From 5941490d81cd8fd4bcefe8995691462fa4de8174 Mon Sep 17 00:00:00 2001 From: Sebastian Golebiewski Date: Wed, 9 Nov 2022 16:54:04 +0100 Subject: [PATCH] Fixing indentation in General Optimizations for master (#13305) A minor fix that corrects indentation of snippets. Porting: https://github.com/openvinotoolkit/openvino/pull/13302 --- .../dldt_deployment_optimization_common.md | 10 ++++------ 1 file changed, 4 insertions(+), 6 deletions(-) diff --git a/docs/optimization_guide/dldt_deployment_optimization_common.md b/docs/optimization_guide/dldt_deployment_optimization_common.md index 57f5a97bdce..977ea89e35f 100644 --- a/docs/optimization_guide/dldt_deployment_optimization_common.md +++ b/docs/optimization_guide/dldt_deployment_optimization_common.md @@ -28,13 +28,11 @@ In the example below, inference is applied to the results of the video decoding. Below are example-codes for the regular and async-based approaches to compare: -- Normally, the frame is captured with OpenCV and then immediately processed:
+- Normally, the frame is captured with OpenCV and then immediately processed:
+ @snippet snippets/dldt_optimization_guide8.cpp part8 -@snippet snippets/dldt_optimization_guide8.cpp part8 - -- In the "true" async mode, the `NEXT` request is populated in the main (application) thread, while the `CURRENT` request is processed:
- -@snippet snippets/dldt_optimization_guide9.cpp part9 +- In the "true" async mode, the `NEXT` request is populated in the main (application) thread, while the `CURRENT` request is processed:
+ @snippet snippets/dldt_optimization_guide9.cpp part9 The technique can be generalized to any available parallel slack. For example, you can do inference and simultaneously encode the resulting or previous frames or run further inference, like emotion detection on top of the face detection results.