object-detection

README.md

これはなに？

春休みの自由研究として固定抵抗の物体検出をOpenCVでやろうとしたときに書いたスクリプトの中から、将来的に再び使用することになるであろうものをとりあえず残しておいたもの。

有用な資料

• 座標内の矩形座標取得
• OpenCVの環境構築と導入
• 物体検出徹底解説！
• OpenCVを使った機械学習
• OpenCVで学ぶ画像認識 オブジェクト検出器の作成方法
• OpenCVのカスケード分類器の学習の章を訳してみた

crop.py

from PIL import Image

def main():
  ok_file = 'OK.txt'

  with open(ok_file) as f:
    k = 0
    for line in f:
      seq = line.split()
      imgname = seq[0]
      im = Image.open(imgname)

      numobj = int(seq[1])
      for i in xrange(numobj):
        x, y, w, h = map(int, seq[2+i*4:2+i*4+4])
        box = (x, y, x+w, y+h)
        im.crop(box).save('OK_samples/{0}.jpg'.format(k))
        k += 1

if __name__ == '__main__':
  main()

detect.cpp

#include <cstdio>

#include <vector>

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
int main(int argc, const char *argv[]) {
  const char *exename = *argv;
  --argc; ++argv;

  if(argc == 0) {
    fprintf(stderr, "usage: %s <img>", exename);
    exit(EXIT_FAILURE);
  }

  const char *fname = *argv;
  --argc; ++argv;

  cv::Mat img = cv::imread(fname);
  if(img.empty()) {
    perror(fname);
    exit(EXIT_FAILURE);
  }

  const char *cascadeName = "./resistor_cascade.xml";
  cv::CascadeClassifier cascade;
  if(!cascade.load(cascadeName)) {
    perror(cascadeName);
    exit(EXIT_FAILURE);
  }

  cv::Mat gray;
  cv::cvtColor(img, gray, CV_RGB2GRAY);

  
  std::vector<cv::Rect> rects;
  cascade.detectMultiScale(gray, rects);

  for (const cv::Rect &rect : rects) {
    cv::rectangle(img, rect, cv::Scalar(255, 0, 0));
  }

  const char *windowName = "window";
  cv::namedWindow(windowName, CV_WINDOW_NORMAL | CV_WINDOW_KEEPRATIO);
  cv::imshow(windowName, img);
  cv::waitKey();
}

hist.cpp

#include <cstdio>

#include <opencv2/core/core.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>

int main(int argc, const char *argv[]) {
  --argc; ++argv;

  const char *fname = "image.jpg";
  if (argc > 0) {
    fname = *argv;
    --argc; ++argv;
  }

  cv::Mat src = cv::imread(fname);
  if(src.empty()) {
    perror(fname);
    exit(EXIT_FAILURE);
  }

  cv::Mat gray;
  cv::cvtColor(src, gray, CV_RGB2GRAY);

  cv::Mat dst;
  cv::equalizeHist(gray, dst);

  const char *src_window = "src";
  const char *dst_window = "dst";

  cv::namedWindow(src_window);
  cv::imshow(src_window, gray);

  cv::namedWindow(dst_window);
  cv::imshow(dst_window, dst);

  cv::waitKey();
}

mv.py

import glob
import os
import shutil

files = glob.glob('**/*.jpg')
for f in files:
  # print f, os.path.join('~/resistor/NG', os.path.dirname(f) + '-' + os.path.basename(f))
  shutil.move(f, os.path.join('/home/arosh/resistor/NG', os.path.dirname(f) + '-' + os.path.basename(f)))

script.py

import os
import glob
import numpy as np
from PIL import Image

def main():
  images = glob.glob('OK_samples/*.jpg')
  k = 0
  for fname in images:
    im = np.array(Image.open(fname).convert('L'))
    edge = []

    for y in xrange(im.shape[0]):
      edge.append(im[y,0])
      edge.append(im[y,-1])

    for x in xrange(1,im.shape[1]-1):
      edge.append(im[0,x])
      edge.append(im[-1,x])

    edge = np.array(edge)
    median = int(np.median(edge))
    thresh = min(int(np.std(edge)), 20)
    command = 'opencv_createsamples -img {} -vec OK_vecs/{}.vec -bg NG.txt -num 40 -bgcolor {} -bgthresh {}'.format(fname, k, median, thresh)
    print command

    k += 1

if __name__ == '__main__':
  main()