update app

app.py

@@ -1,137 +1,108 @@
 import gradio as gr
 
-def create_endosight_demo():
-    # Project description and information
-    project_info = """
-    # 🔬 EndoSight AI - Development Preview
+def create_demo():
+    title = "🔬 EndoSight AI - Development Preview"
     
-    **Advanced Gastrointestinal Polyp Detection & Analysis System**
+    description = """
+    ## Advanced Gastrointestinal Polyp Detection & Analysis System
     
-    EndoSight AI combines YOLOv8 object detection with U-Net segmentation to provide:
-    - **Real-time polyp detection** at 35+ FPS
-    - **Precise boundary segmentation** with 92% pixel accuracy  
-    - **Quantitative size measurement** for clinical decision support
-    - **88% mAP@0.5 detection accuracy** on validation datasets
+    **Performance Metrics:**
+    - **88% mAP@0.5** detection accuracy
+    - **92% pixel-level** segmentation accuracy  
+    - **35+ FPS** real-time processing
+    - **YOLOv8 + U-Net** dual architecture
+    
+    ### 🏥 Clinical Capabilities
+    - Real-time polyp detection and localization
+    - Precise boundary segmentation with pixel-level accuracy
+    - Quantitative size measurement for clinical decision support
+    - Optimized for endoscopy workflow integration
+    
+    ### 🎯 Technical Highlights
+    - **Multi-modal AI**: Combined object detection and segmentation
+    - **Clinical-grade performance**: Sub-second processing times
+    - **Automated measurement**: Size, area, and morphometric analysis
+    - **Real-time inference**: GPU-accelerated deployment ready
     
     ---
     
-    ## 🎯 Key Capabilities
-    - **Multi-modal AI Architecture**: YOLOv8-UNet pipeline
-    - **Clinical Integration**: Real-time processing for endoscopy workflows
-    - **Quantitative Analysis**: Automated polyp measurement and morphometry
-    - **High Performance**: GPU-optimized for clinical deployment
+    ## 🎥 Live System Demonstration
     
-    ## 🏥 Clinical Impact
-    This system enables gastroenterologists to:
-    - Detect polyps with higher accuracy and consistency
-    - Obtain precise measurements for treatment planning  
-    - Reduce procedure time through automated analysis
-    - Improve early detection of potentially malignant lesions
+    **Real-time EndoSight AI in action** - showcasing automated polyp detection, segmentation, and measurement analysis on endoscopy footage.
+    """
     
+    footer = """
     ---
     
-    ### 📊 Performance Metrics
-    - **Detection Accuracy**: 88% mAP@0.5
-    - **Segmentation Accuracy**: 92% pixel-level precision
-    - **Processing Speed**: 35+ FPS real-time analysis
-    - **Model Size**: Optimized for clinical deployment
+    ## 🚀 Development Status & Impact
+    
+    ✅ **Model Training**: Complete with validation metrics achieved  
+    🔄 **Clinical Integration**: Active collaboration with gastroenterology clinic  
+    📊 **Performance**: Production-ready accuracy and speed benchmarks  
+    🎯 **Target**: Q1 2026 clinical deployment
     
-    ### 🔧 Technical Stack
-    - **Detection**: YOLOv8 (Ultralytics)
-    - **Segmentation**: U-Net Architecture  
-    - **Framework**: PyTorch, OpenCV
-    - **Deployment**: Docker, FastAPI backend
+    ### 🤝 Research Collaboration
+    
+    **Academic Partner**: Universidad Central de Venezuela
+    **Research Focus**: AI-Assisted Endoscopy & Computer-Aided Diagnosis  
+    
+    ### 📞 Professional Contact
+    
+    **Technical Lead**: Daniel Cavadia   
+    **Email**: dan.cavadia@gmail.com
     
     ---
     
-    ## 📹 Live Demo Preview
+    ### 🏥 Clinical Impact Potential
     
-    **Note**: This is a development preview. The video below demonstrates EndoSight AI's real-time detection and segmentation capabilities on sample endoscopy footage.
+    EndoSight AI aims to:
+    - **Improve detection rates** of early-stage polyps
+    - **Reduce procedure time** through automated analysis  
+    - **Enhance diagnostic consistency** across practitioners
+    - **Support clinical decision-making** with quantitative measurements
     
