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* Added pre-compiled debs for Raspbian Buster
* Restructured project folders
* Added C++ test
* Updated README / build_information.txt accordingly
TO DO:
* complete python test with verson / cpu enabled features check
* A pre-compiled **OpenCV 4.1.0** for **Raspberry Pi**, optimized for deep learning (**NEON**, **VFPV3**, **TBB** turned on).
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* Bindings for **Python2** and **Python3** are also included.
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* Created with OpenCV cpack targets
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* Tested on **Raspberry Pi 3+** using **Raspbian Stretch (Debian 9)**
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# Faster OpenCV for Raspberry Pi
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Leverage all your CPUs power in OpenCV by using **TBB**, **Neon** and **VFPV3** libraries.
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# Prerequisites
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Before proceeding, install OpenCV library prerequisites.
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Since I've already compiled this on my own Raspberry Pi I made it available on GitHub.
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Save countless of compile time by just installing these debs. Enjoy!
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## What is this?
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* A pre-compiled **OpenCV 4.1.0** for **Raspberry Pi** optimized for deep learning / computer vision applications (**NEON**, **VFPV3**, **TBB** turned on).
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* Bindings for **Python 2** and **Python 3** are also included.
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* For detailed build informations click [here](build_information.txt).
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* Created with OpenCV cpack targets.
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* Tested on **Raspberry Pi 3** using **Raspbian Buster (Debian 10)** (for Raspbian Stretch click [here](https://github.com/dlime/Faster_OpenCV_4_Raspberry_Pi/releases/tag/stretch_410)).
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## How much faster?
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Performance tests have been made in this [great blog article](https://www.pyimagesearch.com/2017/10/09/optimizing-opencv-on-the-raspberry-pi/) which led to an approximate **30%** increase in speed and of over **48%** when applied strictly to DNN module.
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Another performance test is available [here](https://www.theimpossiblecode.com/blog/faster-opencv-smiles-tbb/) which also led to about **30%** increase in speed.
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## How to use it?
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Install OpenCV library prerequisites on your Raspberry Pi.
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