dlib_slow.py

from imutils.video import FPS
import numpy as np
import argparse
import imutils
import dlib
import cv2
from face_recognizer import FaceRecognizer
import time



trackers = []
labels = []


cap=cv2.VideoCapture(0)
fce=FaceRecognizer()
fps = FPS().start()

while True:
        (ret, frame) = cap.read()
        if frame is None:
        	break

        frame = imutils.resize(frame, width=600)
        rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

        if len(trackers) == 0:
                rect=[]
                img,rects,names=fce.get_faces(frame,rect)
                print(rects)
                print(names)

                # loop over the detections
                for i in range(len(rects)):

                		label = 'tracking '+names[i]



                		# compute the (x, y)-coordinates of the bounding box
                		# for the object

                		(startX, startY, endX, endY) = rects[i]

                		# construct a dlib rectangle object from the bounding
                		# box coordinates and start the correlation tracker
                		t = dlib.correlation_tracker()
                		rect = dlib.rectangle(startX, startY, endX, endY)
                		t.start_track(rgb, rect)

                		# update our set of trackers and corresponding class
                		# labels
                		labels.append(label)
                		trackers.append(t)

                		# grab the corresponding class label for the detection
                		# and draw the bounding box
                		cv2.rectangle(frame, (startX, startY), (endX, endY),
                			(0, 255, 0), 2)
                		cv2.putText(frame, label, (startX, startY - 15),
                			cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 255, 0), 2)

        # otherwise, we've already performed detection so let's track
        # multiple objects
        else:
        	# loop over each of the trackers
        	for (t, l) in zip(trackers, labels):
        		# update the tracker and grab the position of the tracked
        		# object
        		t.update(rgb)
        		pos = t.get_position()

        		# unpack the position object
        		startX = int(pos.left())
        		startY = int(pos.top())
        		endX = int(pos.right())
        		endY = int(pos.bottom())

        		# draw the bounding box from the correlation object tracker
        		cv2.rectangle(frame, (startX, startY), (endX, endY),(0, 255, 0), 2)
        		cv2.putText(frame, l, (startX, startY - 15),cv2.FONT_HERSHEY_SIMPLEX, 0.45, (0, 255, 0), 2)

        cv2.imshow("Frame", frame)
        cv2.imshow('face',img)
        key = cv2.waitKey(1) & 0xFF

        # if the `q` key was pressed, break from the loop
        if key == ord("q"):
        	break

        # update the FPS counter
        fps.update()

# stop the timer and display FPS information
fps.stop()
print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))

cv2.destroyAllWindows()