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basic_usage.py

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+"""
+Fashion Inpainting System - Example Implementation
+Correct usage of the fashion_safety_checker API
+"""
+
+from fashion_safety_checker import create_fashion_safety_pipeline
+
+def main():
+    """
+    Example usage of the Fashion Inpainting System
+    """
+    # Initialize the fashion safety pipeline
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Example 1: Basic transformation
+    print("🎨 Basic Fashion Transformation")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/realistic_vision_v2.safetensors",
+        outfit_prompt="elegant red evening dress",
+        output_path="outputs/red_evening_dress_result.jpg",
+        face_scale=0.90  # Manual face to body ratio adjustment
+    )
+    
+    if result['success']:
+        print("✅ Fashion transformation completed successfully")
+        print(f"Output saved to: {result.get('output_path', 'outputs/red_evening_dress_result.jpg')}")
+    else:
+        print("❌ Transformation blocked by safety system")
+        print(f"Blocking reason: {result['blocking_reason']}")
+        print(f"User message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 2: Different outfit style
+    print("🎨 Business Outfit Transformation")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/fashion_professional_v1.safetensors",
+        outfit_prompt="professional business suit, navy blue, elegant",
+        output_path="outputs/business_suit_result.jpg",
+        face_scale=0.85
+    )
+    
+    if result['success']:
+        print("✅ Business transformation completed")
+    else:
+        print("❌ Business transformation blocked")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 3: Swimwear (requires appropriate safety level)
+    print("🎨 Swimwear Transformation (Professional Use)")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/fashion_permissive_v1.safetensors",
+        outfit_prompt="elegant one-piece swimsuit, professional fashion photography",
+        output_path="outputs/swimwear_result.jpg",
+        face_scale=0.92
+    )
+    
+    if result['success']:
+        print("✅ Swimwear transformation completed")
+    else:
+        print("❌ Swimwear transformation blocked")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 4: Error handling for missing files
+    print("🎨 Error Handling Example")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/nonexistent_image.jpg",  # This will fail
+        checkpoint_path="checkpoints/some_checkpoint.safetensors",
+        outfit_prompt="casual summer dress",
+        output_path="outputs/error_test.jpg",
+        face_scale=0.90
+    )
+    
+    if result['success']:
+        print("✅ This shouldn't happen")
+    else:
+        print("❌ Expected error occurred")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+
+def advanced_usage_examples():
+    """
+    Advanced usage examples with different parameters
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Example with different face scales
+    face_scales = [0.80, 0.85, 0.90, 0.95]
+    
+    for i, scale in enumerate(face_scales):
+        print(f"🎨 Testing face_scale={scale}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path="examples/test_subject.jpg",
+            checkpoint_path="checkpoints/fashion_moderate.safetensors", 
+            outfit_prompt="classic white shirt and dark jeans",
+            output_path=f"outputs/face_scale_test_{scale}.jpg",
+            face_scale=scale
+        )
+        
+        if result['success']:
+            print(f"✅ face_scale={scale} completed successfully")
+        else:
+            print(f"❌ face_scale={scale} failed: {result['blocking_reason']}")
+
+def batch_processing_example():
+    """
+    Example of processing multiple transformations
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Batch transformation scenarios
+    transformations = [
+        {
+            "source": "examples/person1.jpg",
+            "checkpoint": "checkpoints/casual_wear.safetensors",
+            "prompt": "comfortable jeans and cozy sweater",
+            "output": "outputs/person1_casual.jpg",
+            "face_scale": 0.90
+        },
+        {
+            "source": "examples/person2.jpg", 
+            "checkpoint": "checkpoints/formal_wear.safetensors",
+            "prompt": "elegant black evening gown",
+            "output": "outputs/person2_formal.jpg",
+            "face_scale": 0.88
+        },
+        {
+            "source": "examples/person3.jpg",
+            "checkpoint": "checkpoints/business_wear.safetensors", 
+            "prompt": "professional gray suit with blue tie",
+            "output": "outputs/person3_business.jpg",
+            "face_scale": 0.85
+        }
+    ]
+    
+    successful_transformations = 0
+    failed_transformations = 0
+    
+    for i, transform in enumerate(transformations):
+        print(f"🎨 Processing transformation {i+1}/{len(transformations)}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path=transform["source"],
+            checkpoint_path=transform["checkpoint"],
+            outfit_prompt=transform["prompt"],
