init

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,8 +1,8 @@
 ---
 title: Snapwear Texture Transfer
-emoji: 😻
-colorFrom: green
-colorTo: green
+emoji: 🎨✨
+colorFrom: red
+colorTo: yellow
 sdk: gradio
 sdk_version: 5.31.0
 app_file: app.py

app.py

@@ -0,0 +1,532 @@
+import os
+import io
+import base64
+import time
+import gradio as gr
+from PIL import Image
+import logging
+import numpy as np
+from gradio_client import Client
+import json
+
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# ─────────  Backend connection ─────────
+HF_TOKEN = os.getenv("HF_TOKEN")
+if not HF_TOKEN:
+    raise ValueError("HF_TOKEN environment variable is required")
+
+# Try to connect to backend
+try:
+    client = Client("SnapwearAI/Pattern-Transfer-Backend", hf_token=HF_TOKEN)
+    logger.info("✅ Backend client established")
+    backend_connected = True
+except Exception as e:
+    logger.warning(f"⚠️ Backend connection failed: {e}")
+    client = None
+    backend_connected = False
+
+# ─────────  Styling ─────────
+css = """
+body, .gradio-container {
+    font-family: 'Inter', 'SF Pro Display', -apple-system, BlinkMacSystemFont, sans-serif;
+}
+#col-left, #col-mid, #col-right {
+    margin: 0 auto;
+    max-width: 400px;
+}
+#col-showcase {
+    margin: 0 auto;
+    max-width: 1200px;
+}
+#button {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: #ffffff;
+    font-weight: 600;
+    font-size: 16px;
+    border: none;
+    border-radius: 12px;
+    padding: 12px 24px;
+    transition: all 0.3s ease;
+}
+#button:hover {
+    transform: translateY(-2px);
+    box-shadow: 0 8px 25px rgba(102,126,234,0.3);
+}
+#button:disabled {
+    background: #ccc !important;
+    cursor: not-allowed;
+    transform: none;
+    box-shadow: none;
+}
+.hero-section {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 40px 20px;
+    border-radius: 20px;
+    margin: 20px 0;
+    text-align: center;
+}
+.feature-box {
+    background: #f8fafc;
+    border: 1px solid #e2e8f0;
+    padding: 20px;
+    border-radius: 12px;
+    margin: 10px 0;
+    border-left: 4px solid #667eea;
+}
+.showcase-section {
+    background: #ffffff;
+    border: 1px solid #e2e8f0;
+    padding: 30px;
+    border-radius: 16px;
+    box-shadow: 0 4px 20px rgba(0,0,0,0.1);
+    margin: 20px 0;
+}
+.step-header {
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    color: white;
+    padding: 15px;
+    border-radius: 12px;
+    text-align: center;
+    font-weight: 600;
+    margin: 10px 0;
+}
+.social-links {
+    text-align: center;
+    margin: 20px 0;
+}
+.social-links a {
+    margin: 0 10px;
+    padding: 8px 16px;
+    background: #667eea;
+    color: white;
+    text-decoration: none;
+    border-radius: 8px;
+    transition: all 0.3s ease;
+}
+.social-links a:hover {
+    background: #764ba2;
+    transform: translateY(-2px);
+}
+.status-banner {
+    padding: 15px;
+    border-radius: 12px;
+    margin: 10px 0;
+    text-align: center;
+    font-weight: 600;
+}
+.status-ready {
+    background: #d4edda;
+    border: 1px solid #c3e6cb;
+    color: #155724;
+}
+.status-starting {
+    background: #fff3cd;
+    border: 1px solid #ffeaa7;
+    color: #856404;
+}
+.status-error {
+    background: #f8d7da;
+    border: 1px solid #f5c6cb;
+    color: #721c24;
+}
+"""
+
+def image_to_base64(image):
+    """Convert PIL Image to base64 string."""
