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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| from streamlit_echarts import st_echarts | |
| from streamlit.components.v1 import html | |
| # from PIL import Image | |
| from app.show_examples import * | |
| import pandas as pd | |
| # huggingface_image = Image.open('style/huggingface.jpg') | |
| # other info | |
| path = "./AudioBench-Leaderboard/additional_info/Leaderboard-Rename.xlsx" | |
| info_df = pd.read_excel(path) | |
| # def nav_to(value): | |
| # try: | |
| # url = links_dic[str(value).lower()] | |
| # js = f'window.open("{url}", "_blank").then(r => window.parent.location.href);' | |
| # st_javascript(js) | |
| # except: | |
| # pass | |
| def draw(folder_name, category_name, dataset_name, metrics): | |
| folder = f"./results/{metrics}/" | |
| display_names = { | |
| 'SU': 'Speech Understanding', | |
| 'ASU': 'Audio Scene Understanding', | |
| 'VU': 'Voice Understanding' | |
| } | |
| data_path = f'{folder}/{category_name.lower()}.csv' | |
| chart_data = pd.read_csv(data_path).round(3) | |
| new_dataset_name = dataset_name.replace('-', '_').lower() | |
| chart_data = chart_data[['Model', new_dataset_name]] | |
| st.markdown(""" | |
| <style> | |
| .stMultiSelect [data-baseweb=select] span{ | |
| max-width: 800px; | |
| font-size: 0.9rem; | |
| } | |
| </style> | |
| """, unsafe_allow_html=True) | |
| # remap model names | |
| display_model_names = {key.strip() :val.strip() for key, val in zip(info_df['AudioBench'], info_df['Proper Display Name'])} | |
| chart_data['Model'] = chart_data['Model'].map(display_model_names) | |
| models = st.multiselect("Please choose the model", | |
| chart_data['Model'].tolist(), | |
| default = chart_data['Model'].tolist()) | |
| chart_data = chart_data[chart_data['Model'].isin(models)] | |
| chart_data = chart_data.sort_values(by=[new_dataset_name], ascending=True).dropna(axis=0) | |
| if len(chart_data) == 0: | |
| return | |
| min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1*chart_data.iloc[:, 1::].min().min(), 1) | |
| max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1*chart_data.iloc[:, 1::].max().max(), 1) | |
| options = { | |
| "title": {"text": f"{display_names[folder_name.upper()]}"}, | |
| "tooltip": { | |
| "trigger": "axis", | |
| "axisPointer": {"type": "cross", "label": {"backgroundColor": "#6a7985"}}, | |
| "triggerOn": 'mousemove', | |
| }, | |
| "legend": {"data": ['Overall Accuracy']}, | |
| "toolbox": {"feature": {"saveAsImage": {}}}, | |
| "grid": {"left": "3%", "right": "4%", "bottom": "3%", "containLabel": True}, | |
| "xAxis": [ | |
| { | |
| "type": "category", | |
| "boundaryGap": True, | |
| "triggerEvent": True, | |
| "data": chart_data['Model'].tolist(), | |
| } | |
| ], | |
| "yAxis": [{"type": "value", | |
| "min": min_value, | |
| "max": max_value, | |
| "boundaryGap": True | |
| # "splitNumber": 10 | |
| }], | |
| "series": [{ | |
| "name": f"{dataset_name}", | |
| "type": "bar", | |
| "data": chart_data[f'{new_dataset_name}'].tolist(), | |
| }], | |
| } | |
| events = { | |
| "click": "function(params) { return params.value }" | |
| } | |
| value = st_echarts(options=options, events=events, height="500px") | |
| # if value != None: | |
| # # print(value) | |
| # nav_to(value) | |
| # if value != None: | |
| # highlight_table_line(value) | |
| ''' | |
| Show table | |
| ''' | |
| # st.divider() | |
| with st.container(): | |
| # st.write("") | |
| st.markdown('##### TABLE') | |
| custom_css = """ | |
| """ | |
| st.markdown(custom_css, unsafe_allow_html=True) | |
| model_link = {key.strip(): val for key, val in zip(info_df['Proper Display Name'], info_df['Link'])} | |
| s = '' | |
| for model in models: | |
| try: | |
| s += f"""<tr> | |
| <td align="center"><input type="checkbox" name="select"></td> | |
| <td><a href={model_link[model]}>{model}</a></td> | |
| <td>{chart_data[chart_data['Model'] == model][new_dataset_name].tolist()[0]}</td> | |
| </tr>""" | |
| except: | |
| # print(f"{model} is not in {dataset_name}") | |
| continue | |
| # select all function | |
| select_all_function = """<script> | |
| function toggle(source) { | |
| var checkboxes = document.querySelectorAll('input[type="checkbox"]'); | |
| for (var i = 0; i < checkboxes.length; i++) { | |
| if (checkboxes[i] != source) | |
| checkboxes[i].checked = source.checked; | |
| } | |
| } | |
| </script>""" | |
| st.markdown(f""" | |
| <div class="select_all">{select_all_function}</div> | |
| """, unsafe_allow_html=True) | |
| info_body_details = f""" | |
| <table style="width:100%"> | |
| <thead> | |
| <tr style="text-align: center;"> | |
| <th style="width:10%"><input type="checkbox" onclick="toggle(this);"></th> | |
| <th style="width:45%">MODEL</th> | |
| <th style="width:45%">{dataset_name}</th> | |
| </tr> | |
| {s} | |
| </thead> | |
| </table> | |
| """ | |
| # html_code = custom_css + select_all_function + info_body_details | |
| # html(html_code, height = 300) | |
| st.markdown(f""" | |
| <div class="my-data-table">{info_body_details}</div> | |
| """, unsafe_allow_html=True) | |
| # st.dataframe(chart_data, | |
| # # column_config = { | |
| # # "Link": st.column_config.LinkColumn( | |
| # # display_text= st.image(huggingface_image) | |
| # # ), | |
| # # }, | |
| # hide_index = True, | |
| # use_container_width=True) | |
| ''' | |
| show samples | |
| ''' | |
| if dataset_name in ['Earnings21-Test', 'Earnings22-Test', 'Tedlium3-Long-form-Test']: | |
| pass | |
| else: | |
| show_examples(category_name, dataset_name, chart_data['Model'].tolist()) | |