177 lines
7.4 KiB
Python
177 lines
7.4 KiB
Python
import gradio as gr
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import os
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from te_u.arxiv import get_news_from_arxiv
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#
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# os.environ['http_proxy'] = '127.0.0.1:7890'
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# os.environ['https_proxy'] = '127.0.0.1:7890'
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from utils import get_news, get_clouds
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from gradio_pdf import PDF
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current_pdf_file = None
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news = []
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choose_news = []
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=20):
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gr.HTML("""<h1 align="center" id="space-title" style="font-size:35px;">科研情报</h1>""")
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with gr.Column(scale=1, min_width=100):
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gr.HTML(
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"""<h5 align="center"> </h5> """
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)
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gr.HTML(
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"""<h5 align="center"> Created by 朱瑞</h5> """
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)
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with gr.Tabs(elem_classes="tab-buttons") as tabs:
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with gr.TabItem("科研文献分析"):
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with gr.Row():
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with gr.Accordion("文献采集区", open=True, ) as area_news_get_fn:
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keywords = gr.Dropdown(choices=["对抗攻击", "knowledge graph", "认知智能与先进计算", "电磁空间感知与利用", "信息安全与攻防博弈"],
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value="对抗攻击", label="关键词", show_label=True)
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source = gr.Dropdown(choices=["知网", "arxiv"], value="知网", label="数据源", show_label=True)
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num = gr.Slider(1, 100, value=10, label="采集条数", step=1)
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news_get = gr.Button("获取论文", variant='primary')
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with gr.Row():
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with gr.Accordion("文献标记分析区", open=True, elem_id="news-panel") as news_get_fn:
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chosen_news = gr.CheckboxGroup(choices=[item['name'] for item in news], label="需要进行操作的文献")
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with gr.Row():
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news_mark = gr.Button("标记文献")
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news_all_mark = gr.Button("全部标记", variant='primary')
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def recover_news_by_choose(news_titles):
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select_news = []
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global news
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for news_title in news_titles:
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for i in news:
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if news_title == i['name']:
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new_i = i
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select_news.append(new_i)
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break
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return select_news
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def mark_new(titles):
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global choose_news
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mark_news = recover_news_by_choose(titles)
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choose_news = mark_news
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def get_news_temp(num, keywords, source):
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""" 获取临时的文献 """
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global news
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results = []
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if source == "知网":
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results = get_news(num, keywords)
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elif source == "arxiv":
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results = get_news_from_arxiv(num, keywords)
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news.extend(results)
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return gr.CheckboxGroup(choices=[item['name'] for item in news], label="需要进行操作的文献")
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def mark_all_new():
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global news
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global choose_news
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choose_news = news
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return gr.CheckboxGroup(choices=[item['name'] for item in news], value=[item['name'] for item in news], label="需要进行操作的文献")
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news_get.click(get_news_temp, inputs=[num, keywords, source], outputs=[chosen_news])
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news_mark.click(mark_new, inputs=[chosen_news])
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news_all_mark.click(mark_all_new, outputs=[chosen_news])
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with gr.TabItem("科研文献获取"):
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with gr.Row():
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with gr.Accordion("功能区", open=True, ) as area_news_analyse_fn:
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with gr.Row():
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ci_yun_by_title = gr.Button("题目词云", variant='primary')
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ci_yun_by_abstract = gr.Button("摘要词云", variant='primary')
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with gr.Row():
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with gr.Accordion("结果展示区", open=True, ) as area_news_result_fn:
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result_place = gr.Image()
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def g_ci_yun_by_title():
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global choose_news
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word_list = [c["name"] for c in choose_news]
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pic = get_clouds(word_list)
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return pic
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def g_ci_yun_by_abstract():
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global choose_news
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word_list = [c["abstract"] for c in choose_news]
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pic = get_clouds(word_list)
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return pic
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ci_yun_by_title.click(g_ci_yun_by_title, outputs=[result_place])
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ci_yun_by_abstract.click(g_ci_yun_by_abstract, outputs=[result_place])
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with gr.TabItem("会议论文查看"):
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with gr.Row():
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with gr.Column(scale=1):
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with gr.Row():
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# gr.Label("会议名称")
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conf_name = gr.Dropdown(choices=["ECCV2022", "ECCV2020", "CVPR2024"], value="ECCV2022", label="会议名称", show_label=True)
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conf_button = gr.Button("查看会议论文", variant='primary')
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dataframe = gr.Dataframe(headers=["论文名称"], col_count=(1, "fixed"), type='array', height=800)
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with gr.Row():
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look_input = gr.Textbox(placeholder="关键词检索", label="关键词过滤")
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filter_button = gr.Button("过滤")
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# up_button = gr.Button("加载")
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with gr.Column(scale=2):
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pdf = PDF(label="Upload a PDF", interactive=True, height=1000)
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# name = gr.Textbox(show_label=False)
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# pdf.upload(lambda f: f, pdf, name)
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def up_load():
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global current_pdf_file
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n = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper\3d-siamese-transformer-network-for-single-object-tracking-on-point-clouds_ECCV_2022.pdf"
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current_pdf_file = n
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return n
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def load_conf_list(conf_name):
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if conf_name == "ECCV2022":
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root_dir = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper"
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return [[i] for i in os.listdir(root_dir)]
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def look_dataframe(evt: gr.SelectData):
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global current_pdf_file
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if evt.value:
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root_dir = r"D:\py\keyan_qingbao\te_u\paper_down_load\ECCV_2022\main_paper"
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n = os.path.join(root_dir, evt.value)
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if os.path.exists(n):
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current_pdf_file = n
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return current_pdf_file
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def filter_by_word(words, paper_list):
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word_list = words.strip().split()
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paper_list_filter = [p[0] for p in paper_list]
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for word in word_list:
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paper_list_filter = [p for p in paper_list_filter if word in p]
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return [[p] for p in paper_list_filter]
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filter_button.click(filter_by_word, inputs=[look_input, dataframe], outputs=[dataframe])
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dataframe.select(look_dataframe, inputs=None, outputs=[pdf])
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conf_button.click(load_conf_list, inputs=[conf_name], outputs=[dataframe])
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# up_button.click(up_load, inputs=None, outputs=[pdf])s
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if __name__ == '__main__':
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demo.queue().launch(inbrowser=True, server_name='127.0.0.1', server_port=23223)
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