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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"
path = "./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, cus_sort=True):
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;
background-color: #3C6478 !important; /* Background color for selected items */
color: white; /* Change text color */
back
}
</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_show'] = chart_data['Model'].map(display_model_names)
models = st.multiselect("Please choose the model",
sorted(chart_data['model_show'].tolist()),
default = sorted(chart_data['model_show'].tolist()),
)
chart_data = chart_data[chart_data['model_show'].isin(models)]
chart_data = chart_data.sort_values(by=[new_dataset_name], ascending=cus_sort).dropna(axis=0)
if len(chart_data) == 0:
return
# Get Values
data_values = chart_data.iloc[:, 1]
# Calculate Q1 and Q3
q1 = data_values.quantile(0.25)
q3 = data_values.quantile(0.75)
# Calculate IQR
iqr = q3 - q1
# Define lower and upper bounds (1.5*IQR is a common threshold)
lower_bound = q1 - 1.5 * iqr
upper_bound = q3 + 1.5 * iqr
# Filter data within the bounds
filtered_data = data_values[(data_values >= lower_bound) & (data_values <= upper_bound)]
# Calculate min and max values after outlier handling
min_value = round(filtered_data.min() - 0.1 * filtered_data.min(), 3)
max_value = round(filtered_data.max() + 0.1 * filtered_data.max(), 3)
options = {
#"title": {"text": f"{display_names[folder_name.upper()]}"},
"title": {"text": f"{dataset_name}"},
"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_show'].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('##### Results')
# 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'])}
chart_data['model_link'] = chart_data['model_show'].map(model_link)
chart_data_table = chart_data[['model_show', chart_data.columns[1], chart_data.columns[3]]]
cur_dataset_name = chart_data_table.columns[1]
print(cur_dataset_name)
if cur_dataset_name in [
'librispeech_test_clean',
'librispeech_test_other',
'common_voice_15_en_test',
'peoples_speech_test',
'gigaspeech_test',
'earnings21_test',
'earnings22_test',
'tedlium3_test',
'tedlium3_long_form_test',
'imda_part1_asr_test',
'imda_part2_asr_test',
'aishell_asr_zh_test',
]:
styled_df = chart_data_table.style.highlight_min(
subset=[chart_data_table.columns[1]], color='yellow'
)
else:
chart_data_table = chart_data_table.sort_values(
by=chart_data_table.columns[1],
ascending=False
).reset_index(drop=True)
styled_df = chart_data_table.style.highlight_max(
subset=[chart_data_table.columns[1]], color='yellow'
)
st.dataframe(
styled_df,
column_config={
'model_show': 'Model',
chart_data_table.columns[1]: {'alignment': 'left'},
"model_link": st.column_config.LinkColumn(
"Model Link",
# # # help="",
# validate=r"^https://(.*?)$",
# # max_chars=100,
# display_text=r"\[(.*?)\]"
),
},
hide_index=True,
use_container_width=True
)
# s = ''
# for model in models:
# try:
# # <td align="center"><input type="checkbox" name="select"></td>
# s += f"""<tr>
# <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:80%">
# <thead>
# <tr style="text-align: center;">
# <th style="width:45%">MODEL</th>
# <th style="width:45%">{dataset_name}</th>
# </tr>
# {s}
# </thead>
# </table>
# """
# #<th style="width:10%"><input type="checkbox" onclick="toggle(this);"></th>
# # 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-Test', 'Tedlium3-Long-form-Test']:
pass
else:
show_examples(category_name, dataset_name, chart_data['Model'].tolist(), display_model_names)
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