add video demo

.cursorindexingignore

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+
+# Don't index SpecStory auto-save files, but allow explicit context inclusion via @ references
+.specstory/**

.specstory/.gitignore

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+# SpecStory explanation file
+/.what-is-this.md

app.py

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 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def create_endosight_demo():
+    # Project description and information
+    project_info = """
+    # 🔬 EndoSight AI - Development Preview
+    
+    **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
+    
+    ---
+    
+    ## 🎯 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
+    
+    ## 🏥 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
+    
+    ---
+    
+    ### 📊 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
+    
+    ### 🔧 Technical Stack
+    - **Detection**: YOLOv8 (Ultralytics)
+    - **Segmentation**: U-Net Architecture  
+    - **Framework**: PyTorch, OpenCV
+    - **Deployment**: Docker, FastAPI backend
+    
+    ---
+    
+    ## 📹 Live Demo Preview
+    
+    **Note**: This is a development preview. The video below demonstrates EndoSight AI's real-time detection and segmentation capabilities on sample endoscopy footage.
+    
+    *Full interactive demo coming soon with model deployment.*
+    """
+    
+    # Create the interface using Blocks for more control
+    with gr.Blocks(
+        title="EndoSight AI - Gastrointestinal Polyp Detection System",
+        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)
+        
+        # Video demonstration section
+        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",
+                    show_label=True,
+                    height=400,
+                    width=600,
+                    interactive=False
+                )
+                
+                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
+                """)
+        
+        # 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.*
+            """)
+    
+    return demo
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Launch the demo
+if __name__ == "__main__":
+    demo = create_endosight_demo()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False
+    )

requirements.txt

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+gradio==4.44.0