c6ab72cd5b
- 更新 .gitignore，忽略本地文件。 - 调整 docker-compose.yml，优化服务配置及端口设置。 - api.Dockerfile 更换为基于 NVIDIA CUDA 的镜像，支持 GPU。 - pyproject.toml 新增依赖 langchain-tavily，并升级 mineru。 - tools_factory.py 重构，采用 langchain_tavily 的 TavilySearch。 - knowledgebase.py 增强 Milvus 连接异常的错误日志。 - _ocr.py 中 OCRPlugin 升级，使用 mineru 新解析方法，并调整健康检查 URL。 - 新增 mineru.py，实现文档解析逻辑。 - logging_config.py 优化日志配置，采用 loguru 管理日志。 - DataBaseInfoView.vue 新增分块参数配置及文件上传相关弹窗和功能。
205 lines
7.0 KiB
Python
205 lines
7.0 KiB
Python
import os
|
||
import uuid
|
||
from pathlib import Path
|
||
from argparse import ArgumentParser
|
||
|
||
import fitz # fitz就是pip install PyMuPDF
|
||
import numpy as np # Added import for numpy
|
||
from PIL import Image
|
||
from tqdm import tqdm
|
||
from rapidocr_onnxruntime import RapidOCR
|
||
|
||
from src.utils import logger, is_text_pdf
|
||
|
||
|
||
GOLBAL_STATE = {}
|
||
|
||
|
||
class OCRPlugin:
|
||
"""OCR 插件"""
|
||
|
||
def __init__(self, **kwargs):
|
||
self.ocr = None
|
||
self.det_box_thresh = kwargs.get('det_box_thresh', 0.3)
|
||
|
||
def load_model(self):
|
||
"""加载 OCR 模型"""
|
||
logger.info("加载 OCR 模型，仅在第一次调用时加载")
|
||
model_dir = os.path.join(os.getenv("MODEL_DIR", ""), "SWHL/RapidOCR")
|
||
det_model_dir = os.path.join(model_dir, "PP-OCRv4/ch_PP-OCRv4_det_infer.onnx")
|
||
rec_model_dir = os.path.join(model_dir, "PP-OCRv4/ch_PP-OCRv4_rec_infer.onnx")
|
||
assert os.path.exists(model_dir), (
|
||
f"模型文件不存在，请下载 SWHL/RapidOCR 到 {model_dir}，"
|
||
"并确认是否在 docker-compose.dev.yml 中添加 MODEL_DIR 环境变量"
|
||
)
|
||
self.ocr = RapidOCR(det_box_thresh=0.3, det_model_path=det_model_dir, rec_model_path=rec_model_dir)
|
||
logger.info(f"OCR Plugin for det_box_thresh = {self.det_box_thresh} loaded.")
|
||
|
||
def process_image(self, image):
|
||
"""
|
||
对单张图像执行OCR并提取文本
|
||
|
||
Args:
|
||
image: 图像数据，支持多种格式：
|
||
- str: 图像文件路径
|
||
- PIL.Image: PIL图像对象
|
||
- numpy.ndarray: numpy图像数组
|
||
|
||
Returns:
|
||
str: 提取的文本内容
|
||
"""
|
||
# 确保模型已加载
|
||
if self.ocr is None:
|
||
self.load_model()
|
||
|
||
# 处理不同类型的输入图像
|
||
try:
|
||
if isinstance(image, str):
|
||
# 图像路径直接传递给OCR处理
|
||
image_path = image
|
||
is_temp_file = False
|
||
else:
|
||
# 创建临时文件
|
||
is_temp_file = True
|
||
image_path = self._create_temp_image_file(image)
|
||
|
||
# 执行 OCR
|
||
result, _ = self.ocr(image_path)
|
||
|
||
# 清理临时文件
|
||
if is_temp_file and os.path.exists(image_path):
|
||
os.remove(image_path)
|
||
|
||
# 提取文本
|
||
if result:
|
||
text = '\n'.join([line[1] for line in result])
|
||
return text
|
||
else:
|
||
logger.warning("OCR未能识别出文本内容")
|
||
return ""
|
||
|
||
except Exception as e:
|
||
logger.error(f"OCR处理失败: {str(e)}")
|
||
raise
|
||
|
||
def _create_temp_image_file(self, image):
|
||
"""
|
||
将图像数据保存为临时文件
|
||
|
||
Args:
|
||
image: PIL.Image或numpy.ndarray格式的图像数据
|
||
|
||
Returns:
|
||
str: 临时文件路径
|
||
"""
|
||
# 为临时文件创建目录（如果不存在）
|
||
tmp_dir = os.path.join(os.getcwd(), 'tmp')
|
||
os.makedirs(tmp_dir, exist_ok=True)
|
||
|
||
# 生成临时文件路径
|
||
temp_filename = f'ocr_temp_{uuid.uuid4().hex[:8]}.png'
|
||
image_path = os.path.join(tmp_dir, temp_filename)
|
||
|
||
# 根据图像类型保存文件
|
||
if isinstance(image, Image.Image):
|
||
# 保存PIL图像对象到临时文件
|
||
