image.jpeg')
-    tshirt_width, tshirt_height = tshirt.size
-    
-    # Get a random edge color from the design
-    edge_color = get_edge_color(design_image)
-    
-    # Color match the t-shirt
-    tshirt = color_match_tshirt(tshirt, edge_color)
-    
-    # Resize design (35% of shirt width)
-    design_width = int(tshirt_width * 0.35)
-    design_height = int(design_width * design_image.size[1] / design_image.size[0])
-    design_image = design_image.resize((design_width, design_height), Image.Resampling.LANCZOS)
-    
-    # Calculate position to center design
-    x = (tshirt_width - design_width) // 2
-    y = int(tshirt_height * 0.2)
-    
-    # Create mask if design has transparency
-    if design_image.mode == 'RGBA':
-        mask = design_image.split()[3]
-    else:
-        mask = None
-    
-    # Paste design onto shirt
-    tshirt.paste(design_image, (x, y), mask)
-    
-    # Add logo watermark
-    tshirt = add_logo_watermark(tshirt)
-    
-    return tshirt
+def create_tshirt_preview(design_image, tshirt_template_path, tshirt_color="white"):
+    """Create a preview of the design on a t-shirt"""
+    try:
+        tshirt = Image.open(tshirt_template_path)
+        tshirt_width, tshirt_height = tshirt.size
+        
+        edge_color = get_edge_color(design_image)
+        tshirt = color_match_tshirt(tshirt, edge_color)
+        
+        design_width = int(tshirt_width * 0.35)
+        design_height = int(design_width * design_image.size[1] / design_image.size[0])
+        design_image = design_image.resize((design_width, design_height), Image.Resampling.LANCZOS)
+        
+        x = (tshirt_width - design_width) // 2
+        y = int(tshirt_height * 0.2)
+        
+        if design_image.mode == 'RGBA':
+            mask = design_image.split()[3]
+        else:
+            mask = None
+        
+        tshirt.paste(design_image, (x, y), mask)
+        return tshirt
+    except Exception as e:
+        print(f"Failed to create t-shirt preview: {str(e)}")
+        return design_image
 
-@spaces.GPU()
-def infer(prompt, style=None, tshirt_color="white", seed=42, randomize_seed=False, 
-          width=1024, height=1024, num_inference_steps=4, 
-          progress=gr.Progress(track_tqdm=True)):
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    
-    enhanced_prompt = enhance_prompt_for_tshirt(prompt, style)
+def enhance_prompt(prompt, style):
+    """Enhance the prompt based on selected style"""
+    if not style:
+        return prompt
+        
+    style_prompts = {
+        "minimal": "minimalist design, clean lines, simple shapes",
+        "vintage": "vintage style, retro, distressed texture",
+        "artistic": "artistic, creative, hand-drawn style",
+        "geometric": "geometric patterns, abstract shapes",
+        "typography": "modern typography, creative lettering",
+        "realistic": "photorealistic, detailed illustration"
+    }
+    
+    return f"{prompt}, {style_prompts.get(style, '')}"
+
+def initialize_pipeline():
+    """Initialize the Stable Diffusion pipeline"""
+    model_id = "stabilityai/stable-diffusion-2-1"
+    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
+    if torch.cuda.is_available():
+        pipe = pipe.to("cuda")
+    return pipe
+
+def generate_design(prompt, style, seed, width, height, num_inference_steps, pipe):
+    """Generate the design using Stable Diffusion"""
+    enhanced_prompt = enhance_prompt(prompt, style)
     generator = torch.Generator().manual_seed(seed)
     
-    # Generate the design
-    design_image = pipe(
+    image = pipe(
         prompt=enhanced_prompt,
         width=width,
         height=height,
         num_inference_steps=num_inference_steps,
         generator=generator,
-        guidance_scale=0.0
     ).images[0]
     
-    # Add logo to design
-    design_image = add_logo_watermark(design_image)
-    
-    # Create t-shirt preview
-    tshirt_preview = create_tshirt_preview(design_image, tshirt_color)
-    
-    return design_image, tshirt_preview, seed
+    return image
 
-# Available t-shirt colors
+# Constants
 TSHIRT_COLORS = {
     "White": "#FFFFFF",
     "Black": "#000000",
@@ -145,14 +134,7 @@ TSHIRT_COLORS = {
     "Gray": "#808080"
 }
 
-examples = [
-    ["Cool geometric mountain landscape", "minimal", "White"],
-    ["Vintage motorcycle with flames", "vintage", "Black"],
-    ["flamingo in scenic forset", "realistic", "White"],
-    ["Adventure Starts typography", "typography", "White"]
-]
-
-styles = [
+STYLES = [
     "minimal",
     "vintage",
     "artistic",
@@ -161,153 +143,67 @@ styles = [
     "realistic"
 ]
 
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 1200px !important;
-    padding: 20px;
-}
-.main-title {
-    text-align: center;
-    color: #2d3748;
-    margin-bottom: 1rem;
-    font-family: 'Poppins', sans-serif;
-}
-.subtitle {
-    text-align: center;
-    color: #4a5568;
-    margin-bottom: 2rem;
-    font-family: 'Inter', sans-serif;
-    font-size: 0.95rem;
-    line-height: 1.5;
-}
-.design-input {
-    border: 2px solid #e2e8f0;
-    border-radius: 10px;
-    padding: 12px !important;
-    margin-bottom: 1rem !important;
-    font-size: 1rem;
-    transition: all 0.3s ease;
-}
-.results-row {
-    display: grid;
-    grid-template-columns: 1fr 1fr;
-    gap: 20px;
-    margin-top: 20px;
-}
-"""
+EXAMPLES = [
+    ["Cool geometric mountain landscape", "minimal", "White"],
+    ["Vintage motorcycle with flames", "vintage", "Black"],
+    ["Flamingo in scenic forest", "realistic", "White"],
+    ["Adventure Starts typography", "typography", "White"]
+]
 
