87 lines
3.5 KiB
Python
87 lines
3.5 KiB
Python
import base64
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import json
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import logging
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import requests
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from Config.Config import GLM_API_KEY, GLM_MODEL_NAME, GLM_BASE_URL
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# 获取模块专属日志器
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logger = logging.getLogger(__name__)
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def extract_text_from_image(image_path):
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"""
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从图片中提取文字内容（排除几何图形中的文字）
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Args:
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image_path: 图片文件的绝对路径
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Returns:
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str: 提取的文字内容，若失败则返回空字符串
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"""
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try:
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# 读取图片并转换为base64
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with open(image_path, "rb") as image_file:
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base64_image = base64.b64encode(image_file.read()).decode('utf-8')
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image_url = f"data:image/png;base64,{base64_image}"
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# 构建API请求
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# 合并重复的要求字段，使用清晰的编号系统
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prompt = "【任务】提取图像中的数学题文字内容（排除几何图形），用【】包裹结果。"
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#prompt += "【专业术语】需准确识别：将军饮马、动点、等量代换、两点之间线段最短、垂线段最短"
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prompt += "【格式】1. 术语错误需修正；2. 保证句子语法通顺；3. 不添加解释；4. 不包含思考过程"
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url = GLM_BASE_URL
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headers = {
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"Authorization": f"Bearer {GLM_API_KEY}",
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"Content-Type": "application/json"
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}
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data = {
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"model": GLM_MODEL_NAME,
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"messages": [{
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"role": "user",
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"content": [
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{"type": "text", "text": prompt},
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{"type": "image_url", "image_url": {"url": image_url}}
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]
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}],
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"stream": True
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}
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# 发送请求并处理流式响应
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extracted_text = []
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seen_content = set() # 用于去重的集合
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with requests.post(url, headers=headers, json=data, stream=True) as response:
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for chunk in response.iter_lines():
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if chunk:
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decoded = chunk.decode('utf-8')
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if decoded.startswith('[DONE]'):
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logger.info("文字提取完成")
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break
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try:
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# 解析流式响应内容
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json_data = json.loads(decoded[5:]) # 移除""前缀
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content = json_data["choices"][0]["delta"].get('content')
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if content and len(content) > 0 and content not in seen_content:
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seen_content.add(content)
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extracted_text.append(content)
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except Exception as e:
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logger.warning(f"解析响应块失败: {str(e)}")
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# 拼接结果并返回
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return ''.join(extracted_text)
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except FileNotFoundError:
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logger.error(f"图片文件不存在: {image_path}")
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except Exception as e:
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logger.error(f"文字提取失败: {str(e)}", exc_info=True)
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return ""
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# 示例用法
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if __name__ == "__main__":
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# 配置日志（实际项目中应在主程序统一配置）
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logging.basicConfig(level=logging.INFO)
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# 测试图片路径
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#test_image = r"D:\dsWork\dsProject\dsLightRag\Test\extracted\a62dce9d67c818accf94113aabefe172\1_1_TXT.png"
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test_image = r'D:\dsWork\dsProject\dsLightRag\Test\extracted\a62dce9d67c818accf94113aabefe172\1_1_TXT.png'
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# 调用提取函数
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text = extract_text_from_image(test_image)
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print("提取结果:\n", text)
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