| import streamlit as st |
| from streamlit import session_state as session |
|
|
| from PIL import Image |
|
|
| class TeethApp: |
| def __init__(self): |
| |
| with open("utils/style.css") as css: |
| st.markdown(f"<style>{css.read()}</style>", unsafe_allow_html=True) |
| |
| |
| self.image_path = "utils/teeth-295404_1280.png" |
| self.image = Image.open(self.image_path) |
| width, height = self.image.size |
| scale = 12 |
| new_width, new_height = width / scale, height / scale |
| self.image = self.image.resize((int(new_width), int(new_height))) |
|
|
| |
| st.sidebar.markdown("# AI ToothSeg") |
| st.sidebar.markdown("Automatic teeth segmentation with Deep Learning") |
| st.sidebar.markdown(" ") |
| st.sidebar.image(self.image, use_column_width=False) |
| st.markdown( |
| """ |
| <style> |
| .css-1bxukto { |
| background-color: rgb(255, 255, 255) ;""", |
| unsafe_allow_html=True, |
| ) |
|
|
| |
| st.set_page_config(page_title="Teeth Segmentation", page_icon="ⓘ") |
|
|
| class Intro(TeethApp): |
| def __init__(self): |
| TeethApp.__init__(self) |
| self.build_app() |
|
|
| def build_app(self): |
| st.title("AI-assited Tooth Segmentation") |
| st.markdown("This app automatically segments intra-oral scans of teeth using machine learning.") |
| st.markdown("Head to the 'Segment' tab to try it out!") |
| st.markdown("**Example:**") |
| st.image("illustration.png") |
|
|
| if __name__ == "__main__": |
| app = Intro() |