OpenCV Mat 形式での .data のデータフォーマットを検証する

Vitis Vision Library の examples では、OpenCV Mat 形式の .data を ap_uint<***> * でキャストして、ハードウェア化する関数に渡していた。そのフォーマットを検証してみよう。
ハードウェア化する関数に渡すDMA の 32 ビット幅のデータ形式については、”Vitis Vision Library の AXI4 Master インターフェース版 medianblur をZYBO Z7-20 で使ってみる1（準備編）”でやっていたのだが、その確認と、それに、ツィッターで @waka3_m さんに CV_8UC4 について教えていただいた。（ @waka3_m さんには Mat のデータ形式についてもアドバイスいただいた。ありがとうございました。）
そのような理由から、Mat 形式の画像のピクセルを AXI4-Stream にする Vitis HLS 2020.2 の array2axi プロジェクトを作って検証してみよう。

array2axis プロジェクトは Mat 形式データを AXI4-Stream に変換するが、あくまで Mat 形式のデータを検証するためのものだ。ハードウェア化する関数にも printf() でデータフォーマットを書き出しているのだが、気にしないようにして欲しい。
まずは、 array2axis.h から貼っておく。
CONFIG_8UC3 と CONFIG_8UC4 の定義を切り替えるようになっている。
CONFIG_8UC3 が定義されている時は、画像ファイルを読み込んだデータを CV_8UC3 のまま array2axis() を呼び出す。
CONFIG_8UC4 が定義されている時は、画像ファイルを読み込んだデータを一旦 CV_8UC4 （BGRA）に変換してから、 array2axis() を呼び出す。

// array2axis.h
// 2021/01/05 by marsee
//

#ifndef __ARRAY2AXIS_H__
#define  __ARRAY2AXIS_H__

#define PICT_WIDTH      128
#define PICT_HEIGHT 128
#define PICT_LIMIT      (PICT_WIDTH * PICT_HEIGHT)
#define PICT_MAT_LIMIT  (((float)PICT_LIMIT*3.0)/4.0)

#define CONFIG_8UC3
//#define CONFIG_8UC4

#endif

array2axis.cpp を貼っておく。

// array2axis.cpp
// 2021/01/05 by marsee
//

#include <ap_int.h>
#include <hls_stream.h>
#include <ap_axi_sdata.h>

#include "array2axis.h"

ap_uint<32> cutout_bit8(ap_uint<32> data, ap_uint<32> bottom_bit){
    return((data>>bottom_bit) & 0xff);
}

int array2axis(ap_uint<32> *array_in, hls::stream<ap_axiu<32,1,1,1> >& axis_out){
#pragma HLS INTERFACE s_axilite port=return
#pragma HLS INTERFACE axis port=axis_out register_mode=both register
#pragma HLS INTERFACE s_axilite port=array_in
#pragma HLS INTERFACE m_axi port=array_in offset=slave depth=480000
    ap_uint<32> mat_array[3];
    ap_axiu<32,1,1,1> mat_pix;

    int pict_mat_8UC3 = (int)(PICT_MAT_LIMIT+(float)0.7); // Round up

#ifdef CONFIG_8UC4
    LOOP_XY: for(int xy=0; xy<PICT_LIMIT; xy++){
#else
    LOOP_XY: for(int xy=0; xy<pict_mat_8UC3; xy++){
#endif
        unsigned int temp = array_in[xy];
        printf("xy = %d , array_in[xy] = %x\n", xy, temp);

        mat_pix.data = (ap_uint<32>)temp;
        if(xy == 0)
            mat_pix.user = 1;
        else
            mat_pix.user = 0;
        mat_pix.last = 0;
        axis_out.write(mat_pix);
    }
    return(0);
}

array2axis_tb.cpp を貼っておく。

// array2axis_tb.cpp
// 2021/01/06 by marsee
//
// Refers to "Vitis_Libraries/vision/L1/examples/medianblur/xf_median_blur_tb.cpp"
// https://github.com/Xilinx/Vitis_Libraries/blob/master/vision/L1/examples/medianblur/xf_median_blur_tb.cpp
//

#include <opencv2/opencv.hpp>
#include <stdint.h>
#include <ap_int.h>
#include <hls_stream.h>
#include <ap_axi_sdata.h>

#include "array2axis.h"

int array2axis(ap_uint<32> *array_in, hls::stream<ap_axiu<32,1,1,1> >& axis_out);

int main(int argc, char** argv) {
    hls::stream<ap_axiu<32,1,1,1> > outs;
    hls::stream<ap_axiu<32,1,1,1> > outs_soft;
    ap_axiu<32,1,1,1> vals;
    ap_axiu<32,1,1,1> vals_soft;
    cv::Mat cnv_img;

    if (argc != 2) {
        fprintf(stderr, "Usage: Please input image files name");
        return(1);
    }

    cv::Mat in_img = cv::imread(argv[1], 1); // reading in the color image

#ifdef CONFIG_8UC4
    cnv_img.create(in_img.rows, in_img.cols, CV_8UC4);
    cv::cvtColor(in_img, cnv_img, cv::COLOR_BGR2BGRA);

    array2axis((ap_uint<32>*)cnv_img.data, outs);
#else
    array2axis((ap_uint<32>*)in_img.data, outs);
#endif

    return(0);
}

Vitis HLS 2020.2 の array2axis プロジェクトを示す。


Project メニューから Project Settings... を選択して、 Project Settings (array2axis) ダイアログを開いた。
Simulation をクリックする。
array2axis_tb.cpp の CFLAGS に -I/usr/local/include を指定した。フルパスで設定しても相対パスに直されるようだ。
Linker Flaos には

-L/usr/local/lib -lopencv_core -lopencv_imgcodecs -lopencv_imgproc

を指定した。
Input Argument には、”Vitis Vision Library の AXI4 Master インターフェース版 medianblur をZYBO Z7-20 で使ってみる1（準備編）”で作った

128x128_blue123.png

を指定した。

128x128_blue123.png は最初のピクセルの RGB の値を 1, 2, 3 にしてある。その次のピクセルの RGB の値は 4, 5, 6 と言うように順番に RGB の値を増やしている画像で、つまりどの RGB が現在転送されているかを一目瞭然で分かるようにした画像だ。

まずは、 array2axis.h で CONFIG_8UC3 を定義して C シミュレーションを行った。結果を示す。


出力された画像データのフォーマットは”Vitis Vision Library の AXI4 Master インターフェース版 medianblur をZYBO Z7-20 で使ってみる1（準備編）”と同じように見える。

xy = 0 , array_in[xy] = 6010203
xy = 1 , array_in[xy] = 8090405
xy = 2 , array_in[xy] = a0b0c07
xy = 3 , array_in[xy] = 120d0e0f
xy = 4 , array_in[xy] = 14151011
xy = 5 , array_in[xy] = 16171813
xy = 6 , array_in[xy] = 1e191a1b
xy = 7 , array_in[xy] = 20211c1d
xy = 8 , array_in[xy] = 2223241f
xy = 9 , array_in[xy] = 2a252627
xy = 10 , array_in[xy] = ff2829

