utils/eval_users.py

import streamlit as st 
import os  
ROOT_FIG_DIR = f'{os.getcwd()}/figures/'

def get_product_dev_page_layout():
    # row6_1, row6_2, = st.columns((1,1))
    row6_1, row6_2,row6_3 = st.tabs(["Evaluation Metrics", "Performance Evaluation", "Issues and Limitations"])

    with row6_1:
        # st.write("**Performance Metrics**")
        st.subheader('Performance Metrics')
        st.write('Following metrics are used for evaluation:')
        st.image(f'{ROOT_FIG_DIR}/evaluation_template.png')
        list_test = """<ul>
                        <li><strong>Accuracy: </strong>it is a ratio of correctly predicted observation to the total observations..</li>
                    </ul>"""
        st.markdown(list_test, unsafe_allow_html=True)
        # st.latex(r''' Accuracy=\frac{TP + TN}{TP+TN+FP+FN}''')
        list_test = """<ul>
                        <li><strong>Precision: </strong>It is the ratio of correctly predicted positive observations to the total predicted positive observations</li>
                    </ul>"""
        st.markdown(list_test, unsafe_allow_html=True)
        # st.latex(r''' Precision=\frac{TP}{TP+FP}''')
        list_test = """<ul>
                        <li><strong>Recall: </strong>It is the ratio of correctly predicted positive observations to the all observations in actual class.</li>
                    </ul>"""
        st.markdown(list_test, unsafe_allow_html=True)
        # st.latex(r''' Recall=\frac{TP}{TP+FN}''')
        # with st.expander('Test Set Confusion Matrix'):
        #     # st.caption('Test Set Results:')
        #     st.image('./figures/test_confmat_20210404.png')

    with row6_2:
        # st.write("**Prediction Samples**")
        # with st.expander('Test Set Confusion Matrix'):
        #     # st.caption('Test Set Results:')
        st.subheader('Test Set Confusion Matrix')
        st.image(f'{ROOT_FIG_DIR}/test_confmat_20210404.png')
        st.subheader('Prediction Samples')
        st.caption('Correctly Classified sample predictions:')
        st.image(f'{ROOT_FIG_DIR}/pred_stats.png')

        st.caption('Miss Classified sample predictions:')
        st.image(f'{ROOT_FIG_DIR}/pred_stats.png')

        st.subheader("Class-wise Prediction Distributions")
        st.image(f'{ROOT_FIG_DIR}/training_prob_stats.png')