import time import fitz import numpy as np from loguru import logger from magic_pdf.libs.config_reader import get_local_models_dir, get_device from magic_pdf.model.model_list import MODEL import magic_pdf.model as model_config def dict_compare(d1, d2): return d1.items() == d2.items() def remove_duplicates_dicts(lst): unique_dicts = [] for dict_item in lst: if not any( dict_compare(dict_item, existing_dict) for existing_dict in unique_dicts ): unique_dicts.append(dict_item) return unique_dicts def load_images_from_pdf(pdf_bytes: bytes, dpi=200) -> list: try: from PIL import Image except ImportError: logger.error("Pillow not installed, please install by pip.") exit(1) images = [] with fitz.open("pdf", pdf_bytes) as doc: for index in range(0, doc.page_count): page = doc[index] mat = fitz.Matrix(dpi / 72, dpi / 72) pm = page.get_pixmap(matrix=mat, alpha=False) # if width or height > 3000 pixels, don't enlarge the image if pm.width > 3000 or pm.height > 3000: pm = page.get_pixmap(matrix=fitz.Matrix(1, 1), alpha=False) img = Image.frombytes("RGB", (pm.width, pm.height), pm.samples) img = np.array(img) img_dict = {"img": img, "width": pm.width, "height": pm.height} images.append(img_dict) return images class ModelSingleton: _instance = None _models = {} def __new__(cls, *args, **kwargs): if cls._instance is None: cls._instance = super().__new__(cls) return cls._instance def get_model(self, ocr: bool, show_log: bool): key = (ocr, show_log) if key not in self._models: self._models[key] = custom_model_init(ocr=ocr, show_log=show_log) return self._models[key] def custom_model_init(ocr: bool = False, show_log: bool = False): model = None if model_config.__model_mode__ == "lite": model = MODEL.Paddle elif model_config.__model_mode__ == "full": model = MODEL.PEK if model_config.__use_inside_model__: model_init_start = time.time() if model == MODEL.Paddle: from magic_pdf.model.pp_structure_v2 import CustomPaddleModel custom_model = CustomPaddleModel(ocr=ocr, show_log=show_log) elif model == MODEL.PEK: from magic_pdf.model.pdf_extract_kit import CustomPEKModel # 从配置文件读取model-dir和device local_models_dir = get_local_models_dir() device = get_device() custom_model = CustomPEKModel(ocr=ocr, show_log=show_log, models_dir=local_models_dir, device=device) else: logger.error("Not allow model_name!") exit(1) model_init_cost = time.time() - model_init_start logger.info(f"model init cost: {model_init_cost}") else: logger.error("use_inside_model is False, not allow to use inside model") exit(1) return custom_model def doc_analyze(pdf_bytes: bytes, ocr: bool = False, show_log: bool = False): model_manager = ModelSingleton() custom_model = model_manager.get_model(ocr, show_log) images = load_images_from_pdf(pdf_bytes) model_json = [] doc_analyze_start = time.time() for index, img_dict in enumerate(images): img = img_dict["img"] page_width = img_dict["width"] page_height = img_dict["height"] result = custom_model(img) page_info = {"page_no": index, "height": page_height, "width": page_width} page_dict = {"layout_dets": result, "page_info": page_info} model_json.append(page_dict) doc_analyze_cost = time.time() - doc_analyze_start logger.info(f"doc analyze cost: {doc_analyze_cost}") return model_json