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multipleWindows_5player.py
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multipleWindows_5player.py
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import numpy as np
import cv2
cap = cv2.VideoCapture('videofu.avi')
# take first frame of the video
ret,frame = cap.read()
# setup initial location of window
r,h,c,w = 360,40,2310,15 # simply hardcoded the values player#6
r1,h1,c1,w1 = 231,20,2281,10 # simply hardcoded the values player#5
r2,h2,c2,w2 = 224,20,2078,10 # simply hardcoded the values player#2
r3,h3,c3,w3 = 312,25,2640,15 # simply hardcoded the values player#9
r4,h4,c4,w4 = 203,20,2352,10 # simply hardcoded the values player#7
#row, hight of the window, col, width of the window
ddddd = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
for i in range(202,215):
for j in range(2354,2360):
print i," ",j," ",ddddd[i,j,:]
track_window = (c,r,w,h)
track_window1 = (c1,r1,w1,h1)
track_window2 = (c2,r2,w2,h2)
track_window3 = (c3,r3,w3,h3)
track_window4 = (c4,r4,w4,h4)
# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
roi1 = frame[r1:r1+h1, c1:c1+w1]
roi2 = frame[r2:r2+h2, c2:c2+w2]
roi3 = frame[r3:r3+h3, c3:c3+w3]
roi4 = frame[r4:r4+h4, c4:c4+w4]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
hsv_roi1 = cv2.cvtColor(roi1, cv2.COLOR_BGR2HSV)
hsv_roi2 = cv2.cvtColor(roi2, cv2.COLOR_BGR2HSV)
hsv_roi3 = cv2.cvtColor(roi3, cv2.COLOR_BGR2HSV)
hsv_roi4 = cv2.cvtColor(roi4, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 180.,130.)), np.array((8.,255.,200.)))
mask1 = cv2.inRange(hsv_roi1, np.array((0., 180.,130.)), np.array((8.,255.,200.)))
mask2 = cv2.inRange(hsv_roi2, np.array((0., 180.,130.)), np.array((8.,255.,200.)))
mask3 = cv2.inRange(hsv_roi3, np.array((0., 180.,130.)), np.array((8.,255.,200.)))#((30., 50.,140.)), np.array((172.,200.,255.)))
mask4 = cv2.inRange(hsv_roi4, np.array((0., 100.,100.)), np.array((18.,200.,200.)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
roi_hist1 = cv2.calcHist([hsv_roi1],[0],mask1,[180],[0,180])
roi_hist2 = cv2.calcHist([hsv_roi2],[0],mask2,[180],[0,180])
roi_hist3 = cv2.calcHist([hsv_roi3],[0],mask3,[180],[0,180])
roi_hist4 = cv2.calcHist([hsv_roi4],[0],mask4,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,0,255,cv2.NORM_MINMAX)
cv2.normalize(roi_hist1,roi_hist1,0,255,cv2.NORM_MINMAX)
cv2.normalize(roi_hist2,roi_hist2,0,255,cv2.NORM_MINMAX)
cv2.normalize(roi_hist3,roi_hist3,0,255,cv2.NORM_MINMAX)
cv2.normalize(roi_hist4,roi_hist4,0,255,cv2.NORM_MINMAX)
# Setup the termination criteria, either 10 iteration or move by atleast 1 pt
term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
count=0
while(cap.isOpened()):
ret ,frame = cap.read()
count+=1
if ret == True:
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv],[0],roi_hist,[0,180],1)
dst1 = cv2.calcBackProject([hsv],[0],roi_hist1,[0,180],1)
dst2 = cv2.calcBackProject([hsv],[0],roi_hist2,[0,180],1)
dst3 = cv2.calcBackProject([hsv],[0],roi_hist3,[0,180],1)
dst4 = cv2.calcBackProject([hsv],[0],roi_hist4,[0,180],1)
# apply meanshift to get the new location
ret, track_window = cv2.meanShift(dst, track_window, term_crit)
ret1, track_window1 = cv2.meanShift(dst1, track_window1, term_crit)
ret2, track_window2 = cv2.meanShift(dst2, track_window2, term_crit)
ret3, track_window3 = cv2.meanShift(dst3, track_window3, term_crit)
ret4, track_window4 = cv2.meanShift(dst4, track_window4, term_crit)
# Draw it on image
x,y,w,h = track_window
x1,y1,w1,h1 = track_window1
x2,y2,w2,h2 = track_window2
x3,y3,w3,h3 = track_window3
x4,y4,w4,h4 = track_window4
cv2.rectangle(frame, (x,y), (x+w,y+h), 255,2)
cv2.rectangle(frame, (x1,y1), (x1+w1,y1+h1), 255,2)
cv2.rectangle(frame, (x2,y2), (x2+w2,y2+h2), 255,2)
cv2.rectangle(frame, (x3,y3), (x3+w3,y3+h3), 255,2)
cv2.rectangle(frame, (x4,y4), (x4+w4,y4+h4), 255,2)
# box = cv2.cv.BoxPoints(rect)
# box = np.int0(box)
# print ('x = ', x+w/2)
# print ('y = ', y+h/2)
# Draw it on image
# pts = cv2.boxPoints(ret)
# pts = np.int0(pts)
# img2 = cv2.polylines(frame,[pts],True, 255,2)
cv2.namedWindow('frame', cv2.WINDOW_OPENGL)
cv2.imshow('frame',frame)
k = cv2.waitKey(60) & 0xff
if count==1:
cv2.imwrite("fffaaaa.jpg",frame)
if k == 27:
break
# else:
# cv2.imwrite(chr(k)+".jpg",img2)
else:
break
cv2.destroyAllWindows()
cap.release()