Skip to content

Commit

Permalink
openvino: update README files for Intel OpenVINO toolkit support
Browse files Browse the repository at this point in the history
Signed-off-by: Ron Evans <[email protected]>
  • Loading branch information
deadprogram committed May 16, 2018
1 parent a55b480 commit 35c6f09
Show file tree
Hide file tree
Showing 2 changed files with 4 additions and 64 deletions.
44 changes: 3 additions & 41 deletions openvino/README.md
Original file line number Diff line number Diff line change
@@ -1,48 +1,10 @@
# Using the Intel OpenVINO toolkit

The Intel OpenVINO toolkit is a set of tools and libraries for computer vision applications. It also includes a complete build of OpenCV installed with the Intel OpenVINO. It uses computer vision and imaging algorithms developed at Intel.
The Intel OpenVINO toolkit is a set of tools and libraries for computer vision applications, that uses computer vision and imaging algorithms developed at Intel. It also includes a complete build of OpenCV.

GoCV support for the Intel OpenVINO Photography Vision Library (PVL) can be found here in the "gocv.io/x/gocv/openvino/pvl" package. Check out the README.md in the `pvl` directory for more information.
GoCV support for the Intel OpenVINO Photography Vision Library (PVL) which can be found in the "gocv.io/x/gocv/openvino/pvl" package. Check out the README.md in the `pvl` directory for more information.

## How to install the Intel OpenVINO toolkit

You will need to install various dependencies before you will be able to run the Intel OpenVINO installer:

```
sudo apt-get update
sudo apt-get install build-essential ffmpeg cmake checkinstall pkg-config yasm libjpeg-dev curl imagemagick gedit mplayer unzip libpng12-dev libcairo2-dev libpango1.0-dev libgtk2.0-dev libgstreamer0.10-dev libswscale.dev libavcodec-dev libavformat-dev
```

### Installing OpenCL Support

If you also want to use the OpenCL support for GPU-based hardware acceleration, you must install the OpenCL runtime. First, install the dependencies:

```
sudo apt-get update
sudo apt-get install build-essential ffmpeg cmake checkinstall pkg-config yasm libjpeg-dev curl imagemagick gedit mplayer unzip libpng12-dev libcairo2-dev libpango1.0-dev libgtk2.0-dev libgstreamer0.10-dev libswscale.dev libavcodec-dev libavformat-dev
```

Next, obtain the OpenCL runtime package:

```
wget http://registrationcenter-download.intel.com/akdlm/irc_nas/11396/SRB5.0_linux64.zip
unzip SRB5.0_linux64.zip -d SRB5.0_linux64
cd SRB5.0_linux64
```

Last, install the OpenCL runtime:

```
sudo apt-get install xz-utils
mkdir intel-opencl
tar -C intel-opencl -Jxf intel-opencl-r5.0-63503.x86_64.tar.xz
tar -C intel-opencl -Jxf intel-opencl-devel-r5.0-63503.x86_64.tar.xz
tar -C intel-opencl -Jxf intel-opencl-cpu-r5.0-63503.x86_64.tar.xz
sudo cp -R intel-opencl/* /
sudo ldconfig
```

### Installing Intel OpenVINO toolkit
## Installing Intel OpenVINO toolkit

The most recent version of the Intel OpenVINO toolkit is currently R1. You can obtain it from here:

Expand Down
24 changes: 1 addition & 23 deletions openvino/pvl/README.md
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Using the Intel OpenVINO Photography Vision Library

The Intel OpenVINO Photography Vision Library (PVL) is a set of extensions to OpenCV that is installed with the Intel CV SDK. It uses computer vision and imaging algorithms developed at Intel.
The Photography Vision Library (PVL) is a set of extensions to OpenCV that is installed with the Intel OpenVINO toolkit. It uses computer vision and imaging algorithms developed at Intel.

GoCV support for the PVL can be found here in the "gocv.io/x/gocv/openvino/pvl" package.

Expand Down Expand Up @@ -79,25 +79,3 @@ func main() {
```

Some PVL examples are in the [cmd/openvino/pvl directory](../cmd/openvino/pvl) of this repo, in the form of some useful commands such as the [smile detector](../cmd/openvino/pvl/smiledetector).

## How to build/run code

Setup the environment for the Intel OpenVINO toolkit, by running the `setupvars.sh` program included with OpenVINO:

```
source /opt/intel/computer_vision_sdk/bin/setupvars.sh
```

Then set the needed other exports for building/running GoCV code by running the `env.sh` that is in the GoCV `openvino` directory:

You only need to do these two steps one time per session. Once you have run them, you do not need to run them again until you close your terminal window.

Now you can run the version command example to make sure you are compiling/linking against Intel OpenVINO:

```
$ go run ./cmd/version/main.go
gocv version: 0.7.0
opencv lib version: 3.3.1-cvsdk_2017_R3.2
```

Examples that use the Intel OpenVINO toolkit can be found in the `cmd/openvino/pvl` directory of this repository.

0 comments on commit 35c6f09

Please sign in to comment.