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from transformers import Pipeline
import torch
from typing import Union, List
import fitz
import os
from detectron2.config import get_cfg
from detectron2.engine import DefaultPredictor
class MinerUPipeline(Pipeline):
def __init__(self, model_path, **kwargs):
super().__init__(**kwargs)
# 加载Layout模型
cfg = get_cfg()
cfg.merge_from_file(os.path.join(model_path, "models/Layout/config.json"))
cfg.MODEL.WEIGHTS = os.path.join(model_path, "models/Layout/model_final.pth")
self.layout_model = DefaultPredictor(cfg)
# 加载其他模型
self.formula_detector = torch.load(os.path.join(model_path, "models/MFD/weights.pt"))
self.formula_recognizer = AutoModel.from_pretrained(os.path.join(model_path, "models/MFR/UniMERNet"))
self.table_recognizer = AutoModel.from_pretrained(os.path.join(model_path, "TabRec/StructEqTable"))
def preprocess(self, pdf_path):
"""处理PDF输入"""
doc = fitz.open(pdf_path)
pages = []
for page in doc:
# 获取页面图像
pix = page.get_pixmap()
# 转换为模型所需格式
img = torch.tensor(pix.samples).permute(2, 0, 1).float()
pages.append(img)
return pages
def _forward(self, pages):
results = []
for page in pages:
# 1. 布局分析
layout = self.layout_model(page)
# 2. 根据布局结果处理不同区域
text_regions = []
formula_regions = []
table_regions = []
for region in layout:
if region.type == "text":
text_regions.append(self._process_text(region))
elif region.type == "formula":
formula_regions.append(self._process_formula(region))
elif region.type == "table":
table_regions.append(self._process_table(region))
results.append({
"text": text_regions,
"formulas": formula_regions,
"tables": table_regions
})
return results
def _process_formula(self, region):
# 公式检测和识别
detected = self.formula_detector(region.image)
return self.formula_recognizer(detected)
def _process_table(self, region):
# 表格识别
return self.table_recognizer(region.image)
def postprocess(self, model_outputs):
"""转换为Markdown"""
markdown = []
for page in model_outputs:
# 组合文本、公式和表格
markdown.extend(page["text"])
markdown.extend([f"$${formula}$$" for formula in page["formulas"]])
markdown.extend([table.to_markdown() for table in page["tables"]])
return "\n\n".join(markdown) |