orc识别较慢_关于半自动标注工具PPOCRLabel运行速度由快逐渐变慢的问题

news/2024/7/4 13:23:34

1.问题描述

在使用PPOCRLabel进行自动标注的过程中,发现文本检测模块运行速度由最开始的每帧三百多毫秒逐渐变为每帧数秒,且速度还在不断变慢中。初步定位为后处理DBPostProcess耗时在增加,db模型预测速度正常。其余方向分类和文本识别模块运行正常。

2.运行环境

ubuntu16.04,paddlepaddle-gpu 2.0.0rc0,PaddleOcr为最新版本

3.终端输出信息

/home/scxd/anaconda3/envs/tf15/bin/python /home/scxd/下载/PaddleOCR/PPOCRLabel/PPOCRLabel.py

You are using Paddle compiled with TensorRT, but TensorRT dynamic library is not found. Ignore this if TensorRT is not needed.W1211 15:50:30.711303 20512 analysis_predictor.cc:1042] Deprecated. Please use CreatePredictor instead.

Namespace(cls=True, cls_batch_num=30, cls_image_shape='3, 48, 192', cls_model_dir='/home/scxd/.paddleocr/cls', cls_thresh=0.9, det=True, det_algorithm='DB', det_db_box_thresh=0.5, det_db_thresh=0.3, det_db_unclip_ratio=2.0, det_east_cover_thresh=0.1, det_east_nms_thresh=0.2, det_east_score_thresh=0.8, det_max_side_len=960, det_model_dir='/home/scxd/.paddleocr/det', enable_mkldnn=True, gpu_mem=8000, image_dir=None, ir_optim=True, label_list=['0', '180'], lang='ch', max_text_length=25, rec=True, rec_algorithm='CRNN', rec_batch_num=30, rec_char_dict_path='./ppocr/utils/ppocr_keys_v1.txt', rec_char_type='ch', rec_image_shape='3, 32, 320', rec_model_dir='/home/scxd/.paddleocr/rec/ch', use_angle_cls=True, use_gpu=False, use_pdserving=False, use_space_char=True, use_tensorrt=False, use_zero_copy_run=True)

--- fused 0 scale with matmul

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with transpose's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape with transpose's xshape

--- Fused 0 MatmulTransposeReshape patterns

--- fused 0 scale with matmul

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with transpose's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape with transpose's xshape

--- Fused 0 MatmulTransposeReshape patterns

--- fused 0 scale with matmul

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with transpose's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape

--- Fused 0 ReshapeTransposeMatmulMkldnn patterns with reshape's xshape with transpose's xshape

--- Fused 0 MatmulTransposeReshape patterns

det predict time: 0.037546396255493164

dt_boxes num : 1, elapse : 0.039429426193237305

cls num : 1, elapse : 0.057495832443237305

rec_res num : 1, elapse : 0.04390716552734375

file name in openNext is /home/scxd/下载/PaddleOCR/PPOCRLabel/0202/车牌号码一致-不合格/0582010260002_豫ELE138_LS4AAB3D69A207903_B_长安牌_SC6399E3S_4110000820296_0202.jpg

