CamShift + Face detection in OpenCv

I'm currently combing two examples from OpenCv which let you detect your face and track object. The purpose is to first detect the face and then track it. My code currently : ``` import numpy as np import cv2 import cv2.cv as cv import video import math cascade = 0 counter = 0 class App(object): def __init__(self, video_src): self.cam = video.create_capture(video_src) ret, self.frame = self.cam.read() cv2.namedWindow('camshift') self.selection = None self.drag_start = None self.tracking_state = 0 self.show_backproj = False def show_hist(self): bin_count = self.hist.shape[0] bin_w = 24 img = np.zeros((256, bin_count*bin_w, 3), np.uint8) for i in xrange(bin_count): h = int(self.hist[i]) cv2.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1) img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR) cv2.imshow('hist', img) ''' @param: img the image for the face detection @param: cascade the cascade of the ViolaJones face detection @return: rects, an array of the cornors of the detected face. [x1 y1 x2 y2] ''' def detect(self,img, cascade): # Detect the faces rects = cascade.detectMultiScale(img, scaleFactor=1.1, minNeighbors=3, minSize=(150, 150), flags = cv.CV_HAAR_SCALE_IMAGE) # Check if any faces are detected if len(rects) == 0: # return empty array return [] else: # Get the correct x and y values rects[:,2:] += rects[:,:2] # loop over the recs and shrink the width with 40% for rec in rects: rec[0] = rec[0] + int(math.floor(((rec[2] - rec[0])*0.4)/2)) rec[2] = rec[2] - int(math.floor(((rec[2] - rec[0])*0.4)/2)) return rects def draw_rects(self,img, rects, color): for x1, y1, x2, y2 in rects: cv2.rectangle(img, (x1, y1), (x2, y2), color, 2) def getFace(self,img): gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) gray = cv2.equalizeHist(gray) rects = self.detect(gray, cascade) self.rects = rects img = self.draw_rects(img, rects, (0, 255, 0)) if len(rects) != 0: self.selection = rects[0][1], rects[0][0], rects[0][3], rects[0][2] return rects def run(self): counter= 0 rects = None while True: counter +=1; ret, self.frame = self.cam.read() vis = self.frame.copy() if counter % 150 == 0: rects = self.getFace(vis); hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV) mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.))) if rects is not None: self.draw_rects(vis, rects, (0, 255, 0)) if self.selection: print 'test0' x0, y0, x1, y1 = self.selection self.track_window = (x0, y0, x1-x0, y1-y0) hsv_roi = hsv[x0:x1,y0:y1] mask_roi = mask[x0:x1,y0:y1] hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] ) cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX); self.hist = hist.reshape(-1) self.show_hist() vis_roi = vis[x0:x1,y0:y1] cv2.bitwise_not(vis_roi, vis_roi) vis[mask == 0] = 0 self.tracking_state = 1 self.selection = None if self.tracking_state == 1: self.selection = None prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1) prob &= mask term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 ) track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit) if self.show_backproj: vis[:] = prob[...,np.newaxis] try: cv2.ellipse(vis, track_box, (0, 0, 255), 2) except: print track_box cv2.imshow('camshift', vis) ch = 0xFF & cv2.waitKey(5) if ch == 27: break if ch == ord('b'): self.show_backproj = not self.show_backproj cv2.destroyAllWindows() if __name__ == '__main__': import sys, getopt args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade=']) try: video_src = video_src[0] except: video_src = 0 args = dict(args) cascade_fn = args.get('--cascade', "haarcascade_frontalface_alt.xml") cascade = cv2.CascadeClassifier(cascade_fn) App(video_src).run() ``` Currently I show where the face was initially (in a green rectangle) and what is tracked at the moment (in a red oval). I am able to detect the face, but the face tracker keeps tracking all other stuff except for my face (always on one or two shoulders). I suspected it had something to do with the coordinates, but I've checked them and they seem fine (mask_roi, hsv_roi, vis_roi). An example : Can anybody point out my mistake ?