update streamlit

app.py

@@ -1,86 +1,116 @@
-import gradio as gr
-
-def create_demo():
-    title = "🔬 EndoSight AI - Development Preview"
+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()
     
-    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.
-"""
+    video_base64 = base64.b64encode(video_bytes).decode('utf-8')
     
-    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  
-**Research Focus**: AI-Assisted Endoscopy & Computer-Aided Diagnosis  
-
-### 📞 Professional Contact
-
-**Technical Lead**: Daniel Cavadia  
-
----
-
-⚕️ **Medical Disclaimer**: *Research prototype under clinical validation - not intended for diagnostic use.*
-"""
-
-    # Create interface using Gradio 3.x syntax
-    with gr.Blocks(title="EndoSight AI") as demo:
-        gr.Markdown(f"# {title}")
-        gr.Markdown(description)
-        
-        # Video component (simpler syntax for v3.x)
-        with gr.Row():
-            video = gr.Video(
-                value="demo_video.mp4",
-                label="EndoSight AI Real-time Detection & Segmentation"
-            )
-        
-        with gr.Row():
-            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
+    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
+    
+    ---
+    
+    ⚕️ **Medical Disclaimer**: *Research prototype under clinical validation - not intended for diagnostic use. Always consult qualified medical professionals for medical decisions.*
+    """)
 
 if __name__ == "__main__":
-    demo = create_demo()
-    demo.launch()
+    main()

requirements.txt

@@ -1,2 +1 @@
-gradio==3.50.2
-websockets
+streamlit