次に、 array2axis.h で CONFIG_8UC4 を定義し、CONFIG_8UC4 をコメントアウトして、C シミュレーションを行った。結果を示す。


CV_8UC4 は 8 バイトが 4 個、つまり 1 ピクセルが 4 バイト = 32 ビットなので、 32 ビット幅と相性が良い。

xy = 0 , array_in[xy] = ff010203
xy = 1 , array_in[xy] = ff040506
xy = 2 , array_in[xy] = ff070809
xy = 3 , array_in[xy] = ff0a0b0c
xy = 4 , array_in[xy] = ff0d0e0f
xy = 5 , array_in[xy] = ff101112
xy = 6 , array_in[xy] = ff131415
xy = 7 , array_in[xy] = ff161718
xy = 8 , array_in[xy] = ff191a1b
xy = 9 , array_in[xy] = ff1c1d1e
xy = 10 , array_in[xy] = ff1f2021
xy = 11 , array_in[xy] = ff222324
xy = 12 , array_in[xy] = ff252627
xy = 13 , array_in[xy] = ff28292a

CV_8UC4 では、一番上のバイト・レーンにアルファ・チャネルが付くので、これを無視すれば、 AXI4 Master インターフェースのビットマップ・ディスプレイ・コントローラーで、そのまま DMA すれば画像を表示できそうだ。

Ubuntu 18.04 LTS のパソコンに OpenCV 3.4.9 をインストールする

Vitis Vision ライブラリを Vitis HLS 2020.2 でやってみようと思う。そのための準備として Vitis Vision Library User Guide には OpenCV をインストールするように書いてある。しかも、OpenCV 3.4 が良いようだ。
そこで、”Ubuntu18.04: OpenCV3.4.9 (CUDA10.2)のインストール”を参考にさせていただいて、OpenCV 3.4.9 を Ubuntu 18.04 LTS にインストールしようと思う。

最初に準備として apt でパッケージをインストールした。
sudo apt install build-essential ccache


sudo apt install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev tesseract-ocr libtesseract-dev


sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev


sudo apt-get install libgstreamer-plugins-base1.0-dev libgstreamer1.0-dev libgtk2.0-dev libgtk-3-dev libpng-dev libjpeg-dev libopenexr-dev libtiff-dev libwebp-dev


sudo apt install python3-dev python3-numpy


sudo apt install python3-pip


sudo apt install python-dev python-numpy


src ディレクトリを作り、src ディレクトリに入って、 opencv-3.4.9.zip を Chrome ブラウザでダウンロードする。
opencv-3.4.9.zip を解凍し、 opencv-3.4.9 ディレクトリを opencv ディレクトリとしてシンボリック・リンクする。
opencv_contrib-3.4.9.zip を Chrome ブラウザでダウンロードする。
opencv_contrib-3.4.9.zip を解凍し、opencv_contrib-3.4.9 ディレクトリを opencv_contrib ディレクトリとしてシンボリック・リンクする。
mkdir src
cd src
unzip -q opencv-3.4.9.zip
ln -s opencv-3.4.9 opencv
unzip -q opencv_contrib-3.4.9.zip
ln -s opencv_contrib-3.4.9 opencv_contrib


opencv ディレクトリに cd して、 build ディレクトリを作成し、 build ディレクトリに cd し、 cmake を行ったが、 gcc のバージョンが 7.5.0 だったため、make でエラーになってしまった。 gcc 6 以前を使用する必要があるようだ。
cd opencv
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=/media/masaaki/Ubuntu_Disk/OpenCV/src/opencv_contrib/modules -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D WITH_VTK=ON -D INSTALL_C_EXAMPLES=ON -D PYTHON3_EXECUTABLE=/usr/bin/python3.6 -D PYTHON_INCLUDE_DIR=/usr/include/python3.6 -D PYTHON_INCLUDE_DIR2=/usr/include/x86_64-linux-gnu/python3.6m -D PYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.6m.so -D PYTHON3_NUMPY_INCLUDE_DIRS=/usr/include/python3.6m/numpy -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D WITH_CUBLAS=1 -D WITH_OPENGL=ON -D WITH_CUDA=ON -D CUDA_ARCH_BIN="6.1" -D CUDA_ARCH_PTX="6.1" -DBUILD_opencv_cudacodec=OFF ..


gcc 6.5.0 がインストールされていたので、それを使用することにした。
環境変数の CC と CXX を設定した。
export CC=/usr/bin/gcc-6
export CXX=/usr/bin/g++-6
これで、もう一度 cmake したところ、今度は make で CUDA 関連のエラーが発生した。
そこで、 CUDA を OFF することにした。
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=/media/masaaki/Ubuntu_Disk/OpenCV/src/opencv_contrib/modules -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D WITH_VTK=ON -D INSTALL_C_EXAMPLES=ON -D PYTHON3_EXECUTABLE=/usr/bin/python3.6 -D PYTHON_INCLUDE_DIR=/usr/include/python3.6 -D PYTHON_INCLUDE_DIR2=/usr/include/x86_64-linux-gnu/python3.6m -D PYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.6m.so -D PYTHON3_NUMPY_INCLUDE_DIRS=/usr/include/python3.6m/numpy -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D ENABLE_FAST_MATH=1 -D WITH_CUDA=OFF ..


make -j$(nproc)



sudo make install



sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig


テストする。”Ubuntu18.04: OpenCV3.4.9 (CUDA10.2)のインストール”では、 example_gpu_opticalflow を使用したが、 CUDA=OFF にしてしまったため、 example_tutorial_optical_flow を動かしてみよう。
cp -aur ../opencv/samples/data .
build ディレクトリを確認した。


cd bin
./example_tutorial_optical_flow


ウインドウが表示され、人が歩いているビデオが表示されて、その軌跡が表示されているようだった。


成功のようだ。
最後に sudo make install の結果を貼っておく。

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-- Installing: /usr/local/include/opencv2/xphoto/inpainting.hpp
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-- Installing: /usr/local/share/OpenCV/samples/dpm/cascade_detect_camera.cpp
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-- Installing: /usr/local/share/OpenCV/samples/cpp/train_HOG.cpp
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-- Installing: /usr/local/share/OpenCV/samples/cpp/travelsalesman.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/tree_engine.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/tvl1_optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_basic.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_camera.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_gphoto2_autofocus.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_gstreamer_pipeline.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_image_sequence.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_intelperc.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_openni.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videocapture_starter.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videostab.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/videowriter_basic.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/warpPerspective_demo.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/watershed.cpp
-- Installing: /usr/local/share/OpenCV/samples/cpp/CMakeLists.txt
-- Installing: /usr/local/share/OpenCV/samples/dnn/classification.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/colorization.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/object_detection.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/openpose.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/segmentation.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/text_detection.cpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/common.hpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/custom_layers.hpp
-- Installing: /usr/local/share/OpenCV/samples/dnn/CMakeLists.txt
-- Installing: /usr/local/share/OpenCV/samples/gpu/alpha_comp.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/bgfg_segm.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/cascadeclassifier.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/farneback_optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/generalized_hough.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/hog.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/houghlines.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/morphology.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/multi.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/pyrlk_optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/stereo_match.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/stereo_multi.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/super_resolution.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/surf_keypoint_matcher.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/video_reader.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/video_writer.cpp
-- Installing: /usr/local/share/OpenCV/samples/gpu/CMakeLists.txt
-- Installing: /usr/local/share/OpenCV/samples/tapi/bgfg_segm.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/camshift.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/clahe.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/dense_optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/hog.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/opencl_custom_kernel.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/pyrlk_optical_flow.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/squares.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/ufacedetect.cpp
-- Installing: /usr/local/share/OpenCV/samples/tapi/CMakeLists.txt
-- Installing: /usr/local/share/OpenCV/samples/opencl/opencl-opencv-interop.cpp
-- Installing: /usr/local/share/OpenCV/samples/opencl/CMakeLists.txt
-- Installing: /usr/local/share/OpenCV/samples/python/_coverage.py
-- Installing: /usr/local/share/OpenCV/samples/python/_doc.py
-- Installing: /usr/local/share/OpenCV/samples/python/asift.py
-- Installing: /usr/local/share/OpenCV/samples/python/browse.py
-- Installing: /usr/local/share/OpenCV/samples/python/calibrate.py
-- Installing: /usr/local/share/OpenCV/samples/python/camera_calibration_show_extrinsics.py
-- Installing: /usr/local/share/OpenCV/samples/python/camshift.py
-- Installing: /usr/local/share/OpenCV/samples/python/coherence.py
-- Installing: /usr/local/share/OpenCV/samples/python/color_histogram.py
-- Installing: /usr/local/share/OpenCV/samples/python/common.py
-- Installing: /usr/local/share/OpenCV/samples/python/contours.py
-- Installing: /usr/local/share/OpenCV/samples/python/deconvolution.py
-- Installing: /usr/local/share/OpenCV/samples/python/demo.py
-- Installing: /usr/local/share/OpenCV/samples/python/dft.py
-- Installing: /usr/local/share/OpenCV/samples/python/digits.py
-- Installing: /usr/local/share/OpenCV/samples/python/digits_adjust.py
-- Installing: /usr/local/share/OpenCV/samples/python/digits_video.py
-- Installing: /usr/local/share/OpenCV/samples/python/distrans.py
-- Installing: /usr/local/share/OpenCV/samples/python/edge.py
-- Installing: /usr/local/share/OpenCV/samples/python/facedetect.py
-- Installing: /usr/local/share/OpenCV/samples/python/feature_homography.py
-- Installing: /usr/local/share/OpenCV/samples/python/find_obj.py
-- Installing: /usr/local/share/OpenCV/samples/python/fitline.py
-- Installing: /usr/local/share/OpenCV/samples/python/floodfill.py
-- Installing: /usr/local/share/OpenCV/samples/python/gabor_threads.py
-- Installing: /usr/local/share/OpenCV/samples/python/gaussian_mix.py
-- Installing: /usr/local/share/OpenCV/samples/python/grabcut.py
-- Installing: /usr/local/share/OpenCV/samples/python/hist.py
-- Installing: /usr/local/share/OpenCV/samples/python/houghcircles.py
-- Installing: /usr/local/share/OpenCV/samples/python/houghlines.py
-- Installing: /usr/local/share/OpenCV/samples/python/inpaint.py
-- Installing: /usr/local/share/OpenCV/samples/python/kalman.py
-- Installing: /usr/local/share/OpenCV/samples/python/kmeans.py
-- Installing: /usr/local/share/OpenCV/samples/python/lappyr.py
-- Installing: /usr/local/share/OpenCV/samples/python/letter_recog.py
-- Installing: /usr/local/share/OpenCV/samples/python/lk_homography.py
-- Installing: /usr/local/share/OpenCV/samples/python/lk_track.py
-- Installing: /usr/local/share/OpenCV/samples/python/logpolar.py
-- Installing: /usr/local/share/OpenCV/samples/python/morphology.py
-- Installing: /usr/local/share/OpenCV/samples/python/mosse.py
-- Installing: /usr/local/share/OpenCV/samples/python/mouse_and_match.py
-- Installing: /usr/local/share/OpenCV/samples/python/mser.py
-- Installing: /usr/local/share/OpenCV/samples/python/opencv_version.py
-- Installing: /usr/local/share/OpenCV/samples/python/opt_flow.py
-- Installing: /usr/local/share/OpenCV/samples/python/peopledetect.py
-- Installing: /usr/local/share/OpenCV/samples/python/plane_ar.py
-- Installing: /usr/local/share/OpenCV/samples/python/plane_tracker.py
-- Installing: /usr/local/share/OpenCV/samples/python/squares.py
-- Installing: /usr/local/share/OpenCV/samples/python/stereo_match.py
-- Installing: /usr/local/share/OpenCV/samples/python/texture_flow.py
-- Installing: /usr/local/share/OpenCV/samples/python/tst_scene_render.py
-- Installing: /usr/local/share/OpenCV/samples/python/turing.py
-- Installing: /usr/local/share/OpenCV/samples/python/video.py
-- Installing: /usr/local/share/OpenCV/samples/python/video_threaded.py
-- Installing: /usr/local/share/OpenCV/samples/python/video_v4l2.py
-- Installing: /usr/local/share/OpenCV/samples/python/watershed.py

ikwzm さんの Ultra96-V2 用 Ubuntu 18.04 上で OpenCV 3.4.3 をインストールして環境構築

ikwzm さんの”Ultra96/Ultra96-V2 向け Debian GNU/Linux で XRT(Xilinx Runtime) を動かす(Vitis編)”で実装されている Ultra96-V2 用の Ubuntu 18.04 LTS に、fclkcfg や udmabuf をインストールしてある。（”ikwzm さんの”Ultra96/Ultra96-V2 向け Debian GNU/Linux で XRT(Xilinx Runtime) を動かす”をやってみる5（fclkcfg, udmabufインストール編）”参照）

この Ubuntu 18.04 LTS に OpenCV 3.4.3 をインストールして環境を構築しよう。
まずは OpenCV 3.4.3 をインストールする。インストール方法は”Ultra96 のDebian にOpenCV 3.4.3 をインストール1”を参照してインストールしたが、sample/python の asift.py を動作させるには、GTK-2.0 が必要だったので、 cmake の前に以下のライブラリをインストールした。
sudo apt install libgtk2.0-dev libgtk2.0-dev

また、python3 のバージョンは 3.6.9 だった。

sudo apt install python3-tk
を実行する必要があったが、”Ultra96 のDebian にOpenCV 3.4.3 をインストール1”では PYTHONPATH を設定しているが、それは必要なかった。
opencv-3.4.3/samples/python ディレクトリに行って
python3 demo.py
で動作した。


asift.py の実行結果を示す。


OpenCV がインストールできたので、環境を構築しよう。
C++ のファイルをコンパイルできるようにしたい。”Ultra96 のDebianにインストールしたOpenCVのC++サンプルデザインをコンパイル”を参考にする。

ホームディレクトリに bin ディレクトリを作成して、スクリプト・ファイルの g++_opencv を用意し、実行パーミッションを与えた。
g++_opencv のコードを示す。

#!/bin/sh

if [ $# -eq 1 ] ; then
    g++ -ggdb `pkg-config --cflags opencv` -o `basename $1 .cpp` $1 `pkg-config --libs opencv`;
else
    echo "g++_opencv < C++ file name >"
fi

