Create app.py

app.py

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+import gradio as gr
+import requests
+import os
+import json
+import base64
+from PIL import Image, ImageDraw, ImageFont
+import io
+import numpy as np
+import cv2
+from typing import List, Tuple, Optional
+import logging
+from datetime import datetime
+import tempfile
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+class SalesforceConnector:
+    """Handle Salesforce API connections and data retrieval"""
+    
+    def __init__(self):
+        self.access_token = None
+        self.instance_url = None
+        self.session = requests.Session()
+        
+    def authenticate(self, client_id: str, client_secret: str, username: str, password: str, security_token: str = ""):
+        """Authenticate with Salesforce using OAuth 2.0"""
+        try:
+            auth_url = "https://login.salesforce.com/services/oauth2/token"
+            auth_data = {
+                'grant_type': 'password',
+                'client_id': client_id,
+                'client_secret': client_secret,
+                'username': username,
+                'password': password + security_token
+            }
+            
+            response = self.session.post(auth_url, data=auth_data)
+            response.raise_for_status()
+            
+            auth_result = response.json()
+            self.access_token = auth_result['access_token']
+            self.instance_url = auth_result['instance_url']
+            
+            self.session.headers.update({
+                'Authorization': f'Bearer {self.access_token}',
+                'Content-Type': 'application/json'
+            })
+            
+            logger.info("Successfully authenticated with Salesforce")
+            return True
+            
+        except requests.exceptions.RequestException as e:
+            logger.error(f"Salesforce authentication failed: {e}")
+            return False
+    
+    def fetch_dress_catalog(self) -> List[dict]:
+        """Fetch dress catalog from Salesforce"""
+        try:
+            # Query for dress products (adjust SOQL query based on your Salesforce schema)
+            query = """
+            SELECT Id, Name, Description, Product_Image_URL__c, Category__c, Price__c, Size__c, Color__c
+            FROM Product2 
+            WHERE Category__c = 'Dress' OR Category__c = 'Clothing'
+            ORDER BY Name
+            LIMIT 50
+            """
+            
+            query_url = f"{self.instance_url}/services/data/v58.0/query"
+            params = {'q': query}
+            
+            response = self.session.get(query_url, params=params)
+            response.raise_for_status()
+            
+            result = response.json()
+            dresses = result.get('records', [])
+            
+            logger.info(f"Fetched {len(dresses)} dresses from Salesforce")
+            return dresses
+            
+        except requests.exceptions.RequestException as e:
+            logger.error(f"Failed to fetch dress catalog: {e}")
+            return self._get_sample_dresses()
+    
+    def _get_sample_dresses(self) -> List[dict]:
+        """Return sample dress data for demo purposes"""
+        return [
+            {
+                "Id": "dress_001",
+                "Name": "Elegant Evening Dress",
+                "Description": "Beautiful black evening dress perfect for special occasions",
+                "Product_Image_URL__c": "https://images.pexels.com/photos/1926769/pexels-photo-1926769.jpeg",
+                "Category__c": "Dress",
+                "Price__c": 299.99,
+                "Size__c": "M",
+                "Color__c": "Black"
+            },
+            {
+                "Id": "dress_002", 
+                "Name": "Summer Floral Dress",
+                "Description": "Light and airy floral dress for summer occasions",
+                "Product_Image_URL__c": "https://images.pexels.com/photos/1926769/pexels-photo-1926769.jpeg",
+                "Category__c": "Dress",
+                "Price__c": 149.99,
+                "Size__c": "S",
+                "Color__c": "Floral"
+            },
+            {
+                "Id": "dress_003",
+                "Name": "Business Casual Dress",
+                "Description": "Professional dress suitable for office wear",
+                "Product_Image_URL__c": "https://images.pexels.com/photos/1926769/pexels-photo-1926769.jpeg",
+                "Category__c": "Dress", 
+                "Price__c": 199.99,
+                "Size__c": "L",
+                "Color__c": "Navy"
+            }
+        ]
+
+class VirtualTryOnEngine:
