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)