119 lines
5.0 KiB
Python
119 lines
5.0 KiB
Python
from typing import List
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import cv2
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import numpy as np
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import tqdm
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from langchain_community.document_loaders.unstructured import UnstructuredFileLoader
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from PIL import Image
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import re
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from chatchat.settings import Settings
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from chatchat.server.file_rag.document_loaders.ocr import get_ocr
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from chatchat.utils import build_logger
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logger = build_logger()
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class RapidOCRPDFLoader(UnstructuredFileLoader):
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def _get_elements(self) -> List:
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def rotate_img(img, angle):
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"""
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img --image
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angle --rotation angle
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return--rotated img
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"""
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h, w = img.shape[:2]
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rotate_center = (w / 2, h / 2)
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# 获取旋转矩阵
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# 参数1为旋转中心点;
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# 参数2为旋转角度,正值-逆时针旋转;负值-顺时针旋转
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# 参数3为各向同性的比例因子,1.0原图，2.0变成原来的2倍，0.5变成原来的0.5倍
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M = cv2.getRotationMatrix2D(rotate_center, angle, 1.0)
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# 计算图像新边界
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new_w = int(h * np.abs(M[0, 1]) + w * np.abs(M[0, 0]))
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new_h = int(h * np.abs(M[0, 0]) + w * np.abs(M[0, 1]))
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# 调整旋转矩阵以考虑平移
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M[0, 2] += (new_w - w) / 2
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M[1, 2] += (new_h - h) / 2
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rotated_img = cv2.warpAffine(img, M, (new_w, new_h))
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return rotated_img
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def pdf2text(filepath):
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import fitz # pyMuPDF里面的fitz包，不要与pip install fitz混淆
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import numpy as np
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ocr = get_ocr()
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doc = fitz.open(filepath)
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resp = ""
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b_unit = tqdm.tqdm(
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total=doc.page_count, desc="RapidOCRPDFLoader context page index: 0"
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)
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for i, page in enumerate(doc):
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b_unit.set_description(
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"RapidOCRPDFLoader context page index: {}".format(i)
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)
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b_unit.refresh()
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text = page.get_text("")
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# resp += text + "\n"
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text_lines = text.strip().split("\n")
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logger.info(f"****page:{i+1}****，文字内容：{text_lines}")
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img_list = page.get_image_info(xrefs=True)
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ocr_result = []
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for img in img_list:
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if xref := img.get("xref"):
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bbox = img["bbox"]
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# 检查图片尺寸是否超过设定的阈值
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if (bbox[2] - bbox[0]) / (page.rect.width) < Settings.kb_settings.PDF_OCR_THRESHOLD[
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0
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] or (bbox[3] - bbox[1]) / (
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page.rect.height
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) < Settings.kb_settings.PDF_OCR_THRESHOLD[1]:
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continue
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pix = fitz.Pixmap(doc, xref)
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samples = pix.samples
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if int(page.rotation) != 0: # 如果Page有旋转角度，则旋转图片
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img_array = np.frombuffer(
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pix.samples, dtype=np.uint8
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).reshape(pix.height, pix.width, -1)
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tmp_img = Image.fromarray(img_array)
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ori_img = cv2.cvtColor(np.array(tmp_img), cv2.COLOR_RGB2BGR)
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rot_img = rotate_img(img=ori_img, angle=360 - page.rotation)
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img_array = cv2.cvtColor(rot_img, cv2.COLOR_RGB2BGR)
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else:
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img_array = np.frombuffer(
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pix.samples, dtype=np.uint8
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).reshape(pix.height, pix.width, -1)
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result, _ = ocr(img_array)
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if result:
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ocr_result = [line[1] for line in result]
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resp += "\n".join(ocr_result)
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if (len(ocr_result)>0):
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resp += "\n".join(ocr_result)
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else:
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if text_lines:
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# 假设页码在最后一行
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if text_lines[-1].isdigit():
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text = "\n".join(text_lines[:-1])
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print(f"******去除了页码")
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resp += text + "\n"
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# 更新进度
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b_unit.update(1)
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resp = re.sub(r'((?<!.)\d+(?!\.|[a-zA-Z0-9]))', r"\1 ", resp)
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resp = re.sub(r'((?<!.)[a-zA-Z0-9]+\s*\.\s*[a-zA-Z0-9]+(?!\.|[a-zA-Z0-9]))', r"\1 ", resp)
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resp = re.sub(r'((?<!.)[a-zA-Z0-9]+\s*\.\s*[a-zA-Z0-9]+\s*\.\s*[a-zA-Z0-9]+(?!\.|[a-zA-Z0-9]))', r"\1 ", resp)
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return resp
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text = pdf2text(self.file_path)
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from unstructured.partition.text import partition_text
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return partition_text(text=text, **self.unstructured_kwargs)
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if __name__ == "__main__":
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loader = RapidOCRPDFLoader(file_path="/Users/tonysong/Desktop/test.pdf")
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docs = loader.load()
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print(docs)
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