Opencv Python program za prepoznavanje lica

Opencv Python program za prepoznavanje lica

Cilj navedenog programa je detektirati predmet interesa (lice) u stvarnom vremenu i nastaviti pratiti isti objekt. Ovo je jednostavan primjer kako detektirati lice u Pythonu. Možete pokušati upotrijebiti uzorke za uvježbavanje bilo kojeg drugog objekta po vašem izboru koji će biti otkriven uvježbavanjem klasifikatora na traženim objektima. U nastavku su navedeni koraci za preuzimanje zahtjeva.

koraci:

  1. Preuzmite Python 2.7.x verziju numpy i Opencv 2.7.x verziju. Provjerite je li vaš Windows 32-bitni ili 64-bitni kompatibilan i instalirajte ga u skladu s tim.
  2. Provjerite radi li numpy u vašem pythonu, a zatim pokušajte instalirati opencv.
  3. Stavite datoteke haarcascade_eye.xml i haarcascade_frontalface_default.xml u istu mapu (veze dane u donjem kodu).

Provedba

Python
   # OpenCV program to detect face in real time   # import libraries of python OpenCV    # where its functionality resides   import   cv2   # load the required trained XML classifiers   # https://github.com/opencv/opencv/tree/master   # data/haarcascades/haarcascade_frontalface_default.xml   # Trained XML classifiers describes some features of some   # object we want to detect a cascade function is trained   # from a lot of positive(faces) and negative(non-faces)   # images.   face_cascade   =   cv2  .  CascadeClassifier  (  'haarcascade_frontalface_default.xml'  )   # https://github.com/opencv/opencv/tree/master   # /data/haarcascades/haarcascade_eye.xml   # Trained XML file for detecting eyes   eye_cascade   =   cv2  .  CascadeClassifier  (  'haarcascade_eye.xml'  )   # capture frames from a camera   cap   =   cv2  .  VideoCapture  (  0  )   # loop runs if capturing has been initialized.   while   1  :   # reads frames from a camera   ret     img   =   cap  .  read  ()   # convert to gray scale of each frames   gray   =   cv2  .  cvtColor  (  img     cv2  .  COLOR_BGR2GRAY  )   # Detects faces of different sizes in the input image   faces   =   face_cascade  .  detectMultiScale  (  gray     1.3     5  )   for   (  x    y    w    h  )   in   faces  :   # To draw a rectangle in a face    cv2  .  rectangle  (  img  (  x    y  )(  x  +  w    y  +  h  )(  255    255    0  )  2  )   roi_gray   =   gray  [  y  :  y  +  h     x  :  x  +  w  ]   roi_color   =   img  [  y  :  y  +  h     x  :  x  +  w  ]   # Detects eyes of different sizes in the input image   eyes   =   eye_cascade  .  detectMultiScale  (  roi_gray  )   #To draw a rectangle in eyes   for   (  ex    ey    ew    eh  )   in   eyes  :   cv2  .  rectangle  (  roi_color  (  ex    ey  )(  ex  +  ew    ey  +  eh  )(  0    127    255  )  2  )   # Display an image in a window   cv2  .  imshow  (  'img'    img  )   # Wait for Esc key to stop   k   =   cv2  .  waitKey  (  30  )   &   0xff   if   k   ==   27  :   break   # Close the window   cap  .  release  ()   # De-allocate any associated memory usage   cv2  .  destroyAllWindows  ()   

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