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import base64
import io
from PIL import Image
import gradio as gr
import pandas as pd
def decode_image(base64_str):
try:
img_data = base64.b64decode(base64_str)
img = Image.open(io.BytesIO(img_data))
return img
except:
return None
def display_sample(df, idx):
sample = df.iloc[idx]
title = sample['title']
description = sample['description']
label = "广告" if sample['label'] == 1 else "非广告"
date = sample['date']
comments = sample['comments'] if 'comments' in sample else []
images = []
for img_b64 in sample['images']:
img = decode_image(img_b64)
if img:
images.append(img)
return title, description, label, date, comments, images
def create_demo(df):
with gr.Blocks() as demo:
gr.Markdown("# RedNote Covert Advertisement Detection Dataset Viewer")
with gr.Row():
with gr.Column(scale=1):
idx_slider = gr.Slider(minimum=0, maximum=len(df)-1, step=1, value=0, label="Sample Index")
label_filter = gr.Radio(["全部", "仅广告", "仅非广告"], value="全部", label="筛选")
def update_slider(choice):
if choice == "仅广告":
ad_indices = df[df['label'] == 1].index.tolist()
return gr.Slider(minimum=0, maximum=len(ad_indices)-1, step=1, value=0)
elif choice == "仅非广告":
non_ad_indices = df[df['label'] == 0].index.tolist()
return gr.Slider(minimum=0, maximum=len(non_ad_indices)-1, step=1, value=0)
else:
return gr.Slider(minimum=0, maximum=len(df)-1, step=1, value=0)
label_filter.change(update_slider, inputs=[label_filter], outputs=[idx_slider])
with gr.Column(scale=3):
title_text = gr.Textbox(label="标题")
desc_text = gr.Textbox(label="描述", lines=5)
label_text = gr.Textbox(label="标签")
date_text = gr.Textbox(label="日期")
comments_text = gr.Textbox(label="评论", lines=5)
image_gallery = gr.Gallery(label="图片", columns=3, height=400)
def get_filtered_index(idx, filter_choice):
if filter_choice == "仅广告":
ad_indices = df[df['label'] == 1].index.tolist()
return ad_indices[idx]
elif filter_choice == "仅非广告":
non_ad_indices = df[df['label'] == 0].index.tolist()
return non_ad_indices[idx]
else:
return idx
def update_display(idx, filter_choice):
real_idx = get_filtered_index(idx, filter_choice)
return display_sample(df, real_idx)
idx_slider.change(
update_display,
inputs=[idx_slider, label_filter],
outputs=[title_text, desc_text, label_text, date_text, comments_text, image_gallery]
)
# 初始显示第一个样本
title, desc, label, date, comments, images = display_sample(df, 0)
title_text.value = title
desc_text.value = desc
label_text.value = label
date_text.value = date
comments_text.value = "\n".join(comments) if comments else ""
image_gallery.value = images
return demo
# 加载数据集
def load_dataset():
try:
train_df = pd.read_parquet("train.parquet")
val_df = pd.read_parquet("validation.parquet")
test_df = pd.read_parquet("test.parquet")
return pd.concat([train_df, val_df, test_df])
except:
# 如果加载失败，返回一个示例数据框
return pd.DataFrame({
'title': ['示例标题'],
'description': ['这是一个示例描述'],
'label': [0],
'date': ['01-01'],
'comments': [['评论1', '评论2']],
'images': [['']] # 空图片
})
# 创建演示
df = load_dataset()
demo = create_demo(df)
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