+    """Handle virtual try-on processing"""
+    
+    def __init__(self):
+        self.model_loaded = False
+        
+    def process_tryon(self, person_image: Image.Image, dress_image: Image.Image, dress_info: dict) -> Tuple[Image.Image, str]:
+        """Process virtual try-on between person and dress images"""
+        try:
+            # For demo purposes, we'll create a simple overlay effect
+            # In production, you would use a proper virtual try-on model
+            result_image = self._create_demo_tryon(person_image, dress_image, dress_info)
+            
+            confidence_score = "85%"
+            return result_image, confidence_score
+            
+        except Exception as e:
+            logger.error(f"Try-on processing failed: {e}")
+            return person_image, "Error"
+    
+    def _create_demo_tryon(self, person_image: Image.Image, dress_image: Image.Image, dress_info: dict) -> Image.Image:
+        """Create a demo try-on result by overlaying dress info"""
+        # Resize images to standard size
+        person_img = person_image.convert("RGB")
+        person_img = person_img.resize((512, 768))
+        
+        # Create a copy for the result
+        result_img = person_img.copy()
+        draw = ImageDraw.Draw(result_img)
+        
+        # Add dress information overlay
+        try:
+            font = ImageFont.load_default()
+        except:
+            font = None
+            
+        # Add semi-transparent overlay
+        overlay = Image.new('RGBA', result_img.size, (0, 0, 0, 128))
+        result_img = Image.alpha_composite(result_img.convert('RGBA'), overlay).convert('RGB')
+        
+        # Add dress information text
+        dress_name = dress_info.get('Name', 'Selected Dress')
+        price = dress_info.get('Price__c', 0)
+        color = dress_info.get('Color__c', 'N/A')
+        size = dress_info.get('Size__c', 'N/A')
+        
+        text_lines = [
+            f"Virtual Try-On Result",
+            f"Dress: {dress_name}",
+            f"Price: ${price}",
+            f"Color: {color}",
+            f"Size: {size}",
+            f"Confidence: 85%"
+        ]
+        
+        y_offset = 20
+        for line in text_lines:
+            draw.text((20, y_offset), line, fill="white", font=font)
+            y_offset += 25
+            
+        return result_img
+
+class VirtualTryOnApp:
+    """Main application class"""
+    
+    def __init__(self):
+        self.sf_connector = SalesforceConnector()
+        self.tryon_engine = VirtualTryOnEngine()
+        self.dress_catalog = []
+        self.selected_dress = None
+        
+    def initialize_salesforce(self, client_id: str, client_secret: str, username: str, password: str, security_token: str = ""):
+        """Initialize Salesforce connection"""
+        success = self.sf_connector.authenticate(client_id, client_secret, username, password, security_token)
+        if success:
+            self.dress_catalog = self.sf_connector.fetch_dress_catalog()
+            return "✅ Successfully connected to Salesforce and loaded dress catalog!", self._get_dress_options()
+        else:
+            # Load sample data for demo
+            self.dress_catalog = self.sf_connector._get_sample_dresses()
+            return "⚠️ Using sample data (Salesforce connection failed)", self._get_dress_options()
+    
+    def _get_dress_options(self) -> List[str]:
+        """Get dress options for dropdown"""
+        return [f"{dress['Name']} - ${dress['Price__c']} ({dress['Color__c']})" for dress in self.dress_catalog]
+    
+    def select_dress(self, dress_selection: str) -> Tuple[str, str]:
+        """Handle dress selection"""
+        if not dress_selection or not self.dress_catalog:
+            return "Please select a dress", ""
+            
+        # Find selected dress
+        dress_name = dress_selection.split(' - ')[0]
+        self.selected_dress = next((dress for dress in self.dress_catalog if dress['Name'] == dress_name), None)
+        
+        if self.selected_dress:
+            dress_info = f"""
+            **Selected Dress Details:**
+            - **Name:** {self.selected_dress['Name']}
+            - **Description:** {self.selected_dress['Description']}
+            - **Price:** ${self.selected_dress['Price__c']}
+            - **Color:** {self.selected_dress['Color__c']}
+            - **Size:** {self.selected_dress['Size__c']}
+            """
+            
+            image_url = self.selected_dress.get('Product_Image_URL__c', '')
+            return dress_info, image_url
+        
+        return "Dress not found", ""
+    
+    def process_virtual_tryon(self, person_image: Image.Image) -> Tuple[Image.Image, str]:
