Notes

from imutils.video import VideoStream
from imutils.video import FPS
import argparse
import imutils
import time
import cv2
import numpy as np


onClick = False
point =(0,0)
endPoint = (0,0)
initBB = None
tracker = None
fps = FPS().start()

def mouse_drawing(event,x,y,flags,param):
global point,endPoint,onClick,initBB,tracker,fps
if event == cv2.EVENT_LBUTTONDOWN and onClick == False:
onClick=True
initBB = None
tracker = OPENCV_OBJECT_TRACKERS[args["tracker"]]()
point = (x,y)
endPoint = (x,y)
elif event == cv2.EVENT_MOUSEMOVE and onClick == True:
endPoint = (x,y)
elif event == cv2.EVENT_LBUTTONUP:
onClick = False
initBB = (point[0],point[1],endPoint[0]-point[0],endPoint[1]-point[1])
tracker.init(frame, initBB)
fps = FPS().start()
elif event == cv2.EVENT_RBUTTONDOWN:
initBB = None
tracker = OPENCV_OBJECT_TRACKERS[args["tracker"]]()



ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", type=str,
help="path to input video file")
ap.add_argument("-t", "--tracker", type=str, default="kcf",
help="OpenCV object tracker type")
args = vars(ap.parse_args())

# extract the OpenCV version info
(major, minor) = cv2.__version__.split(".")[:2]
# if we are using OpenCV 3.2 OR BEFORE, we can use a special factory
# function to create our object tracker
if int(major) == 3 and int(minor) < 3:
tracker = cv2.Tracker_create(args["tracker"].upper())
# otherwise, for OpenCV 3.3 OR NEWER, we need to explicity call the
# approrpiate object tracker constructor:
else:
# initialize a dictionary that maps strings to their corresponding
# OpenCV object tracker implementations
OPENCV_OBJECT_TRACKERS = {
"csrt": cv2.TrackerCSRT_create,
"kcf": cv2.TrackerKCF_create,
"boosting": cv2.TrackerBoosting_create,
"mil": cv2.TrackerMIL_create,
"tld": cv2.TrackerTLD_create,
"medianflow": cv2.TrackerMedianFlow_create,
"mosse": cv2.TrackerMOSSE_create
}
# grab the appropriate object tracker using our dictionary of
# OpenCV object tracker objects


if not args.get("video", False):
print("[INFO] starting video stream...")
vs = VideoStream(src=0).start()
time.sleep(1.0)
# otherwise, grab a reference to the video file
else:
vs = cv2.VideoCapture(args["video"])

cv2.namedWindow("Frame")
cv2.setMouseCallback("Frame",mouse_drawing)

# loop over frames from the video stream
while True:
# grab the current frame, then handle if we are using a
# VideoStream or VideoCapture object
frame = vs.read()
frame = frame[1] if args.get("video", False) else frame
# check to see if we have reached the end of the stream
if frame is None:
break
# resize the frame (so we can process it faster) and grab the
# frame dimensions
if frame is not None:
frame = imutils.resize(frame, width=500)
(H, W) = frame.shape[:2]

if onClick and frame is not None :
cv2.rectangle(frame,point,endPoint,(255,255,255),2)

# check to see if we are currently tracking an object
if initBB is not None:
# grab the new bounding box coordinates of the object
(success, box) = tracker.update(frame)

# check to see if the tracking was a success
if success:
(x, y, w, h) = [int(v) for v in box]
cv2.rectangle(frame, (x, y), (x+w,y+h),
(255, 255, 255), 2)
# update the FPS counter
fps.update()
fps.stop()
# initialize the set of information we'll be displaying on
# the frame
info = [
("Tracker", args["tracker"]),
("Success", "Yes" if success else "No"),
("FPS", "{:.2f}".format(fps.fps())),
]
# loop over the info tuples and draw them on our frame
for (i, (k, v)) in enumerate(info):
text = "{}: {}".format(k, v)
cv2.putText(frame, text, (10, H - ((i * 20) + 20)),
cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 255, 0), 2)
# show the output frame
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the 's' key is selected, we are going to "select" a bounding
# box to track
if key == ord("q"):
break
# if we are using a webcam, release the pointer
if not args.get("video", False):
vs.stop()
# otherwise, release the file pointer
else:
vs.release()
# close all windows
cv2.destroyAllWindows()