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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| from streamlit_echarts import st_echarts | |
| # from streamlit_echarts import JsCode | |
| from streamlit_javascript import st_javascript | |
| # from PIL import Image | |
| from app.show_examples import * | |
| links_dic = {} | |
| links_dic = {k.lower().replace('_', '-') : v for k, v in links_dic.items()} | |
| # huggingface_image = Image.open('style/huggingface.jpg') | |
| 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(2) | |
| # if sorted == 'Ascending': | |
| # ascend = True | |
| # else: | |
| # ascend = False | |
| new_dataset_name = dataset_name.replace('-', '_').lower() | |
| chart_data = chart_data[['Model', new_dataset_name]] | |
| 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, 1) | |
| max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 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": False, | |
| "triggerEvent": True, | |
| "data": chart_data['Model'].tolist(), | |
| } | |
| ], | |
| "yAxis": [{"type": "value", | |
| "min": min_value, | |
| "max": max_value, | |
| # "splitNumber": 10 | |
| }], | |
| "series": [{ | |
| "name": f"{dataset_name}", | |
| "type": "line", | |
| "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.expander('TABLE'): | |
| # chart_data['Link'] = chart_data['Model'].map(links_dic) | |
| 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 | |
| ''' | |
| show_examples(category_name, dataset_name, chart_data['Model'].tolist()) | |