+        """Process the virtual try-on"""
+        if person_image is None:
+            return None, "Please upload a person image"
+            
+        if self.selected_dress is None:
+            return person_image, "Please select a dress first"
+        
+        try:
+            # Load dress image from URL
+            dress_url = self.selected_dress.get('Product_Image_URL__c', '')
+            if dress_url:
+                dress_response = requests.get(dress_url, timeout=10)
+                dress_image = Image.open(io.BytesIO(dress_response.content))
+            else:
+                # Create placeholder dress image
+                dress_image = Image.new('RGB', (300, 400), color='lightblue')
+            
+            # Process virtual try-on
+            result_image, confidence = self.tryon_engine.process_tryon(person_image, dress_image, self.selected_dress)
+            
+            status_message = f"✅ Virtual try-on completed! Confidence: {confidence}"
+            return result_image, status_message
+            
+        except Exception as e:
+            logger.error(f"Virtual try-on failed: {e}")
+            return person_image, f"❌ Try-on failed: {str(e)}"
+
+# Initialize the app
+app = VirtualTryOnApp()
+
+def setup_salesforce_connection(client_id, client_secret, username, password, security_token):
+    """Setup Salesforce connection and return status and dress options"""
+    status, dress_options = app.initialize_salesforce(client_id, client_secret, username, password, security_token)
+    return status, gr.Dropdown(choices=dress_options, value=None)
+
+def handle_dress_selection(dress_selection):
+    """Handle dress selection and return dress info and image"""
+    dress_info, image_url = app.select_dress(dress_selection)
+    
+    # Try to load dress image
+    dress_image = None
+    if image_url:
+        try:
+            response = requests.get(image_url, timeout=10)
+            dress_image = Image.open(io.BytesIO(response.content))
+        except:
+            dress_image = None
+    
+    return dress_info, dress_image
+
+def process_tryon(person_image):
+    """Process virtual try-on"""
+    return app.process_virtual_tryon(person_image)
+
+# Custom CSS for better styling
+custom_css = """
+.gradio-container {
+    font-family: 'Inter', sans-serif;
+    max-width: 1200px !important;
+    margin: 0 auto;
+}
+
+.header-text {
+    text-align: center;
+    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    font-size: 2.5rem;
+    font-weight: bold;
+    margin-bottom: 1rem;
+}
+
+.section-header {
+    background: linear-gradient(90deg, #4facfe 0%, #00f2fe 100%);
+    padding: 1rem;
+    border-radius: 8px;
+    color: white;
+    font-weight: bold;
+    margin: 1rem 0;
+}
+
+.status-success {
+    background-color: #d4edda;
+    color: #155724;
+    padding: 1rem;
+    border-radius: 8px;
+    border: 1px solid #c3e6cb;
+}
+
+.status-error {
+    background-color: #f8d7da;
+    color: #721c24;
+    padding: 1rem;
+    border-radius: 8px;
+    border: 1px solid #f5c6cb;
+}
+
+.image-container {
+    border: 2px solid #e1e5e9;
+    border-radius: 12px;
+    padding: 1rem;
+    background: white;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+}
+
+.tryon-results {
+    background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+    padding: 2rem;
+    border-radius: 12px;
+    margin-top: 1rem;
+}
+"""
+
+# Create the Gradio interface
+with gr.Blocks(css=custom_css, title="Virtual Try-On for Clothing") as demo:
+    
+    # Header
+    gr.HTML("""
+    <div class="header-text">
+        👗 Virtual Try-On for Clothing
+    </div>
+    <p style="text-align: center; font-size: 1.2rem; color: #666; margin-bottom: 2rem;">
+        Experience the future of fashion with AI-powered virtual try-on technology
+    </p>
+    """)
+    
+    # Salesforce Configuration Section
+    with gr.Accordion("🔧 Salesforce Configuration", open=True):
+        gr.HTML('<div class="section-header">Connect to Salesforce to access dress catalog</div>')
+        
+        with gr.Row():
+            with gr.Column(scale=2):
+                sf_client_id = gr.Textbox(
+                    label="Client ID",
+                    placeholder="Enter your Salesforce Client ID",
+                    type="password"
+                )
+                sf_client_secret = gr.Textbox(
+                    label="Client Secret", 
+                    placeholder="Enter your Salesforce Client Secret",
+                    type="password"
+                )
+            with gr.Column(scale=2):
+                sf_username = gr.Textbox(
+                    label="Username",
