diff --git a/deploy/pdserving/README.md b/deploy/pdserving/README.md index b5d8953d73a97b0586fdc60de1c0531fb713f90c..34b525c47214d45819690ed7d161ce3d4dc0c322 100644 --- a/deploy/pdserving/README.md +++ b/deploy/pdserving/README.md @@ -156,7 +156,9 @@ The recognition model is the same. Multiple service requests can be sent at the same time if necessary. - The predicted performance data will be automatically written into the `PipelineServingLogs/pipeline.tracer` file: + The predicted performance data will be automatically written into the `PipelineServingLogs/pipeline.tracer` file. + + Tested on 200 real pictures, and limited the detection long side to 960. The average QPS on T4 GPU can reach around 13: ``` 2021-05-12 10:03:24,812 ==================== TRACER ====================== diff --git a/deploy/pdserving/README_CN.md b/deploy/pdserving/README_CN.md index 37d018d0ed2f95543fdf81ddb317de7542e5d244..4bb3427199ff60968226237bcf67277ae72a1b9d 100644 --- a/deploy/pdserving/README_CN.md +++ b/deploy/pdserving/README_CN.md @@ -153,7 +153,9 @@ python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_rec_in ``` 有需要的话可以同时发送多个服务请求 - 预测性能数据会被自动写入 `PipelineServingLogs/pipeline.tracer` 文件中: + 预测性能数据会被自动写入 `PipelineServingLogs/pipeline.tracer` 文件中。 + + 在200张真实图片上测试,把检测长边限制为960。T4 GPU 上 QPS 均值可达到13左右: ``` 2021-05-12 10:03:24,812 ==================== TRACER ====================== @@ -191,6 +193,8 @@ python3 -m paddle_serving_client.convert --dirname ./ch_ppocr_mobile_v2.0_rec_in 2021-05-12 10:03:24,910 chl2(In: ['rec'], Out: ['@DAGExecutor']) size[0/0] ``` + + ## FAQ **Q1**: 发送请求后没有结果返回或者提示输出解码报错