image.save(image_path)
|
||
elif isinstance(image, np.ndarray):
|
||
# 将numpy数组转换为PIL图像并保存
|
||
Image.fromarray(image).save(image_path)
|
||
else:
|
||
raise ValueError("不支持的图像类型，必须是PIL.Image或numpy数组")
|
||
|
||
return image_path
|
||
|
||
def process_pdf(self, pdf_path):
|
||
"""
|
||
处理PDF文件并提取文本
|
||
:param pdf_path: PDF文件路径
|
||
:return: 提取的文本
|
||
"""
|
||
|
||
if not os.path.exists(pdf_path):
|
||
raise FileNotFoundError(f"PDF file not found: {pdf_path}")
|
||
|
||
try:
|
||
# 检查是否为文本PDF，可能会出现错误，比如每一页都有可读取的水印文字，但是内容本身是扫描件，需要使用OCR处理
|
||
# if is_text_pdf(pdf_path):
|
||
# from src.core.indexing import pdfreader
|
||
# logger.info("PDF file is text, use llama_index.readers.file to read")
|
||
# return pdfreader(pdf_path)
|
||
|
||
images = []
|
||
|
||
pdfDoc = fitz.open(pdf_path)
|
||
totalPage = pdfDoc.page_count
|
||
for pg in tqdm(range(totalPage), desc='to images', ncols=100):
|
||
page = pdfDoc[pg]
|
||
rotate, zoom_x, zoom_y = 0, 2, 2
|
||
mat = fitz.Matrix(zoom_x, zoom_y).prerotate(rotate)
|
||
pix = page.get_pixmap(matrix=mat, alpha=False)
|
||
img_pil = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
|
||
images.append(img_pil)
|
||
|
||
# 处理每个图像并合并文本
|
||
all_text = []
|
||
for img_path in tqdm(images, desc='to txt', ncols=100):
|
||
text = self.process_image(img_path)
|
||
all_text.append(text)
|
||
|
||
return '\n\n'.join(all_text)
|
||
|
||
except Exception as e:
|
||
logger.error(f"PDF processing error: {str(e)}")
|
||
return ""
|
||
|
||
def process_pdf_mineru(self, pdf_path):
|
||
"""
|
||
使用Mineru OCR处理PDF文件
|
||
:param pdf_path: PDF文件路径
|
||
:return: 提取的文本
|
||
"""
|
||
mineru_ocr_uri = os.getenv("MINERU_OCR_URI", "http://localhost:30000")
|
||
mineru_ocr_uri_health = f"{mineru_ocr_uri}/health"
|
||
import requests
|
||
import json
|
||
from .mineru import parse_doc
|
||
|
||
health_check_response = requests.get(mineru_ocr_uri_health, timeout=5)
|
||
if health_check_response.status_code != 200:
|
||
logger.error(f"Mineru OCR service health check failed with {mineru_ocr_uri_health}: {health_check_response.json()}")
|
||
raise RuntimeError("Mineru OCR service health check failed. Please check the log use `docker logs mineru-api`")
|
||
|
||
pdf_path_list = [pdf_path]
|
||
output_dir = os.path.join(os.getcwd(), "tmp", "mineru_ocr")
|
||
|
||
pdf_text = parse_doc(pdf_path_list, output_dir,
|
||
backend="vlm-sglang-client",
|
||
server_url=mineru_ocr_uri)[0]
|
||
|
||
logger.debug(f"Mineru OCR result: {pdf_text[:50]}(...) total {len(pdf_text)} characters.")
|
||
return pdf_text
|
||
|
||
def get_state(task_id):
|
||
return GOLBAL_STATE.get(task_id, {})
|
||
|
||
def plainreader(file_path):
|
||
"""读取普通文本文件并返回text文本"""
|
||
assert os.path.exists(file_path), "File not found"
|
||
|
||
with open(file_path) as f:
|
||
text = f.read()
|
||
return text
|
||
|
||
|
||
|
||
if __name__ == "__main__":
|
||
parser = ArgumentParser()
|
||
parser.add_argument('--pdf-path', type=str, required=True, help='Path to the PDF file')
|
||
parser.add_argument('--return-text', action='store_true', help='Return the extracted text')
|
||
args = parser.parse_args()
|
||
|
||
ocr = OCRPlugin()
|
||
text = ocr.process_pdf(args.pdf_path)
|
||
print(text)
|