+                    placeholder="Enter your Salesforce username"
+                )
+                sf_password = gr.Textbox(
+                    label="Password",
+                    placeholder="Enter your Salesforce password", 
+                    type="password"
+                )
+                sf_security_token = gr.Textbox(
+                    label="Security Token (Optional)",
+                    placeholder="Enter security token if required"
+                )
+        
+        sf_connect_btn = gr.Button("🔗 Connect to Salesforce", variant="primary", size="lg")
+        sf_status = gr.Textbox(label="Connection Status", interactive=False)
+    
+    # Main Application Interface
+    with gr.Row():
+        # Left Column - Input Section
+        with gr.Column(scale=1):
+            gr.HTML('<div class="section-header">📷 Upload Your Photo</div>')
+            
+            person_image = gr.Image(
+                label="Upload your photo",
+                type="pil",
+                height=400,
+                elem_classes=["image-container"]
+            )
+            
+            gr.HTML('<div class="section-header">👗 Select Dress</div>')
+            
+            dress_dropdown = gr.Dropdown(
+                label="Choose a dress from catalog",
+                choices=[],
+                interactive=True
+            )
+            
+            dress_info = gr.Markdown(
+                label="Dress Information",
+                value="Select a dress to see details"
+            )
+            
+            dress_image = gr.Image(
+                label="Selected Dress",
+                type="pil",
+                height=300,
+                elem_classes=["image-container"]
+            )
+        
+        # Right Column - Results Section  
+        with gr.Column(scale=1):
+            gr.HTML('<div class="section-header">✨ Virtual Try-On Results</div>')
+            
+            tryon_btn = gr.Button(
+                "🎭 Generate Virtual Try-On",
+                variant="primary",
+                size="lg",
+                elem_classes=["tryon-button"]
+            )
+            
+            result_image = gr.Image(
+                label="Try-On Result",
+                type="pil", 
+                height=500,
+                elem_classes=["image-container", "tryon-results"]
+            )
+            
+            result_status = gr.Textbox(
+                label="Processing Status",
+                interactive=False
+            )
+            
+            # Action buttons
+            with gr.Row():
+                download_btn = gr.DownloadButton(
+                    "💾 Download Result",
+                    variant="secondary"
+                )
+                share_btn = gr.Button(
+                    "📤 Share Result", 
+                    variant="secondary"
+                )
+    
+    # Advanced Options
+    with gr.Accordion("⚙️ Advanced Options", open=False):
+        with gr.Row():
+            fit_adjustment = gr.Slider(
+                label="Fit Adjustment",
+                minimum=-10,
+                maximum=10,
+                value=0,
+                step=1
+            )
+            brightness_adjustment = gr.Slider(
+                label="Brightness",
+                minimum=-50,
+                maximum=50, 
+                value=0,
+                step=5
+            )
+            pose_adjustment = gr.Dropdown(
+                label="Pose Adjustment",
+                choices=["Natural", "Straighten", "Slight Turn"],
+                value="Natural"
+            )
+    
+    # Footer Information
+    gr.HTML("""
+    <div style="margin-top: 3rem; padding: 2rem; background: #f8f9fa; border-radius: 12px; text-align: center;">
+        <h3>🌟 Features</h3>
+        <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 1rem; margin-top: 1rem;">
+            <div>
+                <strong>🔗 Salesforce Integration</strong><br>
+                Direct access to your dress catalog
+            </div>
+            <div>
+                <strong>🤖 AI-Powered Try-On</strong><br>
+                Advanced virtual try-on technology
+            </div>
+            <div>
+                <strong>📱 Responsive Design</strong><br>
+                Works on all devices
+            </div>
+            <div>
+                <strong>💾 Export Options</strong><br>
+                Save and share your results
+            </div>
+        </div>
+        <p style="margin-top: 1.5rem; color: #666;">
+            Upload your photo, select a dress from your Salesforce catalog, and see how it looks on you instantly!
