# // 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() """