+    if image is None:
+        return ""
+    
+    if hasattr(image, 'mode') and image.mode != 'RGB':
+        image = image.convert('RGB')
+    
+    buffer = io.BytesIO()
+    image.save(buffer, format="PNG")
+    buffer.seek(0)
+    return base64.b64encode(buffer.getvalue()).decode('utf-8')
+
+def base64_to_image(b64_string):
+    """Convert base64 string to PIL Image."""
+    if not b64_string:
+        return None
+    
+    try:
+        image_data = base64.b64decode(b64_string)
+        return Image.open(io.BytesIO(image_data))
+    except Exception as e:
+        logger.error(f"Failed to decode base64 image: {e}")
+        return None
+
+def try_connect_backend():
+    """Try to connect to backend and return status"""
+    global client, backend_connected
+    
+    try:
+        test_client = Client("SnapwearAI/Pattern-Transfer-Backend", hf_token=HF_TOKEN)
+        client = test_client
+        backend_connected = True
+        return "🟢 Model is ready!", True
+    except Exception as e:
+        client = None
+        backend_connected = False
+        error_str = str(e).lower()
+        if "timeout" in error_str or "read operation timed out" in error_str:
+            return "🟡 Model is starting up (this takes 5-6 minutes on first load). Please wait and try again.", False
+        else:
+            return f"🔴 Backend error: {str(e)}", False
+
+def call_backend_with_retry(print_image, product_image, max_retries=3):
+    """Call the backend with proper error handling."""
+    global client, backend_connected
+    
+    # Validate inputs
+    if not print_image:
+        return None, "❌ Please upload a print/pattern image"
+    
+    if not product_image:
+        return None, "❌ Please upload a product image"
+    
+    # Check if we have a client
+    if not client or not backend_connected:
+        # Try to reconnect
+        status_msg, is_ready = try_connect_backend()
+        if not is_ready:
+            return None, status_msg
+    
+    # Use fixed default values
+    guidance_scale = 50.0
+    num_steps = 50
+    
+    for attempt in range(max_retries):
+        try:
+            logger.info(f"Calling backend (attempt {attempt + 1}/{max_retries})")
+            
+            # Convert images to base64
+            print_b64 = image_to_base64(print_image)
+            product_b64 = image_to_base64(product_image)
+            
+            logger.info("Images converted to base64")
+            
+            # Make the backend call
+            start_time = time.time()
+            result = client.predict(
+                print_b64,
+                product_b64,
+                guidance_scale,
+                num_steps,
+                api_name="/predict"
+            )
+            
+            processing_time = time.time() - start_time
+            logger.info(f"Backend call completed in {processing_time:.2f}s")
+            
+            # Process the result
+            if result and len(result) >= 2:
+                result_b64, status = result[0], result[1]
+                
+                if result_b64:
+                    result_image = base64_to_image(result_b64)
+                    if result_image:
+                        logger.info("Successfully received and decoded result image")
+                        return result_image, status
+                    else:
+                        return None, "❌ Failed to decode result image"
+                else:
+                    return None, status or "❌ No image returned"
+            else:
+                return None, "❌ Invalid response from backend"
+                
+        except Exception as e:
+            error_str = str(e).lower()
+            if "timeout" in error_str:
+                # Backend might be starting up again
+                backend_connected = False
+                client = None
+                return None, "🟡 Model timed out. It may be starting up again. Please wait 5-6 minutes and try the 'Check Status' button."
