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# import streamlit as st
# import json
# with open("qwen2vl_50.json", "r") as file:
# qwen_data = json.load(file)
# with open("gpt4o_50.json", "r") as file:
# gpt_data = json.load(file)
# st.title("JSON Data Visualization")
# columns_per_row = 4
# columns = st.columns(columns_per_row)
# for idx, (qwen, gpt) in enumerate(zip(qwen_data, gpt_data)):
# image_name, image_url, description, qwen_category = qwen
# _, _, _, gpt_category = gpt
# col = columns[idx % columns_per_row] # 按列循环分配
# with col:
# st.subheader(f"{image_name}")
# st.image(image_url, caption=description, use_column_width=True)
# st.markdown(f"**Description:** {description}")
# st.markdown(f"**Qwen_Category:** {qwen_category}")
# st.markdown(f"**GPT_Category:** {gpt_category}")
# st.markdown("---")
import streamlit as st
import json
# 加载数据
with open("qwen2vl_50.json", "r") as file:
qwen_data = json.load(file)
with open("gpt4o_50.json", "r") as file:
gpt_data = json.load(file)
st.title("JSON Data Visualization")
columns_per_row = 4
columns = st.columns(columns_per_row)
# 用于存储每列的内容高度
heights = [0] * columns_per_row
content_list = [[] for _ in range(columns_per_row)] # 每列内容占位
# 遍历数据并将内容分配到列
for idx, (qwen, gpt) in enumerate(zip(qwen_data, gpt_data)):
image_name, image_url, description, qwen_category = qwen
_, _, _, gpt_category = gpt
# 将内容添加到对应列的内容列表中
col_idx = idx % columns_per_row
content = f"""
### {image_name}

**Description:** {description}
**Qwen_Category:** {qwen_category}
**GPT_Category:** {gpt_category}
---
"""
content_list[col_idx].append(content)
# 渲染每列内容
for col_idx, col_content in enumerate(content_list):
with columns[col_idx]:
for item in col_content:
st.markdown(item)
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