Docker版本,官方提供的基础镜像文件都是包含CUDA的版本,自已基于centos:8.3合成的CPU版,部署和启动时没有任何问题。
W0107 05:13:49.063356 1 analysis_predictor.cc:1058] Deprecated. Please use CreatePredictor instead.
[2021-01-07 05:13:49 +0000] [1] [INFO] Starting gunicorn 20.0.4
[2021-01-07 05:13:49 +0000] [1] [INFO] Listening at: http://0.0.0.0:8868 (1)
[2021-01-07 05:13:49 +0000] [1] [INFO] Using worker: sync
[2021-01-07 05:13:49 +0000] [32] [INFO] Booting worker with pid: 32
[2021-01-07 05:13:49 +0000] [33] [INFO] Booting worker with pid: 33
[2021-01-07 05:13:49 +0000] [34] [INFO] Booting worker with pid: 34
[2021-01-07 05:13:49 +0000] [35] [INFO] Booting worker with pid: 35
但在HTTP调用时,如果图片比较大(分辨率比较高,比如1K x 2K)时,总是出现超时:
[2021-01-07 05:14:35 +0000] [1] [CRITICAL] WORKER TIMEOUT (pid:38)
[2021-01-07 05:14:37 +0000] [50] [INFO] Booting worker with pid: 50
[2021-01-07 05:15:19 +0000] [1] [CRITICAL] WORKER TIMEOUT (pid:37)
[2021-01-07 05:15:20 +0000] [61] [INFO] Booting worker with pid: 61
将图片用工具缩小(600x800左右)后,就可以正常处理:(有并发调用)
[2021-01-07 12:32:55 +0000] [35] [INFO] Worker exiting (pid: 35)
[2021-01-07 12:32:55 +0000] [33] [INFO] Worker exiting (pid: 33)
ocr_system == 1.0.0
ocr_system == 1.0.0
dt_boxes num : 16, elapse : 1.0802247524261475
cls num : 16, elapse : 0.3384115695953369
rec_res num : 16, elapse : 17.49129319190979
dt_boxes num : 4, elapse : 24.130218744277954
cls num : 4, elapse : 0.06459522247314453
rec_res num : 4, elapse : 0.899388313293457
代码中哪里可以把超时值设大一些吗?(javaer,不熟悉python,还在摸索中),
另外源码中参数文件(deploy\hubserving\ocr_system\params.py)有详细说明吗?
def read_params():
cfg = Config()
#params for text detector
cfg.det_algorithm = "DB"
cfg.det_model_dir = "./inference/ch_ppocr_mobile_v1.1_det_infer/"
cfg.det_max_side_len = 960 #这个参数什么含义?
#DB parmas
cfg.det_db_thresh =0.3
cfg.det_db_box_thresh =0.5
cfg.det_db_unclip_ratio =2.0
#EAST parmas
cfg.det_east_score_thresh = 0.8
cfg.det_east_cover_thresh = 0.1
cfg.det_east_nms_thresh = 0.2
#params for text recognizer
cfg.rec_algorithm = "CRNN"
cfg.rec_model_dir = "./inference/ch_ppocr_mobile_v1.1_rec_infer/"
cfg.rec_image_shape = "3, 32, 320" #这个参数什么含义?
cfg.rec_char_type = 'ch'
cfg.rec_batch_num = 30 #这个参数什么含义?
cfg.max_text_length = 25 #这个参数什么含义?
cfg.rec_char_dict_path = "./ppocr/utils/ppocr_keys_v1.txt"
cfg.use_space_char = True
#params for text classifier
cfg.use_angle_cls = True
cfg.cls_model_dir = "./inference/ch_ppocr_mobile_v1.1_cls_infer/"
cfg.cls_image_shape = "3, 48, 192" #这个参数什么含义?
cfg.label_list = ['0', '180']
cfg.cls_batch_num = 30 #这个参数什么含义?
cfg.cls_thresh = 0.9
cfg.use_zero_copy_run = False
cfg.use_pdserving = False
return cfg
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worker timeout并非是由paddleOCR组件引起,而是由环境中的gunicorn组件。gunicorn中默认的线程timeout为30s,在config.py中找到timeout属性,延长timeout即可
可以在PaddleOCR issues下提问,参数含义shape就是输入图片的维度 batch_num是一个批处理的图片张数