diff --git a/ppstructure/kie/requirements.txt b/ppstructure/kie/requirements.txt index 11fa98da1bff7a1863d8a077ca73435d15072523..6cfcba764190fd46f98b76c27e93db6f4fa36c45 100644 --- a/ppstructure/kie/requirements.txt +++ b/ppstructure/kie/requirements.txt @@ -4,4 +4,4 @@ seqeval pypandoc attrdict python_docx -https://paddleocr.bj.bcebos.com/ppstructure/whl/paddlenlp-2.3.0.dev0-py3-none-any.whl +paddlenlp>=2.4.1 diff --git a/ppstructure/table/predict_structure.py b/ppstructure/table/predict_structure.py index 0bf100852b9e9d501dfc858d8ce0787da42a61ed..08e381a846f1e8b4d38918e1031f5b219fed54e2 100755 --- a/ppstructure/table/predict_structure.py +++ b/ppstructure/table/predict_structure.py @@ -68,6 +68,7 @@ def build_pre_process_list(args): class TableStructurer(object): def __init__(self, args): + self.args = args self.use_onnx = args.use_onnx pre_process_list = build_pre_process_list(args) if args.table_algorithm not in ['TableMaster']: @@ -89,8 +90,31 @@ class TableStructurer(object): self.predictor, self.input_tensor, self.output_tensors, self.config = \ utility.create_predictor(args, 'table', logger) + if args.benchmark: + import auto_log + pid = os.getpid() + gpu_id = utility.get_infer_gpuid() + self.autolog = auto_log.AutoLogger( + model_name="table", + model_precision=args.precision, + batch_size=1, + data_shape="dynamic", + save_path=None, #args.save_log_path, + inference_config=self.config, + pids=pid, + process_name=None, + gpu_ids=gpu_id if args.use_gpu else None, + time_keys=[ + 'preprocess_time', 'inference_time', 'postprocess_time' + ], + warmup=0, + logger=logger) + def __call__(self, img): starttime = time.time() + if self.args.benchmark: + self.autolog.times.start() + ori_im = img.copy() data = {'image': img} data = transform(data, self.preprocess_op) @@ -99,6 +123,8 @@ class TableStructurer(object): return None, 0 img = np.expand_dims(img, axis=0) img = img.copy() + if self.args.benchmark: + self.autolog.times.stamp() if self.use_onnx: input_dict = {} input_dict[self.input_tensor.name] = img @@ -110,6 +136,8 @@ class TableStructurer(object): for output_tensor in self.output_tensors: output = output_tensor.copy_to_cpu() outputs.append(output) + if self.args.benchmark: + self.autolog.times.stamp() preds = {} preds['structure_probs'] = outputs[1] @@ -125,6 +153,8 @@ class TableStructurer(object): '', '', '' ] + structure_str_list + ['
', '', ''] elapse = time.time() - starttime + if self.args.benchmark: + self.autolog.times.end(stamp=True) return (structure_str_list, bbox_list), elapse @@ -164,6 +194,8 @@ def main(args): total_time += elapse count += 1 logger.info("Predict time of {}: {}".format(image_file, elapse)) + if args.benchmark: + table_structurer.autolog.report() if __name__ == "__main__": diff --git a/ppstructure/table/predict_table.py b/ppstructure/table/predict_table.py index aeec66deca62f648df249a5833dbfa678d2da612..8f9c7174904ab3818f62544aeadc97c410070b07 100644 --- a/ppstructure/table/predict_table.py +++ b/ppstructure/table/predict_table.py @@ -14,7 +14,6 @@ import os import sys -import subprocess __dir__ = os.path.dirname(os.path.abspath(__file__)) sys.path.append(__dir__) @@ -58,48 +57,28 @@ def expand(pix, det_box, shape): class TableSystem(object): def __init__(self, args, text_detector=None, text_recognizer=None): + self.args = args if not args.show_log: logger.setLevel(logging.INFO) - - self.text_detector = predict_det.TextDetector( - args) if text_detector is None else text_detector - self.text_recognizer = predict_rec.TextRecognizer( - args) if text_recognizer is None else text_recognizer - + args.benchmark = False + self.text_detector = predict_det.TextDetector(copy.deepcopy( + args)) if text_detector is None else text_detector + self.text_recognizer = predict_rec.TextRecognizer(copy.deepcopy( + args)) if text_recognizer is None else text_recognizer + args.benchmark = True self.table_structurer = predict_strture.TableStructurer(args) if args.table_algorithm in ['TableMaster']: self.match = TableMasterMatcher() else: self.match = TableMatch(filter_ocr_result=True) - self.benchmark = args.benchmark self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor( args, 'table', logger) - if args.benchmark: - import auto_log - pid = os.getpid() - gpu_id = utility.get_infer_gpuid() - self.autolog = auto_log.AutoLogger( - model_name="table", - model_precision=args.precision, - batch_size=1, - data_shape="dynamic", - save_path=None, #args.save_log_path, - inference_config=self.config, - pids=pid, - process_name=None, - gpu_ids=gpu_id if args.use_gpu else None, - time_keys=[ - 'preprocess_time', 'inference_time', 'postprocess_time' - ], - warmup=0, - logger=logger) def __call__(self, img, return_ocr_result_in_table=False): result = dict() time_dict = {'det': 0, 'rec': 0, 'table': 0, 'all': 0, 'match': 0} start = time.time() - structure_res, elapse = self._structure(copy.deepcopy(img)) result['cell_bbox'] = structure_res[1].tolist() time_dict['table'] = elapse @@ -118,24 +97,16 @@ class TableSystem(object): toc = time.time() time_dict['match'] = toc - tic result['html'] = pred_html - if self.benchmark: - self.autolog.times.end(stamp=True) end = time.time() time_dict['all'] = end - start - if self.benchmark: - self.autolog.times.stamp() return result, time_dict def _structure(self, img): - if self.benchmark: - self.autolog.times.start() structure_res, elapse = self.table_structurer(copy.deepcopy(img)) return structure_res, elapse def _ocr(self, img): h, w = img.shape[:2] - if self.benchmark: - self.autolog.times.stamp() dt_boxes, det_elapse = self.text_detector(copy.deepcopy(img)) dt_boxes = sorted_boxes(dt_boxes) @@ -233,12 +204,13 @@ def main(args): f_html.close() if args.benchmark: - text_sys.autolog.report() + table_sys.table_structurer.autolog.report() if __name__ == "__main__": args = parse_args() if args.use_mp: + import subprocess p_list = [] total_process_num = args.total_process_num for process_id in range(total_process_num): diff --git a/test_tipc/configs/layoutxlm_ser/train_pact_infer_python.txt b/test_tipc/configs/layoutxlm_ser/train_pact_infer_python.txt index fbf2a880269fba4596908def0980cb778a9281e3..c19b4b73a9fb8cc3b253d932f932479f3d706082 100644 --- a/test_tipc/configs/layoutxlm_ser/train_pact_infer_python.txt +++ b/test_tipc/configs/layoutxlm_ser/train_pact_infer_python.txt @@ -7,14 +7,14 @@ Global.auto_cast:fp32 Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=17 Global.save_model_dir:./output/ Train.loader.batch_size_per_card:lite_train_lite_infer=4|whole_train_whole_infer=8 -Architecture.Backbone.checkpoints:pretrain_models/ser_LayoutXLM_xfun_zh +Architecture.Backbone.pretrained:pretrain_models/ser_LayoutXLM_xfun_zh train_model_name:latest train_infer_img_dir:ppstructure/docs/kie/input/zh_val_42.jpg null:null ## trainer:pact_train norm_train:null -pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/layoutxlm_ser/ser_layoutxlm_xfund_zh.yml -o +pact_train:deploy/slim/quantization/quant.py -c test_tipc/configs/layoutxlm_ser/ser_layoutxlm_xfund_zh.yml -o Global.eval_batch_step=[2000,10] fpgm_train:null distill_train:null null:null diff --git a/test_tipc/configs/slanet/train_pact_infer_python.txt b/test_tipc/configs/slanet/train_pact_infer_python.txt index 42ed0cf5995d17d5fd55d2f35f0659f8e3defecb..98546afa696a0f04d3cbf800542c18352b55dee9 100644 --- a/test_tipc/configs/slanet/train_pact_infer_python.txt +++ b/test_tipc/configs/slanet/train_pact_infer_python.txt @@ -34,7 +34,7 @@ distill_export:null export1:null export2:null ## -infer_model:./inference/en_ppocr_mobile_v2.0_table_structure_infer +infer_model:./inference/en_ppstructure_mobile_v2.0_SLANet_infer infer_export:null infer_quant:True inference:ppstructure/table/predict_table.py --det_model_dir=./inference/en_ppocr_mobile_v2.0_table_det_infer --rec_model_dir=./inference/en_ppocr_mobile_v2.0_table_rec_infer --rec_char_dict_path=./ppocr/utils/dict/table_dict.txt --table_char_dict_path=./ppocr/utils/dict/table_structure_dict.txt --image_dir=./ppstructure/docs/table/table.jpg --det_limit_side_len=736 --det_limit_type=min --output ./output/table diff --git a/test_tipc/prepare.sh b/test_tipc/prepare.sh index 62cda1d8a5b7c75ee6b22ef9e81f467d06907559..da6dfecad0dd1c43cc712ede767c77c8467b4e34 100644 --- a/test_tipc/prepare.sh +++ b/test_tipc/prepare.sh @@ -146,6 +146,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then python_name=${array[0]} ${python_name} -m pip install -r requirements.txt ${python_name} -m pip install https://paddleocr.bj.bcebos.com/libs/auto_log-1.2.0-py3-none-any.whl + ${python_name} -m pip install paddleslim==2.3.4 # pretrain lite train data wget -nc -P ./pretrain_models/ https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV3_large_x0_5_pretrained.pdparams --no-check-certificate wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/dygraph_v2.0/en/det_mv3_db_v2.0_train.tar --no-check-certificate @@ -260,7 +261,7 @@ if [ ${MODE} = "lite_train_lite_infer" ];then wget -nc -P ./pretrain_models/ https://paddleocr.bj.bcebos.com/rec_r32_gaspin_bilstm_att_train.tar --no-check-certificate cd ./pretrain_models/ && tar xf rec_r32_gaspin_bilstm_att_train.tar && cd ../ fi - if [ ${model_name} == "layoutxlm_ser" ]; then + if [[ ${model_name} =~ "layoutxlm_ser" ]]; then ${python_name} -m pip install -r ppstructure/kie/requirements.txt ${python_name} -m pip install opencv-python -U wget -nc -P ./train_data/ https://paddleocr.bj.bcebos.com/ppstructure/dataset/XFUND.tar --no-check-certificate