-with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(
-            """
-            # 👕Deradh's T-Shirt Design Generator
-            """,
-            elem_classes=["main-title"]
-        )
-        
-        gr.Markdown(
-            """
-            Create unique t-shirt designs using Deradh's AI. 
-            Describe your design idea and select a style to generate professional-quality artwork 
-            perfect for custom t-shirts.
-            """,
-            elem_classes=["subtitle"]
-        )
-        
-        with gr.Row():
-            with gr.Column(scale=2):
-                prompt = gr.Text(
-                    label="Design Description",
-                    show_label=False,
-                    max_lines=1,
-                    placeholder="Describe your t-shirt design idea",
-                    container=False,
-                    elem_classes=["design-input"]
-                )
-            with gr.Column(scale=1):
-                style = gr.Dropdown(
-                    choices=[""] + styles,
-                    value="",
-                    label="Style",
-                    container=False
-                )
-            with gr.Column(scale=1):
-                tshirt_color = gr.Dropdown(
-                    choices=list(TSHIRT_COLORS.keys()),
-                    value="White",
-                    label="T-Shirt Color",
-                    container=False
-                )
-            run_button = gr.Button(
-                "✨ Generate",
-                scale=0,
-                elem_classes=["generate-button"]
-            )
-        
-        with gr.Row(elem_classes=["results-row"]):
-            result = gr.Image(
-                label="Generated Design",
-                show_label=True,
-                elem_classes=["result-image"]
+# Gradio Interface
+def create_interface():
+    pipe = initialize_pipeline()
+    
+    def infer(prompt, style, tshirt_color, seed, randomize_seed, width, height, num_inference_steps):
+        if randomize_seed:
+            seed = random.randint(0, MAX_SEED)
+            
+        try:
+            design_image = generate_design(prompt, style, seed, width, height, num_inference_steps, pipe)
+            tshirt_preview = create_tshirt_preview(design_image, "tshirt_template.png", tshirt_color)
+            return design_image, tshirt_preview, seed
+        except Exception as e:
+            print(f"Error during inference: {str(e)}")
+            return None, None, seed
+
+    with gr.Blocks(theme=gr.themes.Soft()) as demo:
+        with gr.Column():
+            gr.Markdown("# 👕 T-Shirt Design Generator")
+            
+            with gr.Row():
+                prompt = gr.Textbox(label="Design Description", placeholder="Describe your t-shirt design idea")
+                style = gr.Dropdown(choices=[""] + STYLES, value="", label="Style")
+                tshirt_color = gr.Dropdown(choices=list(TSHIRT_COLORS.keys()), value="White", label="T-Shirt Color")
+            
+            run_button = gr.Button("✨ Generate")
+            
+            with gr.Row():
+                result = gr.Image(label="Generated Design")
+                preview = gr.Image(label="T-Shirt Preview")
+            
+            with gr.Accordion("Advanced Settings", open=False):
+                seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=0)
+                randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
+                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)
+                num_inference_steps = gr.Slider(label="Steps", minimum=1, maximum=50, step=1, value=25)
+            
+            gr.Examples(
+                examples=EXAMPLES,
+                inputs=[prompt, style, tshirt_color],
+                outputs=[result, preview, seed],
+                fn=lambda p, s, c: infer(p, s, c, 0, True, 512, 512, 25),
+                cache_examples=True
             )
-            preview = gr.Image(
-                label="T-Shirt Preview",
-                show_label=True,
-                elem_classes=["preview-image"]
+            
+            run_button.click(
+                fn=infer,
+                inputs=[prompt, style, tshirt_color, seed, randomize_seed, width, height, num_inference_steps],
+                outputs=[result, preview, seed]
             )
-        
-        with gr.Accordion("🔧 Advanced Settings", open=False):
-            with gr.Group():
-                seed = gr.Slider(
-                    label="Design Seed",
-                    minimum=0,
-                    maximum=MAX_SEED,
-                    step=1,
-                    value=0,
-                )
-                randomize_seed = gr.Checkbox(
-                    label="Randomize Design",
-                    value=True
-                )
-                
-                with gr.Row():
-                    width = gr.Slider(
-                        label="Width",
-                        minimum=256,
-                        maximum=MAX_IMAGE_SIZE,
-                        step=32,
-                        value=1024,
-                    )
-                    height = gr.Slider(
-                        label="Height",
-                        minimum=256,
-                        maximum=MAX_IMAGE_SIZE,
-                        step=32,
-                        value=1024,
-                    )
-                
-                num_inference_steps = gr.Slider(
-                    label="Generation Quality (Steps)",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=4,
-                )
-        
-        gr.Examples(
-            examples=examples,
-            fn=infer,
-            inputs=[prompt, style, tshirt_color],
-            outputs=[result, preview, seed],
-            cache_examples=True
-        )
-        
-        gr.on(
-            triggers=[run_button.click, prompt.submit],
-            fn=infer,
-            inputs=[prompt, style, tshirt_color, seed, randomize_seed, width, height, num_inference_steps],
-            outputs=[result, preview, seed]
-        )
+    
+    return demo
 
-demo.launch()
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch()