meanShiftTrack.py

'''
Created on Sep 9, 2017

@author: inayat
'''

# import the required  packages
from imutils.video import WebcamVideoStream
#from imutils.video import FPS
import numpy as np
import argparse
import imutils
import time
import cv2

from utils.fps2 import FPS2

import dlib

from trackers.meanshifttracker import MeanShiftTracker


    
if __name__ == '__main__':
    
   
    
       
    
    print("[info] starting to read a webcam ...")
    capWebCam = WebcamVideoStream(0).start()
    time.sleep(1.0)
    
    
    # initialize dlib face detector
    
    frontFaceDetector = dlib.get_frontal_face_detector() 
    
    
    # meanShift tracker
    
    meanShifTracker = None
    
    curWindow = None
    
    # start the frame per second  (FPS) counter
    #fps = FPS2().start() 
    
    
    boolDetectFaceinfirsFrameOnly = True
    
    
    
    # loop over the frames obtained from the webcam
    while True:
        # grab each frame from the threaded  stream,
        # resize
        # it, and convert it to grayscale (while still retaining 3
        # channels)
        frame1 = capWebCam.read()
        frame = cv2.flip(frame1,1)
        
        
        #frame = imutils.resize(frame, width=450)
        #frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        #frame = np.dstack([frame, frame, frame])
        
        # display the size of the queue on the frame
        #cv2.putText(frame, "Queue Size: {}".format(fvs.Q.qsize()),
        #            (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
        
        
        if boolDetectFaceinfirsFrameOnly:
            
            faceRect = frontFaceDetector(frame, 0)
            
            if(len(faceRect) == 0):
                continue
            
            
            # start the frame per second  (FPS) counter
            fps = FPS2().start()
            
            bbox = faceRect[0]
            
                        
            # convert dlib rect to opencv rect
            
            curWindow = (int(bbox.left()), int(bbox.top()), int(bbox.right() - bbox.left()),
                         int(bbox.bottom() - bbox.top()) )
            
            # intialize the meanShift Tracker
            meanShifTracker = MeanShiftTracker(curWindow, frame)
            
            boolDetectFaceinfirsFrameOnly = False
            
            
             
            continue 
        
        
            
        
        meanShifTracker.computeNewWindow(frame)
        
        x,y, w, h = meanShifTracker.getCurWindow()
        
        bkprojectImage = meanShifTracker.getBackProjectedImage(frame)
        
        cv2.imshow("MeanShift Face in Back Project Image", bkprojectImage)
        
        
          
        cv2.rectangle(frame, (x,y), (x+w, y+h), (255, 0, 0), 2, cv2.LINE_AA)
           
        
        fps.update()
        cv2.putText(frame, "FPS: {:.2f}".format(fps.fps()),
                    (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
        
        
        # show the frame and update the FPS counter
        cv2.imshow("MeanShift Face Tracking", frame)
        
        k = cv2.waitKey(10) & 0xff
        if k == 27:
            break
        
        
        
        
    # stop the timer and display FPS information
    fps.stop()
    print("[INFO] elasped time: {:.2f}".format(fps.elapsed()))
    print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))
    
    # do a bit of cleanup
    cv2.destroyAllWindows()
    capWebCam.stop()