+            output_path=transform["output"],
+            face_scale=transform["face_scale"]
+        )
+        
+        if result['success']:
+            successful_transformations += 1
+            print(f"✅ Transformation {i+1} completed")
+        else:
+            failed_transformations += 1
+            print(f"❌ Transformation {i+1} failed: {result['blocking_reason']}")
+    
+    print(f"\n📊 Batch Processing Results:")
+    print(f"✅ Successful: {successful_transformations}")
+    print(f"❌ Failed: {failed_transformations}")
+    print(f"📈 Success Rate: {successful_transformations/len(transformations)*100:.1f}%")
+
+def safety_level_examples():
+    """
+    Examples demonstrating different safety behaviors
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Test different prompts with safety implications
+    test_cases = [
+        ("conservative business outfit", "Should pass all safety levels"),
+        ("summer beach dress", "Should pass moderate and permissive"),
+        ("elegant swimwear", "May require permissive safety level"),
+        ("inappropriate content", "Should be blocked by safety system")
+    ]
+    
+    for prompt, expectation in test_cases:
+        print(f"\n🧪 Testing prompt: '{prompt}'")
+        print(f"   Expected: {expectation}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path="examples/test_image.jpg",
+            checkpoint_path="checkpoints/general_fashion.safetensors",
+            outfit_prompt=prompt,
+            output_path=f"outputs/safety_test_{prompt.replace(' ', '_')}.jpg",
+            face_scale=0.90
+        )
+        
+        if result['success']:
+            print(f"   ✅ Result: Transformation completed")
+        else:
+            print(f"   ❌ Result: Blocked - {result['blocking_reason']}")
+            print(f"   💬 Message: {result['user_message']}")
+
+if __name__ == "__main__":
+    print("🎨 Fashion Inpainting System - Example Usage\n")
+    
+    # Run basic examples
+    main()
+    
+    print("\n" + "="*60)
+    print("Advanced Examples")
+    print("="*60)
+    
+    # Uncomment to run advanced examples
+    # advanced_usage_examples()
+    # batch_processing_example() 
+    # safety_level_examples()
+    
+    print("\n✨ Examples completed!")
+    print("📖 For more information, see the documentation at:")
+    print("   GitHub: https://github.com/your-org/fashion-inpainting-system")
+    print("   Hugging Face: https://huggingface.co/your-org/fashion-inpainting-system")

quickstart.md

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+"""
+Fashion Inpainting System - Example Implementation
+Correct usage of the fashion_safety_checker API
+"""
+
+from fashion_safety_checker import create_fashion_safety_pipeline
+
+def main():
+    """
+    Example usage of the Fashion Inpainting System
+    """
+    # Initialize the fashion safety pipeline
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Example 1: Basic transformation
+    print("🎨 Basic Fashion Transformation")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/realistic_vision_v2.safetensors",
+        outfit_prompt="elegant red evening dress",
+        output_path="outputs/red_evening_dress_result.jpg",
+        face_scale=0.90  # Manual face to body ratio adjustment
+    )
+    
+    if result['success']:
+        print("✅ Fashion transformation completed successfully")
+        print(f"Output saved to: {result.get('output_path', 'outputs/red_evening_dress_result.jpg')}")
+    else:
+        print("❌ Transformation blocked by safety system")
+        print(f"Blocking reason: {result['blocking_reason']}")
+        print(f"User message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 2: Different outfit style
+    print("🎨 Business Outfit Transformation")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/fashion_professional_v1.safetensors",
+        outfit_prompt="professional business suit, navy blue, elegant",
+        output_path="outputs/business_suit_result.jpg",
+        face_scale=0.85
+    )
+    
+    if result['success']:
+        print("✅ Business transformation completed")
+    else:
+        print("❌ Business transformation blocked")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 3: Swimwear (requires appropriate safety level)
+    print("🎨 Swimwear Transformation (Professional Use)")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/person_in_casual_wear.jpg",
+        checkpoint_path="checkpoints/fashion_permissive_v1.safetensors",
+        outfit_prompt="elegant one-piece swimsuit, professional fashion photography",
+        output_path="outputs/swimwear_result.jpg",
+        face_scale=0.92
+    )
+    
+    if result['success']:
+        print("✅ Swimwear transformation completed")
+    else:
+        print("❌ Swimwear transformation blocked")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+    
+    print("-" * 50)
+    
+    # Example 4: Error handling for missing files
+    print("🎨 Error Handling Example")
+    result = pipeline.safe_fashion_transformation(
+        source_image_path="examples/nonexistent_image.jpg",  # This will fail
+        checkpoint_path="checkpoints/some_checkpoint.safetensors",