dirPath in importDirImages is /home/scxd/下载/PaddleOCR/PPOCRLabel/0202/车牌号码一致-不合格

Using model from paddle

det predict time: 0.2977015972137451

dt_boxes num : 77, elapse : 0.3498392105102539

cls num : 77, elapse : 0.1686859130859375

rec_res num : 77, elapse : 0.6987478733062744

det predict time: 0.22007083892822266

dt_boxes num : 73, elapse : 0.2685093879699707

cls num : 73, elapse : 0.1276531219482422

rec_res num : 73, elapse : 0.47435808181762695

det predict time: 0.1806654930114746

dt_boxes num : 76, elapse : 0.22925329208374023

cls num : 76, elapse : 0.10770082473754883

rec_res num : 76, elapse : 0.5447311401367188

det predict time: 0.20402884483337402

dt_boxes num : 76, elapse : 0.6207420825958252

cls num : 76, elapse : 0.11475825309753418

rec_res num : 76, elapse : 0.5139966011047363

det predict time: 0.19577980041503906

dt_boxes num : 73, elapse : 0.864727258682251

cls num : 73, elapse : 0.123138427734375

rec_res num : 73, elapse : 0.564220666885376

det predict time: 0.24736261367797852

dt_boxes num : 77, elapse : 0.8772099018096924

cls num : 77, elapse : 0.13273119926452637

rec_res num : 77, elapse : 0.5378413200378418

det predict time: 0.21146535873413086

dt_boxes num : 73, elapse : 1.1587340831756592

cls num : 73, elapse : 0.11177635192871094

rec_res num : 73, elapse : 0.5897774696350098

det predict time: 0.24874520301818848

dt_boxes num : 73, elapse : 1.2370197772979736

cls num : 73, elapse : 0.10873270034790039

rec_res num : 73, elapse : 0.565443754196167

det predict time: 0.1952371597290039

dt_boxes num : 76, elapse : 1.2825310230255127

cls num : 76, elapse : 0.11092448234558105

rec_res num : 76, elapse : 0.5688521862030029

det predict time: 0.2193150520324707

dt_boxes num : 76, elapse : 1.639373540878296

cls num : 76, elapse : 0.14500761032104492

rec_res num : 76, elapse : 0.7249767780303955

det predict time: 0.3704209327697754

dt_boxes num : 74, elapse : 1.8702874183654785

cls num : 74, elapse : 0.1795973777770996

rec_res num : 74, elapse : 0.5498309135437012

det predict time: 0.18817448616027832

dt_boxes num : 73, elapse : 1.4679145812988281

cls num : 73, elapse : 0.10832524299621582

rec_res num : 73, elapse : 0.4966611862182617

det predict time: 0.2001192569732666

dt_boxes num : 74, elapse : 1.62302565574646

cls num : 74, elapse : 0.11504983901977539

rec_res num : 74, elapse : 0.5624067783355713

det predict time: 0.2997562885284424

dt_boxes num : 74, elapse : 2.0461623668670654

cls num : 74, elapse : 0.14160466194152832

rec_res num : 74, elapse : 0.5207874774932861

det predict time: 0.19435358047485352

dt_boxes num : 76, elapse : 1.9407012462615967

cls num : 76, elapse : 0.14803338050842285

rec_res num : 76, elapse : 0.6762921810150146

det predict time: 0.3132789134979248

dt_boxes num : 75, elapse : 2.5018603801727295

cls num : 75, elapse : 0.1715550422668457

rec_res num : 75, elapse : 0.6884877681732178

det predict time: 0.3265566825866699

dt_boxes num : 75, elapse : 2.079115629196167

cls num : 75, elapse : 0.10779476165771484

rec_res num : 75, elapse : 0.5672132968902588

det predict time: 0.21246790885925293

dt_boxes num : 72, elapse : 1.6790547370910645

cls num : 72, elapse : 0.14844393730163574

rec_res num : 72, elapse : 0.5574753284454346

det predict time: 0.3297126293182373

dt_boxes num : 73, elapse : 2.6516916751861572

cls num : 73, elapse : 0.16812753677368164

rec_res num : 73, elapse : 0.6038415431976318

det predict time: 0.3096339702606201

dt_boxes num : 73, elapse : 2.999793291091919

cls num : 73, elapse : 0.16036033630371094

rec_res num : 73, elapse : 0.5871908664703369

det predict time: 0.3044452667236328

dt_boxes num : 71, elapse : 1.8405787944793701

cls num : 71, elapse : 0.13389158248901367

rec_res num : 71, elapse : 0.49244165420532227

det predict time: 0.19132757186889648

dt_boxes num : 70, elapse : 2.9579010009765625

cls num : 70, elapse : 0.1821136474609375

rec_res num : 70, elapse : 0.6313180923461914

det predict time: 0.31190919876098633

dt_boxes num : 73, elapse : 3.1229403018951416

cls num : 73, elapse : 0.11895394325256348

rec_res num : 73, elapse : 0.5247178077697754

det predict time: 0.1909348964691162

dt_boxes num : 73, elapse : 2.9996631145477295

cls num : 73, elapse : 0.14319229125976562

rec_res num : 73, elapse : 0.5795223712921143

det predict time: 0.3408496379852295

dt_boxes num : 68, elapse : 2.336437463760376

cls num : 68, elapse : 0.13057756423950195

rec_res num : 68, elapse : 0.4755406379699707

det predict time: 0.2293105125427246

dt_boxes num : 74, elapse : 3.192828893661499

cls num : 74, elapse : 0.2037339210510254

rec_res num : 74, elapse : 0.6341958045959473

det predict time: 0.263242244720459

dt_boxes num : 70, elapse : 3.8145816326141357

cls num : 70, elapse : 0.15537261962890625

rec_res num : 70, elapse : 0.5746915340423584

det predict time: 0.3264651298522949

dt_boxes num : 68, elapse : 2.273308515548706

cls num : 68, elapse : 0.15056896209716797

rec_res num : 68, elapse : 0.5434515476226807

det predict time: 0.19071388244628906

dt_boxes num : 76, elapse : 3.6470935344696045

cls num : 76, elapse : 0.17305803298950195

rec_res num : 76, elapse : 0.5492415428161621

det predict time: 0.35550856590270996

dt_boxes num : 74, elapse : 3.73460054397583

cls num : 74, elapse : 0.1271042823791504

rec_res num : 74, elapse : 0.49611639976501465

det predict time: 0.2380836009979248

dt_boxes num : 72, elapse : 4.321373701095581

cls num : 72, elapse : 0.17403864860534668

rec_res num : 72, elapse : 0.5772228240966797

det predict time: 0.36488890647888184

dt_boxes num : 69, elapse : 3.1870806217193604

cls num : 69, elapse : 0.13794469833374023

...


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