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multipleWindows_playeMOUSEEVENT.py
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multipleWindows_playeMOUSEEVENT.py
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import numpy as np
import cv2
from time import time
boxes = []
def on_mouse(event, x, y, flags, params):
# global img
t = time()
if event == cv2.cv.CV_EVENT_LBUTTONDBLCLK:
print 'Start Mouse Position: '+str(x)+', '+str(y)
sbox = [x, y]
boxes.append(sbox)
# print count
# print sbox
elif event == cv2.cv.CV_EVENT_MBUTTONDBLCLK:
print 'End Mouse Position: '+str(x)+', '+str(y)
ebox = [x, y]
boxes.append(ebox)
print boxes
crop = img[boxes[-2][1]:boxes[-1][1],boxes[-2][0]:boxes[-1][0]]
cv2.imshow('crop',crop)
k = cv2.waitKey(0)
if ord('r')== k:
cv2.imwrite('Crop'+str(t)+'.jpg',crop)
print "Written to file"
count = 0
while(1):
count += 1
img = cv2.imread('FIRST_FRAME.PNG',1)
# img = cv2.blur(img, (3,3))
# img = cv2.resize(img, None, fx = 0.25,fy = 0.25)
cv2.namedWindow('real image')
cv2.cv.SetMouseCallback('real image', on_mouse, 0)
cv2.imshow('real image', img)
if count < 50:
if cv2.waitKey(33) == 27:
cv2.destroyAllWindows()
break
elif count >= 50:
if cv2.waitKey(0) == 27:
cv2.destroyAllWindows()
break
count = 0
cap = cv2.VideoCapture('videofu.avi')
# take first frame of the video
ret,frame = cap.read()
# setup initial location of window
r,h,c,w = boxes[0][1],boxes[1][1]-boxes[0][1],boxes[0][0],boxes[1][0]-boxes[0][0] # simply hardcoded the values player2
#row, hight of the window, col, width of the window
#ddddd = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
ddddd = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
for i in range(boxes[0][1],boxes[1][1]):
for j in range(boxes[0][0],boxes[1][0]):
print i," ",j," ",ddddd[i,j,:]
meann= np.mean(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],0])
stddeviation = np.std(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],0])
meann2= np.mean(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],1])
stddeviation2 = np.std(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],1])
meann3= np.mean(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],2])
stddeviation3 = np.std(ddddd[boxes[0][1]:boxes[1][1],boxes[0][0]:boxes[1][0],2])
track_window = (c,r,w,h)
# set up the ROI for tracking
roi = frame[r:r+h, c:c+w]
hsv_roi = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
#asdroi = frame[r:r+h, c:c+w]
#asdsd_roi = cv2.cvtColor(asdroi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((meann-stddeviation, meann2-stddeviation2,meann3-stddeviation3)), np.array((meann+stddeviation,meann2+stddeviation2,meann3+stddeviation3)))
roi_hist = cv2.calcHist([hsv_roi],[0],mask,[180],[0,180])
cv2.normalize(roi_hist,roi_hist,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, 100, 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)
# apply meanshift to get the new location
ret, track_window = cv2.meanShift(dst, track_window, term_crit)
# Draw it on image
x,y,w,h = track_window
cv2.rectangle(frame, (x,y), (x+w,y+h), 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()