diff --git a/recognition/arcface_paddle/deploy/pdserving/README.md b/recognition/arcface_paddle/deploy/pdserving/README.md index 3ed7f789..94647801 100644 --- a/recognition/arcface_paddle/deploy/pdserving/README.md +++ b/recognition/arcface_paddle/deploy/pdserving/README.md @@ -26,7 +26,7 @@ The introduction and tutorial of Paddle Serving service deployment framework ref Arcface operating environment and Paddle Serving operating environment are needed. 1. Please prepare Arcface operating environment reference [link](../../README_en.md). - Download the corresponding paddle whl package according to the environment, it is recommended to install version 2.0.1. + Download the corresponding paddle whl package according to the environment, it is recommended to install version 2.2+. 2. The steps of PaddleServing operating environment prepare are as follows: @@ -143,40 +143,30 @@ The recognition model is the same. Tested on 700 real picture. The average QPS on V100 GPU can reach around 57: ``` - - 2021-05-13 03:42:36,895 ==================== TRACER ====================== - 2021-05-13 03:42:36,975 Op(rec): - 2021-05-13 03:42:36,976 in[14.472382882882883 ms] - 2021-05-13 03:42:36,976 prep[9.556855855855856 ms] - 2021-05-13 03:42:36,976 midp[59.921905405405404 ms] - 2021-05-13 03:42:36,976 postp[15.345945945945946 ms] - 2021-05-13 03:42:36,976 out[1.9921216216216215 ms] - 2021-05-13 03:42:36,976 idle[0.16254943864471572] - 2021-05-13 03:42:36,976 Op(det): - 2021-05-13 03:42:36,976 in[315.4468035714286 ms] - 2021-05-13 03:42:36,976 prep[69.5980625 ms] - 2021-05-13 03:42:36,976 midp[18.989535714285715 ms] - 2021-05-13 03:42:36,976 postp[18.857803571428573 ms] - 2021-05-13 03:42:36,977 out[3.1337544642857145 ms] - 2021-05-13 03:42:36,977 idle[0.7477961159203756] - 2021-05-13 03:42:36,977 DAGExecutor: - 2021-05-13 03:42:36,977 Query count[224] - 2021-05-13 03:42:36,977 QPS[22.4 q/s] - 2021-05-13 03:42:36,977 Succ[0.9910714285714286] - 2021-05-13 03:42:36,977 Error req[169, 170] - 2021-05-13 03:42:36,977 Latency: - 2021-05-13 03:42:36,977 ave[535.1678348214285 ms] - 2021-05-13 03:42:36,977 .50[172.651 ms] - 2021-05-13 03:42:36,977 .60[187.904 ms] - 2021-05-13 03:42:36,977 .70[245.675 ms] - 2021-05-13 03:42:36,977 .80[526.684 ms] - 2021-05-13 03:42:36,977 .90[854.596 ms] - 2021-05-13 03:42:36,977 .95[1722.728 ms] - 2021-05-13 03:42:36,977 .99[3990.292 ms] - 2021-05-13 03:42:36,978 Channel (server worker num[10]): - 2021-05-13 03:42:36,978 chl0(In: ['@DAGExecutor'], Out: ['det']) size[0/0] - 2021-05-13 03:42:36,979 chl1(In: ['det'], Out: ['rec']) size[6/0] - 2021-05-13 03:42:36,979 chl2(In: ['rec'], Out: ['@DAGExecutor']) size[0/0] + 2021-11-04 13:38:52,507 Op(ArcFace): + 2021-11-04 13:38:52,507 in[135.4579597902098 ms] + 2021-11-04 13:38:52,507 prep[0.9921311188811189 ms] + 2021-11-04 13:38:52,507 midp[3.9232132867132865 ms] + 2021-11-04 13:38:52,507 postp[0.12166258741258741 ms] + 2021-11-04 13:38:52,507 out[0.9898286713286714 ms] + 2021-11-04 13:38:52,508 idle[0.9643989520087675] + 2021-11-04 13:38:52,508 DAGExecutor: + 2021-11-04 13:38:52,508 Query count[573] + 2021-11-04 13:38:52,508 QPS[57.3 q/s] + 2021-11-04 13:38:52,509 Succ[0.9982547993019197] + 2021-11-04 13:38:52,509 Error req[394] + 2021-11-04 13:38:52,509 Latency: + 2021-11-04 13:38:52,509 ave[11.52941186736475 ms] + 2021-11-04 13:38:52,509 .50[11.492 ms] + 2021-11-04 13:38:52,509 .60[11.658 ms] + 2021-11-04 13:38:52,509 .70[11.95 ms] + 2021-11-04 13:38:52,509 .80[12.251 ms] + 2021-11-04 13:38:52,509 .90[12.736 ms] + 2021-11-04 13:38:52,509 .95[13.21 ms] + 2021-11-04 13:38:52,509 .99[13.987 ms] + 2021-11-04 13:38:52,510 Channel (server worker num[10]): + 2021-11-04 13:38:52,510 chl0(In: ['@DAGExecutor'], Out: ['ArcFace']) size[0/0] + 2021-11-04 13:38:52,510 chl1(In: ['ArcFace'], Out: ['@DAGExecutor']) size[0/0] ```