+            
+            logger.error(f"Backend call attempt {attempt + 1} failed: {e}")
+            if attempt == max_retries - 1:
+                return None, f"❌ Backend error: {str(e)}"
+            time.sleep(2)  # Wait before retry
+    
+    return None, "❌ All attempts failed"
+
+# ─────────  Main UI ─────────
+with gr.Blocks(css=css, title="Pattern & Color Transfer Studio") as demo:
+    
+    # ──────── Hero Section ────────
+    gr.HTML("""
+        <div class="hero-section">
+            <h1 style="font-size:48px;margin:0;background:linear-gradient(45deg,#fff,#f0f8ff);-webkit-background-clip:text;-webkit-text-fill-color:transparent;">
+                🎨 Snapwear Texture Transfer Studio
+            </h1>
+            <h2 style="font-size:24px;margin:10px 0;opacity:0.9;">
+                Transfer Any Pattern onto Any Product Instantly
+            </h2>
+            <p style="font-size:18px;margin:15px 0;opacity:0.8;">
+                • Instant results • Perfect for designers, brands & creators
+            </p>
+            <div class="social-links">
+                <a href="https://snapwear.io" target="_blank">🌐 Official Website</a>
+                <a href="https://www.instagram.com/snapwearai/" target="_blank">📸 Instagram</a>
+                <a href="https://huggingface.co/spaces/SnapwearAI/Snapwear-Virtual-Try-On" target="_blank">👗 Try Virtual Try-On</a>
+            </div>
+        </div>
+    """)
+
+    # ──────── Status Check Section ────────
+    with gr.Row():
+        with gr.Column():
+            # Initial status message
+            if backend_connected:
+                initial_status = '<div class="status-banner status-ready">🟢 Model is ready! You can generate pattern transfers.</div>'
+            else:
+                initial_status = '<div class="status-banner status-starting">🟡 Model may be starting up. Click "Check Status" to verify.</div>'
+            
+            status_display = gr.HTML(value=initial_status)
+            
+            # Status check button
+            check_status_btn = gr.Button("🔄 Check Status", size="sm")
+    
+    # ──────── Info Box ────────
+    gr.HTML("""
+        <div style="background:#e8f4fd;border:1px solid #bee5eb;border-radius:12px;padding:20px;margin:20px 0;">
+            <h3 style="color:#0c5460;margin:0 0 10px 0;">ℹ️ First Time Here?</h3>
+            <p style="color:#0c5460;margin:0;">
+                Our AI model takes 5-6 minutes to start up on first visit after being idle. 
+                Use the "Check Status" button above to see when the system is ready. 
+                Once ready, pattern transfers complete in 30-60 seconds!
+            </p>
+        </div>
+    """)
+
+    # ──────── Key Features ────────
+    gr.HTML("""
+        <div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(250px,1fr));gap:20px;margin:30px 0;">
+            <div class="feature-box">
+                <h3>🚀 Instant Transfer</h3>
+                <p>Apply any pattern to any product in 30-60 seconds with professional results</p>
+            </div>
+            <div class="feature-box">
+                <h3>🎯 Perfect Mapping</h3>
+                <p>Preserve product shape, lighting, and texture for realistic results</p>
+            </div>
+            <div class="feature-box">
+                <h3>🎨 Endless Possibilities</h3>
+                <p>Transfer prints, patterns, textures, and colors across any product type</p>
+            </div>
+        </div>
+    """)
+
+    # ──────── Step Headers ────────
+    with gr.Row():
+        with gr.Column(elem_id="col-left"):
+            gr.HTML('<div class="step-header">Step 1: Upload Pattern/Print 🎨</div>')
+        with gr.Column(elem_id="col-mid"):
+            gr.HTML('<div class="step-header">Step 2: Upload Product 📦</div>')
+        with gr.Column(elem_id="col-right"):
+            gr.HTML('<div class="step-header">Step 3: Generate Magic ✨</div>')
+
+    # ──────── Main Interface ────────
+    with gr.Row():
+        # ① Pattern/Print Upload
+        with gr.Column(elem_id="col-left"):
+            print_image = gr.Image(
+                label="Pattern/Print Image",
+                type="pil",
+                height=400,
+            )
+            gr.HTML('<p style="text-align:center;color:#666;font-size:14px;">Upload any color, print, or design you want to transfer</p>')
+            
+            # Print examples
+            if os.path.exists("Assets/print"):
+                print_examples = [os.path.join("Assets/print", f) for f in os.listdir("Assets/print")][:10]
+                if print_examples:
+                    gr.Examples(
+                        label="✨ Example Patterns",
+                        inputs=print_image,
+                        examples_per_page=10,
+                        examples=print_examples,
+                    )
+
+        # ② Product Upload
+        with gr.Column(elem_id="col-mid"):
+            product_image = gr.Image(
+                label="Product Image",
+                type="pil", 
+                height=400,
+            )
+            gr.HTML('<p style="text-align:center;color:#666;font-size:14px;">Upload the product you want to apply the pattern to</p>')
+            
+            # Product examples
+            if os.path.exists("Assets/product"):
+                product_examples = [os.path.join("Assets/product", f) for f in os.listdir("Assets/product")][:12]
+                if product_examples:
+                    gr.Examples(
+                        label="📦 Example Products",
+                        inputs=product_image,
+                        examples_per_page=12,
+                        examples=product_examples,
+                    )
+
+        # ③ Result + Controls
+        with gr.Column(elem_id="col-right"):
+            result_img = gr.Image(
+                label="✨ Transformed Result",
+                show_share_button=True,
+                height=400
+            )
+
+            # Status display
+            status_text = gr.Text(
+                label="Generation Status",
+                interactive=False,
+                placeholder="Upload images and click generate..."