ホームディレクトリの .bashrc にパスを追加する。

export PATH=$PATH:~/bin

OpenCV の facedetect.cpp をコンパイルしてみよう。
cd ~/work/opencv-3.4.3/samples/cpp/
g++_opencv facedetect.cpp
コンパイルできて、 facedetect ができた。成功だ。


facedetect を起動した。
./facedetect ../data/lena.jpg


何で XRT がエラー出しているんだろうか？

facedetect 結果を示す。


成功だ。

ZYBO-Z7-20のDebianにOpenCV 3.1.0をインストール

”@ikwzmさんの”FPGA+SoC+Linux+Device Tree Overlay+FPGA Region(SDSoC対応編)”をやってみる1”で作りなおしたZYBO-Z7-20のDebianにOpenCV3.1.0をインストールした。

なお、何でOpenCV 3.1.0 かというと、reVISION-Zybo-Z7-20 で作成したMicro SD カードでOpenCVのバージョンを調べるために、
pkg-config --modversion opencv
を実行したところ、3.1.0 だったためだ。

さて、OpenCV 3.1.0 をインストールしていこう。
最初に”Ubuntu 16.04にOpenCV 3.1をインストールする手順”を見ながら下準備をした。
しかし、無いモジュールもあった。コマンドを示す。
sudo apt-get install build-essential cmake git


sudo apt-get install ffmpeg libopencv-dev libgtk-3-dev python-numpy python3-numpy libdc1394-22 libdc1394-22-dev libjpeg-dev libtiff5-dev libavcodec-dev libavformat-dev libswscale-dev libxine2-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libv4l-dev libtbb-dev qtbase5-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip


OpenCV 3.1.0 をダウンロードする。
wget https://github.com/Itseez/opencv/archive/3.1.0.zip


OpenCV 3.1.0 を解凍する。
unzip 3.1.0.zip


cd opencv-3.1.0/
mkdir build
cd build


この辺りで、Raspberry Pi のOpenCVインストール記事に乗り換える。”Raspberry Pi 2 ★ OpenCV 3.1.0 のインストール 〜 C++ & Python サンプルでのカメラ動作確認まで”を参考にした。その記事によると、cmake-gui を使うとのことなので、
sudo apt install cmake-gui
で cmake-gui をインストールした。


cmake-gui
Where is the source code: に /home/fpga/opencv-3.1.0
Where is build the binaries: に /home/fpga/opencv-3.1.0/build
を設定した。
Add Entry ボタンをクリックして以下のエントリを追加し、チェックを付けた。
ENABLE_NEON
ENABLE_OMIT_FRAME_POINTER
ENABLE_PRECOMPILED_HEADERS　（このエントリを追加してチェックをつけたことにより、後でエラーになってしまった。チェック無しをお勧めする）
ENABLE_VFPV3


Configure ボタンをクリックする。（下の図はクリックする前）


CMakeSetup ダイアログが開いた。Specify the generator for this project をUnix Makefile のままとして、Finish ボタンをクリックした。


Configure が進んでいるところを示す。
 

Configure が終了し、エントリが増えた。
Generate ボタンをクリックした。


Generate 終了。cmake-gui を閉じた。


make
make が始まった。


19% 付近でエラー発生。なんと stdlib.h がないと言われている。。。


検索してみると、”opencv2系をgcc6でコンパイルしたらエラーになった"がヒット。それによると、

-D ENABLE_PRECOMPILED_HEADERS=OFF

にする必要があるということだ。
もう一度
cmake-gui
して、ENABLE_PRECOMPILED_HEADERS のチェックを外した。


Configure して、Generate した。


そして、もう一度
make
した。


make が成功した。やった〜〜〜。

sudo make install
sudo ldconfig



python のサンプルを実行する。
cd ../samples/python/
ls


./video.py


./video.py を実行すると以下のウインドウが表示された。


次は C++ のサンプルをやってみる。
cd ~/opencv-3.1.0/samples/cpp/example_cmake/
make


opencv_example ができた。

./opencv_example
で実行すると、

Gtk-Message: Failed to load module "canberra-gtk-module"

が出ている。


./opencv_example を実行すると下のようなウインドウが表示された。


”Gtk-Message: Failed to load”表示が気になるので、検索したところ” [SOLVED] Gtk-Message: Failed to load module "canberra-gtk-module"”が見つかった。
それによると、
sudo apt-get install libcanberra-gtk3-module
すればよいそうなので、やってみた。
もう一度、
./opencv_example
すると、”Gtk-Message: Failed to load”表示は解消された。


しかし表示されたウインドウに変化はなかった。


example.cpp を見てみると、VideoCapture とかを使用していて、カメラ画像をキャプチャするサンプルのようだ。これは無理のようだ。

ともかく、OpenCV 3.1.0 をインストールすることができた。

Ubuntu 16.04 にOpenCV 3.3.0 rc をインストールした

”Ubuntu 16.04 にOpenCV 3.1.0 をインストールした”の続き。

前回は、Ubuntu 16.04 にOpenCV 3.1.0 をインストールしようとしたのだが、make でエラーになってしまった。どうやらCUDA 8.0 が悪さしているようだというのがわかった。dandelion さんからOpenCV 3.2 だったら大丈夫と教えていただいたので、OpenCV 3.2 以降をインストールすることにした。

”UbuntuにOpenCV3.2とcontribをインストールする。”を参考にさせていただいた。
さて、前準備は前回思いっきりやってあるので、OpenCV のソースコードのダウンロードからやってみよう。
まずは、ホームディレクトリ下に OpenCV ディレクトリを生成し、移動した。
mkdir OpenCV
cd OpenCV

OpenCV ソースをダウンロードした。
git clone https://github.com/opencv/opencv.git
git clone https://github.com/opencv/opencv_contrib.git

opencv ディレクトリに移動して、build ディレクトリを生成した。build ディレクトリに移動して、cmake を実行した。
cd opencv
mkdir build
cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=~/OpenCV/opencv_contrib/modules


cmake のコンフィギュレーションを示す。

-- General configuration for OpenCV 3.3.0-rc =====================================
--   Version control:               3.3.0-rc-159-g06407b4
-- 
--   Extra modules:
--     Location (extra):            /home/masaaki/OpenCV/opencv_contrib/modules
--     Version control (extra):     3.3.0-rc-7-g067b0a6
-- 
--   Platform:
--     Timestamp:                   2017-07-27T05:33:25Z
--     Host:                        Linux 4.4.0-87-generic x86_64
--     CMake:                       3.3.2
--     CMake generator:             Unix Makefiles
--     CMake build tool:            /usr/bin/make
--     Configuration:               RELEASE
-- 
--   CPU/HW features:
--     Baseline:                    SSE SSE2 SSE3
--       requested:                 SSE3
--     Dispatched code generation:  SSE4_1 SSE4_2 FP16 AVX AVX2
--       requested:                 SSE4_1 SSE4_2 AVX FP16 AVX2
--       SSE4_1 (2 files):          + SSSE3 SSE4_1
--       SSE4_2 (1 files):          + SSSE3 SSE4_1 POPCNT SSE4_2
--       FP16 (1 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
--       AVX (5 files):             + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
--       AVX2 (7 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2
-- 
--   C/C++:
--     Built as dynamic libs?:      YES
--     C++ Compiler:                /usr/bin/c++  (ver 5.4.0)
--     C++ flags (Release):         -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections  -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG  -DNDEBUG
--     C++ flags (Debug):           -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections  -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -g  -O0 -DDEBUG -D_DEBUG
--     C Compiler:                  /usr/bin/cc
--     C flags (Release):           -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections  -msse -msse2 -msse3 -fvisibility=hidden -O3 -DNDEBUG  -DNDEBUG
--     C flags (Debug):             -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections  -msse -msse2 -msse3 -fvisibility=hidden -g  -O0 -DDEBUG -D_DEBUG
--     Linker flags (Release):
--     Linker flags (Debug):
--     ccache:                      NO
--     Precompiled headers:         YES
--     Extra dependencies:          gtk-3 gdk-3 pangocairo-1.0 pango-1.0 atk-1.0 cairo-gobject cairo gdk_pixbuf-2.0 gio-2.0 gthread-2.0 /usr/lib/x86_64-linux-gnu/libpng.so /usr/lib/x86_64-linux-gnu/libz.so /usr/lib/x86_64-linux-gnu/libtiff.so /usr/lib/x86_64-linux-gnu/libjasper.so /usr/lib/x86_64-linux-gnu/libjpeg.so /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so gstbase-1.0 gstreamer-1.0 gobject-2.0 glib-2.0 gstvideo-1.0 gstapp-1.0 gstriff-1.0 gstpbutils-1.0 dc1394 avcodec-ffmpeg avformat-ffmpeg avutil-ffmpeg swscale-ffmpeg freetype harfbuzz dl m pthread rt cudart nppc nppi npps cufft -L/usr/local/cuda/lib64
--     3rdparty dependencies:
-- 
--   OpenCV modules:
--     To be built:                 cudev core cudaarithm flann imgproc ml objdetect phase_unwrapping plot reg surface_matching video xphoto bgsegm cudabgsegm cudafilters cudaimgproc cudawarping dnn face freetype fuzzy img_hash imgcodecs photo shape videoio xobjdetect cudacodec highgui ts bioinspired dpm features2d line_descriptor saliency text calib3d ccalib cudafeatures2d cudalegacy cudaobjdetect cudaoptflow cudastereo datasets rgbd stereo structured_light superres tracking videostab xfeatures2d ximgproc aruco optflow stitching python2
--     Disabled:                    world contrib_world
--     Disabled by dependency:      -
--     Unavailable:                 java python3 viz cnn_3dobj cvv dnn_modern hdf matlab sfm
-- 
--   GUI: 
--     QT:                          NO
--     GTK+ 3.x:                    YES (ver 3.18.9)
--     GThread :                    YES (ver 2.48.2)
--     GtkGlExt:                    NO
--     OpenGL support:              NO
--     VTK support:                 NO
-- 
--   Media I/O: 
--     ZLib:                        /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.8)
--     JPEG:                        /usr/lib/x86_64-linux-gnu/libjpeg.so (ver )
--     WEBP:                        build (ver encoder: 0x020e)
--     PNG:                         /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.2.54)
--     TIFF:                        /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42 - 4.0.6)
--     JPEG 2000:                   /usr/lib/x86_64-linux-gnu/libjasper.so (ver 1.900.1)
--     OpenEXR:                     /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so (ver 2.2.0)
--     GDAL:                        NO
--     GDCM:                        NO
-- 
--   Video I/O:
--     DC1394 1.x:                  NO
--     DC1394 2.x:                  YES (ver 2.2.4)
--     FFMPEG:                      YES
--       avcodec:                   YES (ver 56.60.100)
--       avformat:                  YES (ver 56.40.101)
--       avutil:                    YES (ver 54.31.100)
--       swscale:                   YES (ver 3.1.101)
--       avresample:                NO
--     GStreamer:                   
--       base:                      YES (ver 1.8.3)
--       video:                     YES (ver 1.8.3)
--       app:                       YES (ver 1.8.3)
--       riff:                      YES (ver 1.8.3)
--       pbutils:                   YES (ver 1.8.3)
--     OpenNI:                      NO
--     OpenNI PrimeSensor Modules:  NO
--     OpenNI2:                     NO
--     PvAPI:                       NO
--     GigEVisionSDK:               NO
--     Aravis SDK:                  NO
--     UniCap:                      NO
--     UniCap ucil:                 NO
--     V4L/V4L2:                    NO/YES
--     XIMEA:                       NO
--     Xine:                        NO
--     Intel Media SDK:             NO
--     gPhoto2:                     NO
-- 
--   Parallel framework:            pthreads
-- 
--   Trace:                         YES (with Intel ITT)
-- 
--   Other third-party libraries:
--     Use Intel IPP:               2017.0.2 [2017.0.2]
--                at:               /home/masaaki/OpenCV/opencv/build/3rdparty/ippicv/ippicv_lnx
--     Use Intel IPP IW:            prebuilt binaries (2017.0.2)
--     Use Intel IPP Async:         NO
--     Use VA:                      NO
--     Use Intel VA-API/OpenCL:     NO
--     Use Lapack:                  NO
--     Use Eigen:                   NO
--     Use Cuda:                    YES (ver 8.0)
--     Use OpenCL:                  YES
--     Use OpenVX:                  NO
--     Use custom HAL:              NO
-- 
--   NVIDIA CUDA
--     Use CUFFT:                   YES
--     Use CUBLAS:                  NO
--     USE NVCUVID:                 NO
--     NVIDIA GPU arch:             20 30 35 37 50 52 60 61
--     NVIDIA PTX archs:
--     Use fast math:               NO
-- 
--   OpenCL:                        <Dynamic loading of OpenCL library>
--     Include path:                /home/masaaki/OpenCV/opencv/3rdparty/include/opencl/1.2
--     Use AMDFFT:                  NO
--     Use AMDBLAS:                 NO
-- 
--   Python 2:
--     Interpreter:                 /usr/bin/python2.7 (ver 2.7.12)
--     Libraries:                   /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.12)
--     numpy:                       /home/masaaki/.local/lib/python2.7/site-packages/numpy/core/include (ver 1.11.0)
--     packages path:               lib/python2.7/dist-packages
-- 
--   Python 3:
--     Interpreter:                 /usr/bin/python3 (ver 3.5.2)
-- 
--   Python (for build):            /usr/bin/python2.7
-- 
--   Java:
--     ant:                         NO
--     JNI:                         NO
--     Java wrappers:               NO
--     Java tests:                  NO
-- 
--   Matlab:                        Matlab not found or implicitly disabled
-- 
--   Documentation:
--     Doxygen:                     NO
-- 
--   Tests and samples:
--     Tests:                       YES
--     Performance tests:           YES
--     C/C++ Examples:              NO
-- 
--   Install path:                  /usr/local
-- 
--   cvconfig.h is in:              /home/masaaki/OpenCV/opencv/build
-- -----------------------------------------------------------------
-- 
-- Configuring done
-- Generating done
-- Build files have been written to: /home/masaaki/OpenCV/opencv/build

make を行った。
make -j $(nproc)


make が成功した。

sudo make install


sudo ldconfig


cmake のログでも出てきたが、OpenCV 3.3.0 rc をインストールしたようだ。

opencv/samples を見てみると、dnn やopencl やいろいろなサンプルがあって楽しみだ。

Ubuntu 16.04 にOpenCV 3.1.0 をインストールした

白線追従用の画像を処理するためにUbuntu 16.04 にOpenCV 3.1.0 をインストールすることにした。
なお、”Ubuntu 16.04にOpenCV 3.1をインストールする手順”を参考にさせていただいた。

早速、下準備から、
sudo apt-get install build-essential cmake git


sudo apt-get install ffmpeg libopencv-dev libgtk-3-dev python-numpy python3-numpy libdc1394-22 libdc1394-22-dev libjpeg-dev libpng12-dev libtiff5-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libxine2-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libv4l-dev libtbb-dev qtbase5-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip


wget https://github.com/Itseez/opencv/archive/3.1.0.zip


unzip 3.1.0


cd opencv-3.1.0
mkdir build
cd build


cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D WITH_V4L=ON -D WITH_QT=ON -D WITH_OPENGL=ON ..


成功した。コンフィギュレーションを貼っておく。

-- General configuration for OpenCV 3.1.0 =====================================
--   Version control:               unknown
-- 
--   Platform:
--     Host:                        Linux 4.4.0-87-generic x86_64
--     CMake:                       3.3.2
--     CMake generator:             Unix Makefiles
--     CMake build tool:            /usr/bin/make
--     Configuration:               RELEASE
-- 
--   C/C++:
--     Built as dynamic libs?:      YES
--     C++ Compiler:                /usr/bin/c++  (ver 5.4.0)
--     C++ flags (Release):         -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wno-narrowing -Wno-delete-non-virtual-dtor -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG  -DNDEBUG
--     C++ flags (Debug):           -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wno-narrowing -Wno-delete-non-virtual-dtor -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -fvisibility-inlines-hidden -g  -O0 -DDEBUG -D_DEBUG
--     C Compiler:                  /usr/bin/cc
--     C flags (Release):           -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wno-narrowing -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -O3 -DNDEBUG  -DNDEBUG
--     C flags (Debug):             -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wno-narrowing -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -msse -msse2 -mno-avx -msse3 -mno-ssse3 -mno-sse4.1 -mno-sse4.2 -ffunction-sections -fvisibility=hidden -g  -O0 -DDEBUG -D_DEBUG
--     Linker flags (Release):
--     Linker flags (Debug):
--     Precompiled headers:         YES
--     Extra dependencies:          Qt5::Core Qt5::Gui Qt5::Widgets Qt5::Test Qt5::Concurrent Qt5::OpenGL /usr/lib/x86_64-linux-gnu/libpng.so /usr/lib/x86_64-linux-gnu/libz.so /usr/lib/x86_64-linux-gnu/libtiff.so /usr/lib/x86_64-linux-gnu/libjasper.so /usr/lib/x86_64-linux-gnu/libjpeg.so /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so gstvideo-1.0 gstapp-1.0 gstbase-1.0 gstriff-1.0 gstpbutils-1.0 gstreamer-1.0 gobject-2.0 glib-2.0 dc1394 v4l1 v4l2 avcodec-ffmpeg avformat-ffmpeg avutil-ffmpeg swscale-ffmpeg dl m pthread rt /usr/lib/x86_64-linux-gnu/libGLU.so /usr/lib/x86_64-linux-gnu/libGL.so tbb atomic cudart nppc nppi npps cufft -L/usr/local/cuda/lib64
--     3rdparty dependencies:       libwebp
-- 
--   OpenCV modules:
--     To be built:                 cudev core cudaarithm flann imgproc ml video cudabgsegm cudafilters cudaimgproc cudawarping imgcodecs photo shape videoio cudacodec highgui objdetect ts features2d calib3d cudafeatures2d cudalegacy cudaobjdetect cudaoptflow cudastereo stitching superres videostab python2
--     Disabled:                    world
--     Disabled by dependency:      -
--     Unavailable:                 java python3 viz
-- 
--   GUI: 
--     QT 5.x:                      YES (ver 5.5.1)
--     QT OpenGL support:           YES (Qt5::OpenGL 5.5.1)
--     OpenGL support:              YES (/usr/lib/x86_64-linux-gnu/libGLU.so /usr/lib/x86_64-linux-gnu/libGL.so)
--     VTK support:                 NO
-- 
--   Media I/O: 
--     ZLib:                        /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.8)
--     JPEG:                        /usr/lib/x86_64-linux-gnu/libjpeg.so (ver )
--     WEBP:                        build (ver 0.3.1)
--     PNG:                         /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.2.54)
--     TIFF:                        /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42 - 4.0.6)
--     JPEG 2000:                   /usr/lib/x86_64-linux-gnu/libjasper.so (ver 1.900.1)
--     OpenEXR:                     /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so (ver 2.2.0)
--     GDAL:                        NO
-- 
--   Video I/O:
--     DC1394 1.x:                  NO
--     DC1394 2.x:                  YES (ver 2.2.4)
--     FFMPEG:                      YES
--       codec:                     YES (ver 56.60.100)
--       format:                    YES (ver 56.40.101)
--       util:                      YES (ver 54.31.100)
--       swscale:                   YES (ver 3.1.101)
--       resample:                  NO
--       gentoo-style:              YES
--     GStreamer:                   
--       base:                      YES (ver 1.8.3)
--       video:                     YES (ver 1.8.3)
--       app:                       YES (ver 1.8.3)
--       riff:                      YES (ver 1.8.3)
--       pbutils:                   YES (ver 1.8.3)
--     OpenNI:                      NO
--     OpenNI PrimeSensor Modules:  NO
--     OpenNI2:                     NO
--     PvAPI:                       NO
--     GigEVisionSDK:               NO
--     UniCap:                      NO
--     UniCap ucil:                 NO
--     V4L/V4L2:                    Using libv4l1 (ver 1.10.0) / libv4l2 (ver 1.10.0)
--     XIMEA:                       NO
--     Xine:                        NO
--     gPhoto2:                     NO
-- 
--   Parallel framework:            TBB (ver 4.4 interface 9002)
-- 
--   Other third-party libraries:
--     Use IPP:                     9.0.1 [9.0.1]
--          at:                     /home/masaaki/opencv-3.1.0/3rdparty/ippicv/unpack/ippicv_lnx
--     Use IPP Async:               NO
--     Use VA:                      NO
--     Use Intel VA-API/OpenCL:     NO
--     Use Eigen:                   NO
--     Use Cuda:                    YES (ver 8.0)
--     Use OpenCL:                  YES
--     Use custom HAL:              NO
-- 
--   NVIDIA CUDA
--     Use CUFFT:                   YES
--     Use CUBLAS:                  NO
--     USE NVCUVID:                 NO
--     NVIDIA GPU arch:             20 21 30 35
--     NVIDIA PTX archs:            30
--     Use fast math:               NO
-- 
--   OpenCL:
--     Version:                     dynamic
--     Include path:                /home/masaaki/opencv-3.1.0/3rdparty/include/opencl/1.2
--     Use AMDFFT:                  NO
--     Use AMDBLAS:                 NO
-- 
--   Python 2:
--     Interpreter:                 /usr/bin/python2.7 (ver 2.7.12)
--     Libraries:                   /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.12)
--     numpy:                       /home/masaaki/.local/lib/python2.7/site-packages/numpy/core/include (ver 1.11.0)
--     packages path:               lib/python2.7/dist-packages
-- 
--   Python 3:
--     Interpreter:                 /usr/bin/python3 (ver 3.5.2)
-- 
--   Python (for build):            /usr/bin/python2.7
-- 
--   Java:
--     ant:                         NO
--     JNI:                         NO
--     Java wrappers:               NO
--     Java tests:                  NO
-- 
--   Matlab:                        Matlab not found or implicitly disabled
-- 
--   Documentation:
--     Doxygen:                     NO
--     PlantUML:                    NO
-- 
--   Tests and samples:
--     Tests:                       YES
--     Performance tests:           YES
--     C/C++ Examples:              NO
-- 
--   Install path:                  /usr/local
-- 
--   cvconfig.h is in:              /home/masaaki/opencv-3.1.0/build
-- -----------------------------------------------------------------
-- 
-- Configuring done
-- Generating done
-- Build files have been written to: /home/masaaki/opencv-3.1.0/build

