Pattern recognition learning in video Part 1 Field of Pattern Recognition

background

Learning material

How to proceed with learning

How to install OpenCV (2014/5) * Mac OS X, Mountain Lion *

http://www.jeffreythompson.org/blog/2013/08/22/update-installing-opencv-on-mac-mountain-lion/ Reference

Video playback

import numpy as np
import cv2

cap = cv2.VideoCapture('Full path to video')

while(cap.isOpened()):
    ret, frame = cap.read()

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    cv2.imshow('frame',gray)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

http://docs.opencv.org/trunk/doc/py_tutorials/py_gui/py_video_display/py_video_display.html#display-video

Object tracking in video

MeanShift algorithm

Current source code

import numpy as np
import cv2

cap = cv2.VideoCapture('Full path to video')

ret,frame = cap.read()

r,h,c,w = 150,90,650,125
track_window = (c,r,w,h)

roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi,cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0.,60.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)


term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )

while(1):
  ret,frame = cap.read()

  if ret == True:
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,180],1)

    ret,track_window = cv2.meanShift(dst, track_window, term_crit)

    x,y,w,h = track_window
    img2 = cv2.rectangle(frame,(x,y),(x+w,y+h),255,2)
    cv2.imshow('img2',frame)

    k = cv2.waitKey(60) & 0xff
    if k == 27:
      break
    else:
      cv2.imwrite(chr(k)+".jpg ",img2)

  else:
    break

cv2.destroyAllWindows()
cap.release()

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