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import streamlit as st
import pandas as pd
import json
import numpy as np
# 读取 JSON 数据
with open('GenAI-Bench_tags.json', 'r') as file:
data = json.load(file)
with open('genai_image.json', 'r') as file:
humanRatings = json.load(file)
# Streamlit 页面标题
st.set_page_config(page_title="GenAI-Bench Dataset Viewer", page_icon=None, layout="wide", initial_sidebar_state="auto",
menu_items=None)
st.title('GenAI-Bench Dataset Viewer')
# 多选框
basic_options = []
advanced_options = []
for i in data:
data[i]['basic'].sort()
data[i]['advanced'].sort()
for basic in data[i]['basic']:
if basic not in basic_options:
basic_options.append(basic)
for adv in data[i]['advanced']:
if adv not in advanced_options:
advanced_options.append(adv)
data[i]['id'] = i
# modles = ["DALLE_3","DeepFloyd_I_XL_v1","Midjourney_6","SDXL_2_1","SDXL_Base","SDXL_Turbo"]
data[i]['DALLE_3'] = f"app/static/DALLE_3/{i}.jpeg"
data[i]['DeepFloyd_I_XL_v1'] = f"app/static/DeepFloyd_I_XL_v1/{i}.jpeg"
data[i]['Midjourney_6'] = f"app/static/Midjourney_6/{i}.jpeg"
data[i]['SDXL_2_1'] = f"app/static/SDXL_2_1/{i}.jpeg"
data[i]['SDXL_Base'] = f"app/static/SDXL_Base/{i}.jpeg"
data[i]['SDXL_Turbo'] = f"app/static/SDXL_Turbo/{i}.jpeg"
data[i]['DALLE_3_Human'] = round(np.mean(humanRatings[i]["models"]["DALLE_3"]), 1)
data[i]['DeepFloyd_I_XL_v1_Human'] = round(np.mean(humanRatings[i]["models"]["DeepFloyd_I_XL_v1"]), 1)
data[i]['Midjourney_6_Human'] = round(np.mean(humanRatings[i]["models"]["Midjourney_6"]), 1)
data[i]['SDXL_2_1_Human'] = round(np.mean(humanRatings[i]["models"]["SDXL_2_1"]), 1)
data[i]['SDXL_Base_Human'] = round(np.mean(humanRatings[i]["models"]["SDXL_Base"]), 1)
data[i]['SDXL_Turbo_Human'] = round(np.mean(humanRatings[i]["models"]["SDXL_Turbo"]), 1)
selected_basic = st.multiselect('Select Basic Skills:', basic_options)
selected_advanced = st.multiselect('Select Advanced Skills:', advanced_options)
# 筛选数据
filtered_data = [
data[item] for item in data
if all(elem in data[item]['basic'] for elem in selected_basic) and
all(advanced in data[item]['advanced'] for advanced in selected_advanced)
]
# 显示筛选后的数据
if filtered_data:
df = pd.DataFrame(filtered_data)
df = df.reindex(columns=["id", "prompt", "basic", "advanced", "DALLE_3", "DALLE_3_Human", "DeepFloyd_I_XL_v1",
"DeepFloyd_I_XL_v1_Human", "Midjourney_6", "Midjourney_6_Human", "SDXL_2_1",
"SDXL_2_1_Human", "SDXL_Base", "SDXL_Base_Human", "SDXL_Turbo", "SDXL_Turbo_Human"])
st.dataframe(data=df, width = 4096, height = 800,
column_config={
"name": "Data Explorer",
"id": st.column_config.NumberColumn("ID", format="%d", width="small"),
'basic': st.column_config.ListColumn(label="Basic Skills", width="large", help=None),
'advanced': st.column_config.ListColumn(label="Advanced Skills", width="large", help=None),
'prompt': st.column_config.TextColumn(label="Prompt", width="large", help=None, disabled=None,
required=None,
default=None, max_chars=None, validate=None),
"DALLE_3": st.column_config.ImageColumn(label="DALLE_3", width="small", help=None),
"DALLE_3_Human": st.column_config.NumberColumn("Rating Human", format="%.1f", width="small", help="Rating Human for DALLE_3"),
"DeepFloyd_I_XL_v1": st.column_config.ImageColumn(label="DeepFloyd", width="small",
help="DeepFloyd_I_XL_v1"),
"DeepFloyd_I_XL_v1_Human": st.column_config.NumberColumn("Rating Human", format="%.1f",
width="small", help="Rating Human for DeepFloyd"),
"Midjourney_6": st.column_config.ImageColumn(label="Midjourney", width="small", help="Midjourney_6"),
"Midjourney_6_Human": st.column_config.NumberColumn("Rating Human", format="%.1f",
width="small", help="Rating Human for Midjourney_6"),
"SDXL_2_1": st.column_config.ImageColumn(label="SDXL_2_1", width="small", help=None),
"SDXL_2_1_Human": st.column_config.NumberColumn("Rating Human", format="%.1f", width="small", help="Rating Human for SDXL_2_1"),
"SDXL_Base": st.column_config.ImageColumn(label="SDXL_Base", width="small", help=None),
"SDXL_Base_Human": st.column_config.NumberColumn("Rating Human", format="%.1f", width="small", help="Rating Human for SDXL_Base"),
"SDXL_Turbo": st.column_config.ImageColumn(label="SDXL_Turbo", width="small", help=None),
"SDXL_Turbo_Human": st.column_config.NumberColumn("Rating Human", format="%.1f", width="small", help="Rating Human for SDXL_Turbo"),
},
hide_index=True, selection_mode="single-row")
else:
st.write("No data matches the selected filters.")
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