-    *Full interactive demo coming soon with model deployment.*
-    """
+    ---
     
-    # Create the interface using Blocks for more control
+    ⚕️ **Medical Disclaimer**: *Research prototype under clinical validation - not intended for diagnostic use. Always consult qualified medical professionals for medical decisions.*
+    """
+
     with gr.Blocks(
-        title="EndoSight AI - Gastrointestinal Polyp Detection System",
+        title="EndoSight AI - Gastrointestinal Polyp Detection",
         theme=gr.themes.Soft(),
-        css="""
-        .gradio-container {
-            max-width: 900px !important;
-            margin: auto;
-        }
-        .video-container {
-            border: 2px solid #e1e5e9;
-            border-radius: 10px;
-            padding: 20px;
-            margin: 20px 0;
-        }
-        """
     ) as demo:
         
-        # Header and description
-        gr.Markdown(project_info)
+        gr.Markdown(f"# {title}")
+        gr.Markdown(description)
         
-        # Video demonstration section
+        # Video section with autoplay and loop (GIF-like behavior)
         with gr.Row():
             with gr.Column():
-                gr.Markdown("### 🎥 System Demonstration")
-                
-                # Video component - you'll need to upload your video file to the Space
-                video_demo = gr.Video(
-                    value="demo_video.mp4",  # Replace with your video filename
-                    label="EndoSight AI Detection Demo",
+                gr.Video(
+                    value="demo_video.mp4",
+                    label="EndoSight AI Real-time Detection & Segmentation",
+                    height=500,
+                    width=700,
+                    autoplay=True,  # Starts automatically
+                    loop=True,      # Loops like a GIF
                     show_label=True,
-                    height=400,
-                    width=600,
-                    interactive=False
+                    interactive=False  # Users can't control playback
                 )
-                
+        
+        with gr.Row():
+            with gr.Column():
                 gr.Markdown("""
-                **Demo Features Shown:**
-                - Real-time polyp detection with bounding boxes
-                - Precise segmentation masks overlaid on video
-                - Quantitative measurements displayed in real-time
-                - Multi-polyp detection in single frame
-                - Processing speed and accuracy metrics
+                ### 🔍 What You're Seeing:
+                - **Blue bounding boxes**: Real-time polyp detection
+                - **Colored masks**: Precise segmentation boundaries  
+                - **Measurement overlays**: Automated size calculations
+                - **Processing metrics**: FPS and accuracy indicators
+                - **Multi-polyp detection**: Simultaneous analysis capability
                 """)
         
-        # Contact and development status
-        with gr.Row():
-            gr.Markdown("""
-            ---
-            
-            ## 🚀 Development Status
-            
-            **Current Phase**: Model Training & Validation ✅  
-            **Next Phase**: Clinical Integration & Testing  
-            **Target Release**: Q1 2026
-            
-            ### 📞 Collaboration & Contact
-            
-            EndoSight AI is developed in collaboration with:
-            - **Academic Partner**: Universidad Central de Venezuela
-            - **Clinical Partner**: Private Gastroenterology Clinic
-            - **Research Focus**: AI-Assisted Endoscopy
-            
-            For technical inquiries, collaboration opportunities, or clinical trial participation:  
-            **Contact**: [Your Professional Email]  
-            **LinkedIn**: [Your LinkedIn Profile]  
-            **GitHub**: [Repository Link]
-            
-            ---
-            
-            ### ⚕️ Medical Disclaimer
-            *EndoSight AI is a research prototype under development. Not intended for clinical diagnosis. Always consult qualified medical professionals for medical decisions.*
-            """)
+        gr.Markdown(footer)
     
     return demo
 
-# Launch the demo
 if __name__ == "__main__":
-    demo = create_endosight_demo()
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        share=False
-    )
+    demo = create_demo()
+    demo.launch()