update gradio

app.py

@@ -1,116 +1,87 @@
-import streamlit as st
-import base64
-
-# Configure the page
-st.set_page_config(
-    page_title="EndoSight AI - Gastrointestinal Polyp Detection",
-    page_icon="🔬",
-    layout="wide"
-)
-
-def get_video_html(video_path):
-    """Create HTML for auto-playing, looping video"""
-    with open(video_path, "rb") as video_file:
-        video_bytes = video_file.read()
-    
-    video_base64 = base64.b64encode(video_bytes).decode('utf-8')
-    
-    video_html = f"""
-    <video width="100%" height="500" autoplay muted loop controls style="border-radius: 10px; border: 2px solid #e1e5e9;">
-        <source src="data:video/mp4;base64,{video_base64}" type="video/mp4">
-        Your browser does not support the video tag.
-    </video>
-    """
-    return video_html
-
-# Main app
-def main():
-    # Header
-    st.markdown("# 🔬 EndoSight AI - Development Preview")
-    
-    # Description
-    st.markdown("""
-    ## Advanced Gastrointestinal Polyp Detection & Analysis System
-    
-    **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
-    
-    ---
-    
-    ## 🎥 Live System Demonstration
-    
-    **Real-time EndoSight AI in action** - showcasing automated polyp detection, segmentation, and measurement analysis on endoscopy footage.
-    """)
-    
-    # Video section
-    try:
-        video_html = get_video_html("demo_video.mp4")
-        st.markdown(video_html, unsafe_allow_html=True)
-    except FileNotFoundError:
-        st.error("Video file not found. Please upload demo_video.mp4 to your Space.")
-    
-    # Video description
-    st.markdown("""
-    ### 🔍 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
-    """)
-    
-    # Footer
-    st.markdown("""
-    ---
-    
-    ## 🚀 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
-    
-    ### 🤝 Research Collaboration
-    
-    **Academic Partner**: Universidad Central de Venezuela  
-    **Clinical Partner**: Private Gastroenterology Clinic  
-    **Research Focus**: AI-Assisted Endoscopy & Computer-Aided Diagnosis  
-    
-    ### 📞 Professional Contact
-    
-    **Technical Lead**: Daniel Cavadia  
-    **LinkedIn**: Connect for collaboration opportunities  
-    **Portfolio**: View complete AI/ML project portfolio  
-    
-    ---
-    
-    ### 🏥 Clinical Impact Potential
-    
-    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
+import gradio as gr
+
+def create_demo():
+    title = "🔬 EndoSight AI - Development Preview"
     
-    ---
+    description = """
+## Advanced Gastrointestinal Polyp Detection & Analysis System
+
+**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
+
+---
+
+## 🎥 Live System Demonstration
+
+**Real-time EndoSight AI in action** - showcasing automated polyp detection, segmentation, and measurement analysis on endoscopy footage.
+"""
     
-    ⚕️ **Medical Disclaimer**: *Research prototype under clinical validation - not intended for diagnostic use. Always consult qualified medical professionals for medical decisions.*
-    """)
+    footer = """
+---
+
+## 🚀 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
+
+### 🤝 Research Collaboration
+
+**Academic Partner**: Universidad Central de Venezuela  
+**Clinical Partner**: Private Gastroenterology Clinic  
+**Research Focus**: AI-Assisted Endoscopy & Computer-Aided Diagnosis  
+
+### 📞 Professional Contact
+
+**Technical Lead**: Daniel Cavadia  
+**LinkedIn**: Connect for collaboration opportunities  
+**Portfolio**: View complete AI/ML project portfolio  
+
+---
+
+⚕️ **Medical Disclaimer**: *Research prototype under clinical validation - not intended for diagnostic use.*
+"""
+
+    # Create simple interface using Gradio 3.34.0 syntax
+    with gr.Blocks(title="EndoSight AI") as demo:
+        gr.Markdown(f"# {title}")
+        gr.Markdown(description)
+        
+        # Simple video display (no fancy features in older version)
+        video = gr.Video(
+            value="demo_video.mp4",
+            label="EndoSight AI Real-time Detection & Segmentation"
+        )
+        
+        gr.Markdown("""
+### 🔍 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
+""")
+        
+        gr.Markdown(footer)
+    
+    return demo
 
 if __name__ == "__main__":
-    main()
+    demo = create_demo()
+    demo.launch()

requirements.txt

@@ -1 +1 @@
-streamlit
+gradio==3.34.0