make


エラーになってしまった。エラー内容を示す。

/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:120:54: error: ‘NppiGraphcutState’ has not been declared
     typedef NppStatus (*init_func_t)(NppiSize oSize, NppiGraphcutState** ppStat
                                                      ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:135:18: error: ‘NppiGraphcutState’ does not name a type
         operator NppiGraphcutState*()
                  ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:141:9: error: ‘NppiGraphcutState’ does not name a type
         NppiGraphcutState* pState;
         ^
In file included from /home/masaaki/opencv-3.1.0/build/modules/cudalegacy/precomp.hpp:75:0:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp: In constructor ‘{anonymous}::NppiGraphcutStateHandler::NppiGraphcutStateHandler(NppiSize, Npp8u*, {anonymous}::init_func_t)’:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:127:39: error: ‘pState’ was not declared in this scope
             nppSafeCall( func(sznpp, &pState, pDeviceMem) );
                                       ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp: In destructor ‘{anonymous}::NppiGraphcutStateHandler::~NppiGraphcutStateHandler()’:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:132:43: error: ‘pState’ was not declared in this scope
             nppSafeCall( nppiGraphcutFree(pState) );
                                           ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:132:49: error: ‘nppiGraphcutFree’ was not declared in this scope
             nppSafeCall( nppiGraphcutFree(pState) );
                                                 ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp: In function ‘void cv::cuda::graphcut(cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::Stream&)’:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:174:51: error: ‘nppiGraphcutGetSize’ was not declared in this scope
     nppSafeCall( nppiGraphcutGetSize(sznpp, &bufsz) );
                                                   ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:182:61: error: ‘nppiGraphcutInitAlloc’ was not declared in this scope
     NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcutInitAll
                                                             ^
In file included from /home/masaaki/opencv-3.1.0/build/modules/cudalegacy/precomp.hpp:75:0:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:191:146: error: ‘nppiGraphcut_32s8u’ was not declared in this scope
 nsp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
                                                                            ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:196:146: error: ‘nppiGraphcut_32f8u’ was not declared in this scope
 nsp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
                                                                            ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp: In function ‘void cv::cuda::graphcut(cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::GpuMat&, cv::cuda::Stream&)’:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:246:52: error: ‘nppiGraphcut8GetSize’ was not declared in this scope
     nppSafeCall( nppiGraphcut8GetSize(sznpp, &bufsz) );
                                                    ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:254:61: error: ‘nppiGraphcut8InitAlloc’ was not declared in this scope
     NppiGraphcutStateHandler state(sznpp, buf.ptr<Npp8u>(), nppiGraphcut8InitAl
                                                             ^
In file included from /home/masaaki/opencv-3.1.0/build/modules/cudalegacy/precomp.hpp:75:0:
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:267:146: error: ‘nppiGraphcut8_32s8u’ was not declared in this scope
 nsp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
                                                                            ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
/home/masaaki/opencv-3.1.0/modules/cudalegacy/src/graphcuts.cpp:274:146: error: ‘nppiGraphcut8_32f8u’ was not declared in this scope
 nsp.step), sznpp, labels.ptr<Npp8u>(), static_cast<int>(labels.step), state) );
                                                                            ^
/home/masaaki/opencv-3.1.0/modules/core/include/opencv2/core/private.cuda.hpp:165:52: note: in definition of macro ‘nppSafeCall’
 #define nppSafeCall(expr)  cv::cuda::checkNppError(expr, __FILE__, __LINE__, CV
                                                    ^
modules/cudalegacy/CMakeFiles/opencv_cudalegacy.dir/build.make:362: ターゲット 'modules/cudalegacy/CMakeFiles/opencv_cudalegacy.dir/src/graphcuts.cpp.o' のレシピで失敗しました
make[2]: *** [modules/cudalegacy/CMakeFiles/opencv_cudalegacy.dir/src/graphcuts.cpp.o] エラー 1
CMakeFiles/Makefile2:9285: ターゲット 'modules/cudalegacy/CMakeFiles/opencv_cudalegacy.dir/all' のレシピで失敗しました
make[1]: *** [modules/cudalegacy/CMakeFiles/opencv_cudalegacy.dir/all] エラー 2
Makefile:160: ターゲット 'all' のレシピで失敗しました
make: *** [all] エラー 2

どうやらCUDA 関係のエラーのようだ。
”opencv3.10 does not support cuda8.0rc? #6677”とかを見ていろいろとやってみたが、うまく行かなかった。
ツィッターでdandelion さんから、「CUDA8だと一部モジュールがビルドできない問題があります。OpenCV 3.2で修正されてます。」と教えて頂いた。
よって、OpenCV 3.2 以降をインストールすることにした。

Vivado HLSのビデオ プロセッシング関数を使用したOpenCVのFPGAアクセラレーション

この記事は”OpenCV Advent Calendar 2016”の23日目の記事として書きます。

１．FPGAのツールについて
FPGAを知らないという方も多いと思うので、ツールについて説明したいと思います。
Xilinx 社のFPGA 用のツールとしてVivado Design Suite - HLx Edition （通称 Vivado） というツールがあります。これでFPGA を開発するわけです。通常はハードウェア記述言語（HDL）という専用の言語を使います。HDL言語の 2 大勢力としてVerilog HDLとVHDL があります。ですが、最近は高位合成ということで、C, C++, Python, Jave などからHDLを合成できるツールが出てきました。そのうちのC, C++ を使ってHDL を合成するツールがVivado にもあります。Vivado HLS です。
なお、Vivado と Vivado HLS は、デバイス限定ではありますが、無料です。だれでも気軽に始められますよ。

２．Vivado HLS（高位合成ツール）
正確に書くとVivado HLS はC, C++ 言語の記述をHDLに変換して、Vivado のIP を作ります。そのIP をVivado にインポートし、Vivado のIP インテグレータのブロックデザイン上にインスタンスして使用します。（CやC++でどこが高位なのかという疑問があると思いますが、ハードウェアはHDLレベルなので、動作を書けるCやC++ でも高位な言語となります）
また、Xilinx 社のFPGAチップとして、Zynq というチップが出ていますが、これはARMプロセッサのCortex-A9 x2 ＋FPGAが搭載されているチップです。Zynq を使用するとC やC++ でOpenCV でソフトウェアとして書いて実行もできますし、ハードウェアに落としてアクセラレーションすることもできます。ただし、OpenCV のコードはハードウェアに独自のライブラリを使っているため一部書き換えが必要です。

