False memory leaks on Visual Studio with OpenCV and MFC is a known "false" problem. Even if the solution is easy a lot of people is looking for. This article shows the solution step by step.
Raspberry PI is a wonderful system and OpenCV is an outstanding library for computer vision. Here is our how to install and configure OpenCV 3.2.0 for Python/C++ on a Raspberry PI 2 with Raspbian Jessie. On the Net there are many references on this subject, most of them have some missed point or reference to old versions.
In Memory Analysis-Part 1 we conclude that a std::queue of OpenCV Mats is memory effective. Here is a real test case of our pkQueueTS with one grabber and one processor threads. We will perform memory analysis to validate our preliminary conclusion about memory effectiveness and recycling.
A single lock, multiple producer/consumer (MPMC) thread safe queue with wait/timeout Pop. It also provides tools to manage elements like
cv::Mat and an interface for custom OnPush event handler.
Here is shown that both cv::Mat and Standard Library Containers work under memory recycling. We found that using std:queue as buffer for OpenCV Mat, memory requirements depends on size of the queue. We conclude that containers like std::queue can be used effectively as buffer for OpenCV Mats.
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To display an OpenCV image or video into your own MFC interface in Visual C++ you can use GDI's function but keep care of details.
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