Spaces:
Sleeping
Sleeping
update app
Browse files- _contributors.py +0 -6
- assets/members_list.txt +0 -0
- config.py +4 -50
- contributors.py +23 -0
- main.py +3 -5
- _model.py → model.py +5 -4
_contributors.py
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@@ -1,6 +0,0 @@
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import streamlit as st
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from config import CONTRIBUTORS
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def contributors_page():
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st.balloons()
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st.write(CONTRIBUTORS, unsafe_allow_html=True)
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assets/members_list.txt
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Binary file (3.88 kB). View file
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config.py
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@@ -75,56 +75,10 @@ CONTRIBUTORS = """
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</table>
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<br>
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<table>
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<
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<
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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<tr>
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<td>John Doe</td>
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<td>John Doe</td>
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<td>John Doe</td>
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</tr>
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</tbody>
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</table>
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</div>
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"""
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</table>
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<br>
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<table>
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<tr>
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<th width="20%" style="font-size: 140%;" colspan="3">Contributors</th>
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</tr>
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{}
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</table>
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</div>
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"""
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contributors.py
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@@ -0,0 +1,23 @@
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import streamlit as st
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from config import CONTRIBUTORS
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def contributors_page():
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st.balloons()
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with open("assets/members_list.txt", "r", encoding="utf-16") as f:
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data = f.readlines()
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full_string = ""
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for i in range(0,len(data),3):
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contributors = f"""<tr>
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<td>{data[i].strip().title()}</td>
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<td>{data[i+1].strip().title()}</td>
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<td>{data[i+2].strip().title()}</td>
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</tr>
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"""
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full_string += contributors
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st.write(CONTRIBUTORS.format(full_string), unsafe_allow_html=True)
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if __name__ == "__main__":
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contributors_page()
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main.py
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@@ -2,8 +2,8 @@ import base64
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import streamlit as st
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from config import *
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from
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from
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st.set_page_config(
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page_title=f"Omdena | Toronto Chapter",
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def main():
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st.sidebar.image("assets/logo.png")
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st.sidebar.write(SIDEBAR_TEXT_1, unsafe_allow_html=True)
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selected_task = st.sidebar.selectbox("Please navigate through the different sections of our website from here", ["Home", "About", "
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st.sidebar.write(SIDEBAR_TEXT_2, unsafe_allow_html=True)
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if selected_task == "Home":
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home_page()
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elif selected_task == "About":
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st.write(ABOUT_US, unsafe_allow_html=True)
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elif selected_task == "Visualization":
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st.write(VISUALIZATION, unsafe_allow_html=True)
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elif selected_task == "Model":
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model_page()
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elif selected_task == "Contributors":
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import streamlit as st
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from config import *
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from model import model_page
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from contributors import contributors_page
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st.set_page_config(
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page_title=f"Omdena | Toronto Chapter",
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def main():
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st.sidebar.image("assets/logo.png")
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st.sidebar.write(SIDEBAR_TEXT_1, unsafe_allow_html=True)
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selected_task = st.sidebar.selectbox("Please navigate through the different sections of our website from here", ["Home", "About", "Model", "Contributors"], label_visibility="hidden")
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st.sidebar.write(SIDEBAR_TEXT_2, unsafe_allow_html=True)
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if selected_task == "Home":
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home_page()
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elif selected_task == "About":
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st.write(ABOUT_US, unsafe_allow_html=True)
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elif selected_task == "Model":
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model_page()
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elif selected_task == "Contributors":
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_model.py → model.py
RENAMED
@@ -3,8 +3,8 @@ import streamlit as st
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from config import API_URL, CLASS_LABELS
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def model_page():
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st.write("####
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uploaded_file = st.file_uploader("Upload
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predict_button = st.button("ㅤㅤPredictㅤㅤ")
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if predict_button and uploaded_file:
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label = CLASS_LABELS[int(result['label'])]
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prob = round(result['probability'], 4)*100
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st.toast("Prediction completed!", icon="🎉")
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elif predict_button and not uploaded_file:
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st.toast("Please upload an
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def predict_image(image):
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files = {'file': image}
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from config import API_URL, CLASS_LABELS
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def model_page():
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st.write("#### Please upload MRI scan here...")
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uploaded_file = st.file_uploader("Upload MRI scan here...", type=["jpg", "png", "jpeg"], label_visibility="hidden")
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predict_button = st.button("ㅤㅤPredictㅤㅤ")
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if predict_button and uploaded_file:
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label = CLASS_LABELS[int(result['label'])]
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prob = round(result['probability'], 4)*100
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# According to our model, there is a 99.97% chance that this scan is from a non demented person.
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result_ele.info(f"""According to our model, there is a **{prob}%** chance that this scan is from a **{label}** person.""")
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st.toast("Prediction completed!", icon="🎉")
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elif predict_button and not uploaded_file:
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st.toast("Please upload an MRI scan first!", icon="⚠️")
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def predict_image(image):
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files = {'file': image}
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