Vivado HLS についての資料は”Vivado Design Suite ユーザー ガイド 高位合成 UG902 (v2016.3) 2016 年 10 月 5 日”をご覧ください。215ページの「ビデオ プロセ ッ シング関数」にOpenCV ライブラリのことが記述されています。
”Accelerating OpenCV Applications with Zynq-7000 All Programmable SoC using Vivado HLS Video Libraries XAPP1167 (v3.0) June 24, 2015”に使用例が書いてあります。
もう1つの情報源はXilinx のWiki の”HLS Video Library”です。
Xilinx のCommunity Forum も参考になります。
とにかく情報が少なく、どのような構造になっているのかが、よくわからないのが欠点です。

３．Xilinx社のHLS ビデオライブラリのWikiの内容
Xilinx のWiki の”HLS Video Library”からの引用です。日本語はGoogle翻訳を使用します。
Vivado HLS のHLS ビデオライブラリには、以下に示すライブラリ関数があります。

Video Library Data Structures
HLS Video Libraryには、イメージ、ピクセルなどの基本的なデータ構造を表現するためのテンプレートクラスがいくつか用意されています。これらの名前と使用方法のほとんどは、OpenCVに似ており、FPGAの特殊化と最適化があります。
　hls :: Mat <ROWS、COLS、T>
　hls :: Scalar <N、T>
　hls :: Window <ROWS、COLS、T>
　hls :: LineBuffer <ROWS、COLS、T>

OpenCV interface functions
　IplImage2AXIvideo
　AXIvideo2IplImage
　cvMat2AXIvideo
　AXIvideo2cvMat
　CvMat2AXIvideo
　AXIvideo2CvMat
　IplImage2hlsMat
　hlsMat2IplImage
　cvMat2hlsMat
　hlsMat2cvMat
　CvMat2hlsMat
　hlsMat2CvMat
　CvMat2hlsWindow
　hlsWindow2CvMat

AXI4-Stream I/O Functions
　hls :: AXIvideo2Mat
　hls :: Mat2AXIvideo

Video Processing Functions
　hls::AbsDiff
　hls::AddS
　hls::AddWeighted
　hls::And
　hls::Avg
　hls::AvgSdv
　hls::Cmp
　hls::CmpS
　hls::CornerHarris
　hls::CvtColor
　hls::Dilate
　hls::Duplicate
　hls::EqualizeHist
　hls::Erode
　hls::FASTX
　hls::Filter2D
　hls::GaussianBlur
　hls::Harris
　hls::HoughLines2
　hls::Integral
　hls::InitUndistortRectifyMap
　hls::Max
　hls::MaxS
　hls::Mean
　hls::Merge
　hls::Min
　hls::MinMaxLoc
　hls::MinS
　hls::Mul
　hls::Not
　hls::PaintMask
　hls::Range
　hls::Remap
　hls::Reduce
　hls::Resize
　hls::Set
　hls::Scale
　hls::Sobel
　hls::Split
　hls::SubRS
　hls::SubS
　hls::Sum
　hls::Threshold
　hls::Zero

４．Vivado HLS の操作手順について
これからのXilinx社の高位合成ツールのVivado HLS について簡単に説明します。
Vivado HLSのファイルはテストベンチとソースに分けられます。Vivado HLSのファイル構成や手順を図 1 に示します。

図 1 Vivado HLSのファイル構成や手順

テストベンチが main() 関数があるところで、main() からハードウェア化する関数を呼び出して使用します。テストベンチとハードウェア関数は別のファイルで、それぞれ、Vivado HLS のTest Benchフォルダ、Sourcesフォルダにから関連付けされています。その様子を図 2 に示します。

図 2 Vivado HLS 画面

図 2 で、Sourcesフォルダの opencv_ex_ug.cpp がハードウェア化する関数のファイルで、opencv_ex_ug_tb.cpp がテストベンチです。

図 1 に話を戻すと、ハードウェア関数はCコードの合成を行って、HDLに落とされます。次にIP 化を行って、Vivado で使えるようになります。
この辺りは、話せば相当長くなるので、省略します。

つまり何が言いたかったかというと、ソフトウェアでも実装できて、最初にソフトウェアで動作を確認して、そのままハードウェアに落とすことができます。Vivado_HLS のOpenCVライブラリは通常のOpenCVと違うところもあるので、そのままというわけにはいきませんが、ほとんど同じにできます。
ハードウェアにすると、性能が向上するか？という疑問があると思いますが、ハードウェアに適した課題で、しかもハードウェアに合わせてコードを最適化したり、指示子（ディテクティブ、プラグマで書きます）を適切に追加する必要があります。今のところは、FPGAの構造を熟知していないとチューニングは難しいかもしれません？

５．例1　Sobelフィルタ
それでは実際のC コードを見ていきましょう。最初にSobel フィルタのコード例です。

Vivado HLS 2015.4 で OpenCV を使ってみた3（Sobelフィルタを試した1）

ここでは、シミュレーションだけを行っていて、実機では動作させていません。

６．Vivado HLS のC シミュレーションとC/RTL協調シミュレーション
Vivado HLS にはC シミュレーションとC/RTL協調シミュレーションの2つのシミュレーションがあります。C シミュレーションは普通にC ソースコードをコンパイルして実行します。これは普通のVisual Studio とかでやっているのと同じ普通のC の実行です。
もう1つのC/RTL協調シミュレーションは、ハードウェア化する関数をハードウェアとしてHDL に合成した後に動作を確かめるためにRTL シミュレーター（HDLをテストするシミュレーターです）とC のテストベンチを連動させてシミュレーションするものです。この場合に、HDL にしたときのデータの同一性をチェックするためにテストベンチでOpenCVを使用して処理したデータとRTL シミュレーターの出力データを比較しています。今のところテストベンチはそのように記述されています。図 3 にC/RTL協調シミュレーションのブロック図を示します。

図 3　C/RTL協調シミュレーションのブロック図1

OpenCV では、値が一致しないこともあるので、（近い値になっています）その場合は異常終了しないようにしています。
また、FPGAに落とす場合は、浮動小数点演算のコストが大きく、膨大なリソースを使用するため浮動小数演算を固定小数点演算にする場合が多いです。その場合の誤差を計測するためにもシミュレーションを使用します。その場合のブロック図を図 4 に示します。

図 4　C/RTL協調シミュレーションのブロック図2

７．例2　FASTXコーナー検出
OpenCV のFAST コーナー検出器のHLS ビデオライブラリ版のFASTX コーナー検出器を確かめてみたのがこの記事です。

FASTX コーナー検出の改良3（threshold をソフトウェアで変更可能にする）

ここでは、800 x 600 ピクセルの画像で、リアルタイムにFASTX コーナー検出を行っています。レポートを見ると、

FASTX コーナー検出IP は 280 MHz まで動作するというレポートが出ているので、HD 解像度の 148.5 MHz も問題なくできると思う。そのようにすればHD解像度で、60 fps のFASTX コーナー検出ができると思う。

という結論になりました。かなりの性能が出ていると思われます。

その他、Vivado HLS の記事は、Vivado HLS をご覧ください。

８．実例　ミニロボットカーによる自動走行例
Vivado HLS のHLS ビデオライブラリを使用したハードウェア＋ソフトウェアによる白線追従走行の様子です。カメラを使用した画像解析で白線の間を走っています。


次に同様に、Vivado HLS のHLS ビデオライブラリを使用したハードウェア＋ソフトウェアによるマーカーを使用した隊列走行の様子です。