基于边缘检测算法检测视频中文字

nlp scapy use

pip install spacy
python -m spacy download zh_core_web_sm
# z中等
python -m spacy download zh-core-web-md
#大语言模型
python -m spacy download zh-core-web-lg
# 插件 支持
pip install "spacy-pkuseg<2.0.0,>=1.0.0" 


# add run 
pip install "spacy-pkuseg>=0.0.27,<0.1.0"
# or
pip uninstall spacy-pkuseg
pip install spacy-pkuseg==1.0.0

# or
pip uninstall spacy zh-core-web-sm spacy-pkuseg
pip install spacy
pip install zh-core-web-sm
pip install "spacy-pkuseg>=1.0.0,<2.0.0"

python -m spacy download en_core_web_sm

use

# english
import spacy

# 加载下载的模型
nlp = spacy.load('en_core_web_sm')

# 处理文本
doc = nlp("Hello, how are you?")
for token in doc:
    print(token.text, token.pos_)


# chinese

import spacy

# 加载中文模型
nlp = spacy.load('zh_core_web_sm')

def extract_dialogue_with_spacy_chinese(text):
    doc = nlp(text)
    dialogues = []
    current_speaker = None
    current_dialogue = []
    
    for sent in doc.sents:
        for ent in sent.ents:
            if ent.label_ == "PERSON":
                # 假设实体标签为“PERSON”表示人物
                if current_speaker:  # 如果之前有一个人物，记录对话
                    dialogues.append((current_speaker, " ".join(current_dialogue)))
                current_speaker = ent.text
                current_dialogue = []
                break  # 跳到下一个句子
        if current_speaker:
            current_dialogue.append(sent.text.strip())
    
    if current_dialogue:
        dialogues.append((current_speaker, " ".join(current_dialogue)))
    
    return dialogues

# 示例文本
script = """
张三: 你好吗？
李四: 我很好，谢谢！
张三: 太好了！
"""

dialogues = extract_dialogue_with_spacy_chinese(script)
for character, line in dialogues:
    print(f"人物: {character}, 对话: {line}")