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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 | |
| links_dic = {"random": "https://seaeval.github.io/", | |
| "meta_llama_3_8b": "https://huggingface.co/meta-llama/Meta-Llama-3-8B", | |
| "mistral_7b_instruct_v0_2": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2", | |
| "sailor_0_5b": "https://huggingface.co/sail/Sailor-0.5B", | |
| "sailor_1_8b": "https://huggingface.co/sail/Sailor-1.8B", | |
| "sailor_4b": "https://huggingface.co/sail/Sailor-4B", | |
| "sailor_7b": "https://huggingface.co/sail/Sailor-7B", | |
| "sailor_0_5b_chat": "https://huggingface.co/sail/Sailor-0.5B-Chat", | |
| "sailor_1_8b_chat": "https://huggingface.co/sail/Sailor-1.8B-Chat", | |
| "sailor_4b_chat": "https://huggingface.co/sail/Sailor-4B-Chat", | |
| "sailor_7b_chat": "https://huggingface.co/sail/Sailor-7B-Chat", | |
| "sea_mistral_highest_acc_inst_7b": "https://seaeval.github.io/", | |
| "meta_llama_3_8b_instruct": "https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct", | |
| "flan_t5_base": "https://huggingface.co/google/flan-t5-base", | |
| "flan_t5_large": "https://huggingface.co/google/flan-t5-large", | |
| "flan_t5_xl": "https://huggingface.co/google/flan-t5-xl", | |
| "flan_t5_xxl": "https://huggingface.co/google/flan-t5-xxl", | |
| "flan_ul2": "https://huggingface.co/google/flan-t5-ul2", | |
| "flan_t5_small": "https://huggingface.co/google/flan-t5-small", | |
| "mt0_xxl": "https://huggingface.co/bigscience/mt0-xxl", | |
| "seallm_7b_v2": "https://huggingface.co/SeaLLMs/SeaLLM-7B-v2", | |
| "gpt_35_turbo_1106": "https://openai.com/blog/chatgpt", | |
| "meta_llama_3_70b": "https://huggingface.co/meta-llama/Meta-Llama-3-70B", | |
| "meta_llama_3_70b_instruct": "https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct", | |
| "sea_lion_3b": "https://huggingface.co/aisingapore/sea-lion-3b", | |
| "sea_lion_7b": "https://huggingface.co/aisingapore/sea-lion-7b", | |
| "qwen1_5_110b": "https://huggingface.co/Qwen/Qwen1.5-110B", | |
| "qwen1_5_110b_chat": "https://huggingface.co/Qwen/Qwen1.5-110B-Chat", | |
| "llama_2_7b_chat": "https://huggingface.co/meta-llama/Llama-2-7b-chat-hf", | |
| "gpt4_1106_preview": "https://openai.com/blog/chatgpt", | |
| "gemma_2b": "https://huggingface.co/google/gemma-2b", | |
| "gemma_7b": "https://huggingface.co/google/gemma-7b", | |
| "gemma_2b_it": "https://huggingface.co/google/gemma-2b-it", | |
| "gemma_7b_it": "https://huggingface.co/google/gemma-7b-it", | |
| "qwen_1_5_7b": "https://huggingface.co/Qwen/Qwen1.5-7B", | |
| "qwen_1_5_7b_chat": "https://huggingface.co/Qwen/Qwen1.5-7B-Chat", | |
| "sea_lion_7b_instruct": "https://huggingface.co/aisingapore/sea-lion-7b-instruct", | |
| "sea_lion_7b_instruct_research": "https://huggingface.co/aisingapore/sea-lion-7b-instruct-research", | |
| "LLaMA_3_Merlion_8B": "https://seaeval.github.io/", | |
| "LLaMA_3_Merlion_8B_v1_1": "https://seaeval.github.io/"} | |
| 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, sorted): | |
| folder = f"./results/{folder_name}/" | |
| display_names = { | |
| 'ASR': 'Automatic Speech Recognition', | |
| 'SQA': 'Speech Question Answering', | |
| 'SI': 'Speech Instruction', | |
| 'AC': 'Audio Captioning', | |
| 'ASQA': 'Audio Scene Question Answering', | |
| 'AR': 'Accent Recognition', | |
| 'GR': 'Gender Recognition', | |
| 'ER': 'Emotion Recognition' | |
| } | |
| data_path = f'{folder}/{category_name.lower()}.csv' | |
| chart_data = pd.read_csv(data_path).round(2).dropna(axis=0) | |
| if len(chart_data) == 0: | |
| return | |
| if sorted == 'Ascending': | |
| ascend = True | |
| else: | |
| ascend = False | |
| sort_by = dataset_name.replace('-', '_').lower() | |
| chart_data = chart_data.sort_values(by=[sort_by], ascending=ascend) | |
| min_value = round(chart_data.iloc[:, 1::].min().min() - 0.1, 1) | |
| max_value = round(chart_data.iloc[:, 1::].max().max() + 0.1, 1) | |
| columns = list(chart_data.columns)[1:] | |
| series = [] | |
| for col in columns: | |
| series.append( | |
| { | |
| "name": f"{col.replace('_', '-')}", | |
| "type": "line", | |
| "data": chart_data[f'{col}'].tolist(), | |
| } | |
| ) | |
| options = { | |
| "title": {"text": f"{display_names[category_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": False, | |
| "triggerEvent": True, | |
| "data": chart_data['Model'].tolist(), | |
| } | |
| ], | |
| "yAxis": [{"type": "value", | |
| "min": min_value, | |
| "max": max_value, | |
| # "splitNumber": 10 | |
| }], | |
| "series": series, | |
| } | |
| 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) | |
| ### create table | |
| st.divider() | |
| # 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) | |