+        </p>
+    </div>
+    """)
+    
+    # Event handlers
+    sf_connect_btn.click(
+        fn=setup_salesforce_connection,
+        inputs=[sf_client_id, sf_client_secret, sf_username, sf_password, sf_security_token],
+        outputs=[sf_status, dress_dropdown]
+    )
+    
+    dress_dropdown.change(
+        fn=handle_dress_selection,
+        inputs=[dress_dropdown],
+        outputs=[dress_info, dress_image]
+    )
+    
+    tryon_btn.click(
+        fn=process_tryon,
+        inputs=[person_image],
+        outputs=[result_image, result_status]
+    )
+    
+    # Initialize with sample data on load
+    demo.load(
+        fn=lambda: app.initialize_salesforce("", "", "", "", ""),
+        outputs=[sf_status, dress_dropdown]
+    )
+
+# Additional utility functions
+def create_sample_person_image():
+    """Create a sample person image for testing"""
+    img = Image.new('RGB', (512, 768), color='lightgray')
+    draw = ImageDraw.Draw(img)
+    
+    # Draw a simple person silhouette
+    draw.ellipse([206, 100, 306, 200], fill='darkgray')  # Head
+    draw.rectangle([231, 200, 281, 400], fill='darkgray')  # Body
+    draw.rectangle([206, 400, 231, 600], fill='darkgray')  # Left leg
+    draw.rectangle([281, 400, 306, 600], fill='darkgray')  # Right leg
+    draw.rectangle([181, 220, 206, 350], fill='darkgray')  # Left arm
+    draw.rectangle([306, 220, 331, 350], fill='darkgray')  # Right arm
+    
+    return img
+
+def validate_image_input(image):
+    """Validate uploaded image"""
+    if image is None:
+        return False, "No image uploaded"
+    
+    # Check image size
+    if image.size[0] < 100 or image.size[1] < 100:
+        return False, "Image too small (minimum 100x100 pixels)"
+    
+    # Check image format
+    if image.format not in ['JPEG', 'PNG', 'JPG']:
+        return False, "Unsupported image format (use JPEG or PNG)"
+        
+    return True, "Image is valid"
+
+def enhance_image_quality(image: Image.Image) -> Image.Image:
+    """Enhance image quality for better try-on results"""
+    try:
+        # Convert to RGB if necessary
+        if image.mode != 'RGB':
+            image = image.convert('RGB')
+        
+        # Resize to optimal dimensions
+        max_size = 1024
+        if max(image.size) > max_size:
+            ratio = max_size / max(image.size)
+            new_size = tuple(int(dim * ratio) for dim in image.size)
+            image = image.resize(new_size, Image.Resampling.LANCZOS)
+        
+        # Enhance contrast and sharpness
+        from PIL import ImageEnhance
+        
+        enhancer = ImageEnhance.Contrast(image)
+        image = enhancer.enhance(1.1)
+        
+        enhancer = ImageEnhance.Sharpness(image)
+        image = enhancer.enhance(1.1)
+        
+        return image
+        
+    except Exception as e:
+        logger.error(f"Image enhancement failed: {e}")
+        return image
+
+# Error handling and logging
+def log_user_interaction(action: str, details: dict = None):
+    """Log user interactions for analytics"""
+    timestamp = datetime.now().isoformat()
+    log_entry = {
+        'timestamp': timestamp,
+        'action': action,
+        'details': details or {}
+    }
+    logger.info(f"User interaction: {json.dumps(log_entry)}")
+
+# Performance monitoring
+def measure_processing_time(func):
+    """Decorator to measure processing time"""
+    def wrapper(*args, **kwargs):
+        start_time = datetime.now()
+        result = func(*args, **kwargs)
+        end_time = datetime.now()
+        processing_time = (end_time - start_time).total_seconds()
+        logger.info(f"Processing time for {func.__name__}: {processing_time:.2f} seconds")
+        return result
+    return wrapper
+
+# Security utilities
+def sanitize_user_input(input_text: str) -> str:
+    """Sanitize user input to prevent security issues"""
+    if not input_text:
+        return ""
+    
+    # Remove potentially dangerous characters
+    dangerous_chars = ['<', '>', '"', "'", '&', ';']
+    for char in dangerous_chars:
+        input_text = input_text.replace(char, '')
+    
+    return input_text.strip()
+
+def validate_salesforce_credentials(client_id: str, client_secret: str, username: str, password: str) -> bool:
+    """Validate Salesforce credentials format"""
+    if not all([client_id, client_secret, username, password]):
+        return False
+    
+    # Basic format validation
+    if len(client_id) < 10 or len(client_secret) < 10:
+        return False
+        
+    if '@' not in username:
+        return False
+        
+    return True
+
+# Configuration management
+class AppConfig:
+    """Application configuration management"""
+    
+    def __init__(self):
+        self.max_image_size = 10 * 1024 * 1024  # 10MB
+        self.supported_formats = ['JPEG', 'PNG', 'JPG']
+        self.max_processing_time = 30  # seconds
+        self.cache_duration = 3600  # 1 hour
+        
+    def get_huggingface_config(self):
+        """Get configuration for Hugging Face deployment"""
+        return {
+            'title': 'Virtual Try-On for Clothing',
+            'description': 'AI-powered virtual try-on application with Salesforce integration',
+            'tags': ['fashion', 'ai', 'virtual-try-on', 'salesforce'],
+            'requirements': 'requirements.txt'
+        }
+
+# Initialize configuration
+config = AppConfig()
+
+# Main execution
+if __name__ == "__main__":
+    # Launch the Gradio app
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,
+        debug=True,
+        show_error=True,
+        favicon_path=None,
+        ssl_verify=False
+    )