# // https://github.com/jayrambhia/MFTracker
# from mftracker import *
import cv2
# _, img = cap.read()
# _, img = cap.read()
bb = [420,470,36,130]
# cv2.imshow("image", img)
# cv2.waitKey(0)
# mftrack()
# # mftrack("vid_in.mpg" , bb)
import mftracker
mftracker.mftrack("onlyred.mov" )
_, img = cap.read()
_, img = cap.read()
del cap
gray = cv2.cvtColor(img, cv2.cv.CV_BGR2GRAY)
rects = cas.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=3, minSize=(10, 10), flags=cv.CV_HAAR_SCALE_IMAGE)
# rects = cas.detectMultiScale(image=gray,scaleFactor=1.1,minNeighbours=3,flags=cv.CV_HAAR_SCALE_IMAGE,
# minSize=(10, 10))
print rects
if rects is None:
print "No faces found."
sys.exit(1)
for rect in rects:
print rect
cv2.rectangle(img, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] + rect[3]), (255, 0, 0), 3)
cv2.imshow("faces", img)
mftracker.mftrack(0, rect.tolist())
"""
ts = []
cam = Camera()
img0 = cam.getImage()
display = Display()
bb = tuple(rect.tolist())
while display.isNotDone:
img = cam.getImage()
ts = img.track("camshift", ts, img0, bb)
ts.drawBB()
img.show()
"""
rects = cas.detectMultiScale(gray,
scaleFactor=1.1,
minNeighbors=3,
minSize=(10, 10),
flags=cv.CV_HAAR_SCALE_IMAGE)
#rects = cas.detectMultiScale(image=gray,scaleFactor=1.1,minNeighbours=3,flags=cv.CV_HAAR_SCALE_IMAGE,
# minSize=(10, 10))
print rects
if rects is None:
print "No faces found."
sys.exit(1)
for rect in rects:
print rect
cv2.rectangle(img, (rect[0], rect[1]),
(rect[0] + rect[2], rect[1] + rect[3]), (255, 0, 0), 3)
cv2.imshow("faces", img)
mftracker.mftrack(0, rect.tolist())
"""
ts = []
cam = Camera()
img0 = cam.getImage()
display = Display()
bb = tuple(rect.tolist())
while display.isNotDone:
img = cam.getImage()
ts = img.track("camshift", ts, img0, bb)
ts.drawBB()
img.show()
"""
