| import streamlit as st | |
| import torch | |
| def main(): | |
| st.set_page_config( | |
| page_title="Hello", | |
| page_icon="🧬", | |
| layout="wide", | |
| ) | |
| st.write("# Welcome to DN-AI! 👋") | |
| st.write( | |
| "This is a web application for the DN-AI project, which aims to provide an easy-to-use interface for analyzing and processing fiber images." | |
| ) | |
| st.write("## Features") | |
| st.write( | |
| "- **Image loading**: The application accepts CZI file, jpeg and PNG file. \n" | |
| "- **Image segmentation**: The application provides a set of tools to segment the DNA fiber and measure the ratio between analogs. \n" | |
| ) | |
| st.write("## Technical details") | |
| cols = st.columns(2) | |
| with cols[0]: | |
| st.write("### Source") | |
| st.write("The source code for this application is available on GitHub.") | |
| """ | |
| [](https://github.com/ClementPla/DeepFiberQ/tree/relabelled) | |
| """ | |
| st.markdown("<br>", unsafe_allow_html=True) | |
| with cols[1]: | |
| st.write("### Device ") | |
| st.write("If available, the application will try to use a GPU for processing.") | |
| device = "GPU" if torch.cuda.is_available() else "CPU" | |
| cols = st.columns(3) | |
| with cols[0]: | |
| st.write("Running on:") | |
| with cols[1]: | |
| st.button(device, icon="⚙️", disabled=True) | |
| if not torch.cuda.is_available(): | |
| with cols[2]: | |
| st.warning("The application will run on CPU, which may be slower.") | |
| if __name__ == "__main__": | |
| main() | |