+            )
+
+            # Generate button
+            generate_btn = gr.Button(
+                "🚀 Transform Pattern",
+                elem_id="button",
+                size="lg",
+                variant="primary"
+            )
+
+    # ──────── Showcase Examples ────────
+    gr.HTML("""
+        <div class="showcase-section">
+            <h2 style="text-align:center;color:#333;margin-bottom:30px;">
+                🌟 Showcase: Pattern & Color Transfer Examples
+            </h2>
+        </div>
+    """)
+
+    # Pattern Transfer Showcase
+    with gr.Row():
+        gr.HTML('<h3 style="text-align:center;color:#667eea;margin:20px 0;">🎨 Pattern Transfer Showcase</h3>')
+    
+    try:
+        if os.path.exists("Assets/examples"):
+            showcase_examples = [
+                [os.path.join("Assets/examples", "1_product.jpg"), os.path.join("Assets/examples", "1_print.jpg"), os.path.join("Assets/examples", "1_result.jpg")],
+                [os.path.join("Assets/examples", "2_product.jpg"), os.path.join("Assets/examples", "2_print.jpg"), os.path.join("Assets/examples", "2_result.jpg")],
+                [os.path.join("Assets/examples", "3_product.jpg"), os.path.join("Assets/examples", "3_print.jpg"), os.path.join("Assets/examples", "3_result.jpg")],
+                [os.path.join("Assets/examples", "4_product.jpg"), os.path.join("Assets/examples", "4_print.jpg"), os.path.join("Assets/examples", "4_result.jpg")],
+            ]
+            pattern_showcase = gr.Examples(
+                examples=showcase_examples,
+                inputs=[product_image, print_image, result_img],
+                label="Pattern Transfer Examples - Click any example to try it yourself!",
+                examples_per_page=4,
+            )
+    except:
+        gr.HTML("<p style='text-align:center;color:#666;'>Pattern transfer examples will appear here once example files are added to Assets/examples/</p>")
+
+    # Color Transfer Showcase  
+    with gr.Row():
+        gr.HTML('<h3 style="text-align:center;color:#764ba2;margin:20px 0;">🌈 Color Transfer Showcase</h3>')
+    
+    try:
+        if os.path.exists("Assets/examples/color"):
+            color_examples = [
+                [os.path.join("Assets/examples/color", "1_product.jpg"), os.path.join("Assets/examples/color", "1_print.jpg"), os.path.join("Assets/examples/color", "1_result.jpg")],
+                [os.path.join("Assets/examples/color", "2_product.jpg"), os.path.join("Assets/examples/color", "2_print.jpg"), os.path.join("Assets/examples/color", "2_result.jpg")],
+                [os.path.join("Assets/examples/color", "3_product.jpg"), os.path.join("Assets/examples/color", "3_print.jpg"), os.path.join("Assets/examples/color", "3_result.jpg")],
+            ]
+            color_showcase = gr.Examples(
+                examples=color_examples,
+                inputs=[product_image, print_image, result_img],
+                label="Color Transfer Examples - Perfect for recoloring products!",
+                examples_per_page=3,
+            )
+    except:
+        gr.HTML("<p style='text-align:center;color:#666;'>Color transfer examples will appear here once example files are added to Assets/examples/color/</p>")
+
+    # ──────── Use Cases ────────
+    gr.HTML("""
+        <div style="background:#f8fafc;border:1px solid #e2e8f0;padding:30px;border-radius:16px;margin:30px 0;">
+            <h2 style="text-align:center;color:#333;margin-bottom:25px;">🎯 Perfect For</h2>
