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| import streamlit as st | |
| import os | |
| def show(): | |
| st.markdown('<div class="main-header">โน๏ธ About This Project</div>', unsafe_allow_html=True) | |
| # ACVSS Hackathon Information | |
| st.markdown("## ACVSS 2025 Summer School Hackathon Project") | |
| st.info( | |
| "This project was developed by **Team SATOR** as part of the **ACVSS 2025 - The 4th Summer School on Advanced Computer Vision** hackathon. " | |
| "Our goal was to build a functional prototype for surgical scene understanding in a limited time frame." | |
| ) | |
| # ACVSS Description | |
| st.markdown(""" | |
| ### About ACVSS | |
| The **African Computer Vision Summer School (ACVSS)** is an intensive program designed to advance computer vision research and applications across Africa. The summer school brings together researchers, students, and industry professionals to explore cutting-edge technologies in computer vision, machine learning, and artificial intelligence. | |
| **Learn more**: [acvss.ai](https://www.acvss.ai/) | **Year**: 2025 | **Edition**: 4th Summer School | |
| """) | |
| st.markdown("---") | |
| # Team Section | |
| st.markdown("## ๐ฅ Meet Team SATOR") | |
| # Add team description | |
| st.markdown(""" | |
| **Team SATOR** is a diverse group of professionals brought together for the ACVSS 2025 hackathon. | |
| Our team combines expertise in AI/ML, software engineering, data science, and quality assurance to deliver | |
| innovative solutions in surgical scene understanding. | |
| """) | |
| st.markdown("### Team Members") | |
| # Team Member Profiles | |
| team_members = [ | |
| { | |
| "name": "MEM1", | |
| "role": "Team Lead & System Architect", | |
| "desc": "Led the project, designed the overall system architecture, and ensured seamless integration of all components. Her vision guided the project's success.", | |
| "email": "[email protected]", | |
| "linkedin": "https://www.linkedin.com/in/evelyn-reed-acvss", | |
| "github": "https://github.com/evelyn-reed", | |
| "img": "https://i.pravatar.cc/150?img=1" | |
| }, | |
| { | |
| "name": "MEM2", | |
| "role": "AI/ML Specialist", | |
| "desc": "Focused on developing and training the core SwinUnet and scene understanding models. Responsible for the AI-powered analysis and insights.", | |
| "email": "[email protected]", | |
| "linkedin": "https://www.linkedin.com/in/kenji-tanaka-ml", | |
| "github": "https://github.com/kenji-tanaka", | |
| "img": "https://i.pravatar.cc/150?img=2" | |
| }, | |
| { | |
| "name": "MEM3", | |
| "role": "UI/UX & Frontend Developer", | |
| "desc": "Designed and built the Streamlit dashboard, focusing on creating an intuitive and informative user interface for surgeons and researchers.", | |
| "email": "[email protected]", | |
| "linkedin": "https://www.linkedin.com/in/sofia-rossi-ui", | |
| "github": "https://github.com/sofia-rossi", | |
| "img": "https://i.pravatar.cc/150?img=3" | |
| }, | |
| { | |
| "name": "MEM4", | |
| "role": "Data Engineer", | |
| "desc": "Managed the data pipeline, from processing the MM-OR dataset to ensuring the models received clean, well-structured data for training and testing.", | |
| "email": "[email protected]", | |
| "linkedin": "https://www.linkedin.com/in/david-chen-data", | |
| "github": "https://github.com/david-chen", | |
| "img": "https://i.pravatar.cc/150?img=4" | |
| }, | |
| { | |
| "name": "MEM5", | |
| "role": "QA & Testing Lead", | |
| "desc": "Oversaw the testing and validation of the entire pipeline, ensuring the system was robust, accurate, and met the project's objectives.", | |
| "email": "[email protected]", | |
| "linkedin": "https://www.linkedin.com/in/aisha-bello-qa", | |
| "github": "https://github.com/aisha-bello", | |
| "img": "https://i.pravatar.cc/150?img=5" | |
| } | |
| ] | |
| # Display team members in columns | |
| # Display team members in a responsive grid | |
| cols = st.columns(5) | |
| for i, member in enumerate(team_members): | |
| with cols[i]: | |
| st.markdown(f"##### {member['name']}") | |
| st.image(member['img'], width=120) | |
| st.markdown(f"**{member['role']}**") | |
| st.caption(member['desc']) | |
| st.markdown(f"โ๏ธ [{member['email']}](mailto:{member['email']})") | |
| st.markdown(f"๐ผ [LinkedIn]({member['linkedin']})") | |
| st.markdown(f"๐ป [GitHub]({member['github']})") | |
| st.markdown("---") | |
| # Project Overview Section | |
| st.markdown("## ๐ฏ Project Overview") | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.markdown(""" | |
| ### ๐ฅ Video Surgical Scene Understanding | |
| Our project focuses on developing an advanced computer vision system capable of: | |
| - **Scene Analysis**: Understanding surgical environments | |
| - **Tool Recognition**: Identifying medical instruments | |
| - **Workflow Tracking**: Monitoring surgical procedures | |
| - **Real-time Processing**: Immediate analysis and feedback | |
| """) | |
| with col2: | |
| st.markdown(""" | |
| ### ๐ ๏ธ Technical Stack | |
| - **Frontend**: Streamlit Dashboard | |
| - **Backend**: Python | |
| - **ML Models**: SwinUnet, Scene Graphs | |
| - **Dataset**: MM-OR (Multimodal Operating Room) | |
| - **Version**: v1.0 (July 2025) | |
| """) | |
| st.markdown("---") | |
| # Hackathon Achievement Section | |
| st.markdown("## ๐ Hackathon Achievement") | |
| achievement_col1, achievement_col2, achievement_col3 = st.columns(3) | |
| with achievement_col1: | |
| st.metric("Pipeline Version", "v1.0", "Completed") | |
| with achievement_col2: | |
| st.metric("Models Integrated", "2/2", "โ Working") | |
| with achievement_col3: | |
| st.metric("Development Time", "Hackathon", "July 2025") | |
| st.markdown("---") | |
| st.markdown("ยฉ 2025 Team SATOR - ACVSS Hackathon. All Rights Reserved.") | |