Intel Delta 9 course
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Intel Delta 9 lectures

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Image processing language Halide

Date: February, 28. 18:00 - 19:20 MSK

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Deep learning with OpenCV on PC, smartphone, in browser

Date: February, 28. 19:40 - 21:00 MSK

We'll see several computer vision problems are solved by deep learning models. Follow Requirements section if you want to bring laptops or reproduce the code locally.


Guide the following steps for each of the samples. Execute commands in terminal (Ubuntu) or using Developer Command Prompt (Microsoft Windows).

DL on PC

Human pose estimation using OpenPose model.

  • Install python and NumPy on your system

  • Download OpenCV source code or clone it using git:

    git clone --depth 1
  • Create build folder:

    cd /path/to/opencv
    mkdir build && cd build
  • Build OpenCV modules:

    • Ubuntu

      cmake -DCMAKE_BUILD_TYPE=Release -DBUILD_LIST=dnn,python2,highgui,videoio,imgproc .. && make -j4
    • Microsoft Windows

      "C:\Program Files\CMake\bin\cmake.exe" -DCMAKE_BUILD_TYPE=Release -DBUILD_LIST=dnn,python2,highgui,videoio,imgproc -G "Visual Studio 14 Win64" ..
      "C:\Program Files\CMake\bin\cmake.exe" --build . --config Release -- /m:4
  • Specify OpenCV location:

    • Ubuntu

      export PYTHONPATH=/path/to/opencv/build/lib:$PYTHONPATH
    • Microsoft Windows

      Assuming OpenCV installed at C:\Users\%USERNAME%\opencv\build

      set PYTHONPATH=C:\Users\%USERNAME%\opencv\build\lib\Release
      set PATH=C:\Users\%USERNAME%\opencv\build\bin\Release;%PATH%
  • Check installation: create a text file with the following python code:

    import cv2 as cv
    img = cv.imread('example.png')
    cv.imshow('Test OpenCV', img)

    Run by python (Ubuntu) or by C:\Python27\python.exe (Microsoft Windows).

  • Download files

    1. Pose estimation .caffemodel
    2. Pose estimation .prototxt

DL on smartphone

Recognize gender by face. This sample is based on Age- Gender- recognition networks

DL in browser

Use Places205-AlexNet model for scene recognition.

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