# copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import ast from PIL import Image import numpy as np from tools.infer.utility import draw_ocr_box_txt, str2bool, init_args as infer_args def init_args(): parser = infer_args() # params for output parser.add_argument("--output", type=str, default='./output') # params for table structure parser.add_argument("--table_max_len", type=int, default=488) parser.add_argument("--table_algorithm", type=str, default='TableAttn') parser.add_argument("--table_model_dir", type=str) parser.add_argument( "--table_char_dict_path", type=str, default="../ppocr/utils/dict/table_structure_dict.txt") # params for layout parser.add_argument( "--layout_path_model", type=str, default="lp://PubLayNet/ppyolov2_r50vd_dcn_365e_publaynet/config") parser.add_argument( "--layout_label_map", type=ast.literal_eval, default=None, help='label map according to ppstructure/layout/README_ch.md') # params for vqa parser.add_argument("--vqa_algorithm", type=str, default='LayoutXLM') parser.add_argument("--ser_model_dir", type=str) parser.add_argument( "--ser_dict_path", type=str, default="../train_data/XFUND/class_list_xfun.txt") # params for inference parser.add_argument( "--mode", type=str, default='structure', help='structure and vqa is supported') parser.add_argument( "--layout", type=str2bool, default=True, help='Whether to enable layout analysis') parser.add_argument( "--table", type=str2bool, default=True, help='In the forward, whether the table area uses table recognition') parser.add_argument( "--ocr", type=str2bool, default=True, help='In the forward, whether the non-table area is recognition by ocr') parser.add_argument( "--recovery", type=bool, default=False, help='Whether to enable layout of recovery') return parser def parse_args(): parser = init_args() return parser.parse_args() def draw_structure_result(image, result, font_path): if isinstance(image, np.ndarray): image = Image.fromarray(image) boxes, txts, scores = [], [], [] for region in result: if region['type'] == 'table': pass else: for text_result in region['res']: boxes.append(np.array(text_result['text_region'])) txts.append(text_result['text']) scores.append(text_result['confidence']) im_show = draw_ocr_box_txt( image, boxes, txts, scores, font_path=font_path, drop_score=0) return im_show