+        outfit_prompt="casual summer dress",
+        output_path="outputs/error_test.jpg",
+        face_scale=0.90
+    )
+    
+    if result['success']:
+        print("✅ This shouldn't happen")
+    else:
+        print("❌ Expected error occurred")
+        print(f"Reason: {result['blocking_reason']}")
+        print(f"Message: {result['user_message']}")
+
+def advanced_usage_examples():
+    """
+    Advanced usage examples with different parameters
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Example with different face scales
+    face_scales = [0.80, 0.85, 0.90, 0.95]
+    
+    for i, scale in enumerate(face_scales):
+        print(f"🎨 Testing face_scale={scale}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path="examples/test_subject.jpg",
+            checkpoint_path="checkpoints/fashion_moderate.safetensors", 
+            outfit_prompt="classic white shirt and dark jeans",
+            output_path=f"outputs/face_scale_test_{scale}.jpg",
+            face_scale=scale
+        )
+        
+        if result['success']:
+            print(f"✅ face_scale={scale} completed successfully")
+        else:
+            print(f"❌ face_scale={scale} failed: {result['blocking_reason']}")
+
+def batch_processing_example():
+    """
+    Example of processing multiple transformations
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Batch transformation scenarios
+    transformations = [
+        {
+            "source": "examples/person1.jpg",
+            "checkpoint": "checkpoints/casual_wear.safetensors",
+            "prompt": "comfortable jeans and cozy sweater",
+            "output": "outputs/person1_casual.jpg",
+            "face_scale": 0.90
+        },
+        {
+            "source": "examples/person2.jpg", 
+            "checkpoint": "checkpoints/formal_wear.safetensors",
+            "prompt": "elegant black evening gown",
+            "output": "outputs/person2_formal.jpg",
+            "face_scale": 0.88
+        },
+        {
+            "source": "examples/person3.jpg",
+            "checkpoint": "checkpoints/business_wear.safetensors", 
+            "prompt": "professional gray suit with blue tie",
+            "output": "outputs/person3_business.jpg",
+            "face_scale": 0.85
+        }
+    ]
+    
+    successful_transformations = 0
+    failed_transformations = 0
+    
+    for i, transform in enumerate(transformations):
+        print(f"🎨 Processing transformation {i+1}/{len(transformations)}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path=transform["source"],
+            checkpoint_path=transform["checkpoint"],
+            outfit_prompt=transform["prompt"],
+            output_path=transform["output"],
+            face_scale=transform["face_scale"]
+        )
+        
+        if result['success']:
+            successful_transformations += 1
+            print(f"✅ Transformation {i+1} completed")
+        else:
+            failed_transformations += 1
+            print(f"❌ Transformation {i+1} failed: {result['blocking_reason']}")
+    
+    print(f"\n📊 Batch Processing Results:")
+    print(f"✅ Successful: {successful_transformations}")
+    print(f"❌ Failed: {failed_transformations}")
+    print(f"📈 Success Rate: {successful_transformations/len(transformations)*100:.1f}%")
+
+def safety_level_examples():
+    """
+    Examples demonstrating different safety behaviors
+    """
+    pipeline = create_fashion_safety_pipeline()
+    
+    # Test different prompts with safety implications
+    test_cases = [
+        ("conservative business outfit", "Should pass all safety levels"),
+        ("summer beach dress", "Should pass moderate and permissive"),
+        ("elegant swimwear", "May require permissive safety level"),
+        ("inappropriate content", "Should be blocked by safety system")
+    ]
+    
+    for prompt, expectation in test_cases:
+        print(f"\n🧪 Testing prompt: '{prompt}'")
+        print(f"   Expected: {expectation}")
+        
+        result = pipeline.safe_fashion_transformation(
+            source_image_path="examples/test_image.jpg",
+            checkpoint_path="checkpoints/general_fashion.safetensors",
+            outfit_prompt=prompt,
+            output_path=f"outputs/safety_test_{prompt.replace(' ', '_')}.jpg",
+            face_scale=0.90
+        )
+        
+        if result['success']:
+            print(f"   ✅ Result: Transformation completed")
+        else:
+            print(f"   ❌ Result: Blocked - {result['blocking_reason']}")
+            print(f"   💬 Message: {result['user_message']}")
+
+if __name__ == "__main__":
+    print("🎨 Fashion Inpainting System - Example Usage\n")
+    
+    # Run basic examples
+    main()
+    
+    print("\n" + "="*60)
+    print("Advanced Examples")
+    print("="*60)
+    
+    # Uncomment to run advanced examples
+    # advanced_usage_examples()
+    # batch_processing_example() 
+    # safety_level_examples()
+    
+    print("\n✨ Examples completed!")
+    print("📖 For more information, see the documentation at:")
+    print("   GitHub: https://github.com/your-org/fashion-inpainting-system")
+    print("   Hugging Face: https://huggingface.co/your-org/fashion-inpainting-system")