+            <div style="display:grid;grid-template-columns:repeat(auto-fit,minmax(200px,1fr));gap:20px;">
+                <div style="text-align:center;padding:15px;">
+                    <h3 style="color:#667eea;">👗 Fashion Designers</h3>
+                    <p style="color:#666;">Visualize patterns on garments before production</p>
+                </div>
+                <div style="text-align:center;padding:15px;">
+                    <h3 style="color:#667eea;">🛍️ E-commerce Brands</h3>
+                    <p style="color:#666;">Show product variations without inventory</p>
+                </div>
+                <div style="text-align:center;padding:15px;">
+                    <h3 style="color:#667eea;">🎨 Print-on-Demand</h3>
+                    <p style="color:#666;">Preview designs on products instantly</p>
+                </div>
+                <div style="text-align:center;padding:15px;">
+                    <h3 style="color:#667eea;">📱 Content Creators</h3>
+                    <p style="color:#666;">Create unique visuals for social media</p>
+                </div>
+            </div>
+        </div>
+    """)
+
+    # ──────── Event Handlers ────────
+    def update_status_display():
+        """Check backend status and update display"""
+        status_msg, is_ready = try_connect_backend()
+        
+        if is_ready:
+            css_class = "status-ready"
+        elif "starting up" in status_msg:
+            css_class = "status-starting"
+        else:
+            css_class = "status-error"
+        
+        status_html = f'<div class="status-banner {css_class}">{status_msg}</div>'
+        return status_html
+    
+    # Status check button click
+    check_status_btn.click(
+        fn=update_status_display,
+        outputs=[status_display]
+    )
+    
+    # Generate button click
+    generate_btn.click(
+        fn=call_backend_with_retry,
+        inputs=[print_image, product_image],
+        outputs=[result_img, status_text],
+        show_progress="full",
+        concurrency_limit=8,
+    )
+
+    # ──────── Footer ────────
+    gr.HTML("""
+        <div style="text-align:center;padding:40px 20px;background:#f8fafc;border:1px solid #e2e8f0;border-radius:16px;margin:30px 0;">
+            <h3 style="color:#333;">🚀 Powered by Snapwear AI</h3>
+            <p style="color:#666;">
+                Transform your creative vision with professional-grade AI technology.<br/>
+                Join thousands of designers, brands, and creators already using our tools.
+            </p>
+            <div class="social-links">
+                <a href="https://snapwear.io" target="_blank">🌐 Website</a>
+                <a href="https://www.instagram.com/snapwearai/" target="_blank">📸 Instagram</a>
+                <a href="https://huggingface.co/spaces/SnapwearAI/Snapwear-Virtual-Try-On" target="_blank">👗 Virtual Try-On</a>
+            </div>
+            <p style="font-size:12px;color:#999;margin-top:20px;">
+                © 2024 Snapwear AI. Professional AI tools for fashion and design.
+            </p>
+        </div>
+    """)
+
+if __name__ == "__main__":
+    demo.queue(
+        max_size=20,
+        default_concurrency_limit=8,
+        api_open=False
+    ).launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        show_api=False
+    )

requirements.txt

@@ -0,0 +1,3 @@
+gradio>=5.9.0
+gradio-client>=0.8.0
+pillow>=9.0.0