# USAGE
# python multi_object_tracking.py --video videos/soccer_01.mp4 --tracker csrt

# import the necessary packages
from imutils.video import VideoStream
import argparse
import imutils
import time
import cv2

# construct the argument parser and parse the arguments
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())

# 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
}

# initialize OpenCV's special multi-object tracker
trackers = cv2.MultiTracker_create()

# if a video path was not supplied, grab the reference to the web cam
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"])

# 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)
frame = imutils.resize(frame, width=600)

# grab the updated bounding box coordinates (if any) for each
# object that is being tracked
(success, boxes) = trackers.update(frame)

# loop over the bounding boxes and draw then on the frame
for box in boxes:
(x, y, w, h) = [int(v) for v in box]
cv2.rectangle(frame, (x, y), (x + w, y + h), (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("s"):
# select the bounding box of the object we want to track (make
# sure you press ENTER or SPACE after selecting the ROI)
box = cv2.selectROI("Frame", frame, fromCenter=False,
showCrosshair=True)

# create a new object tracker for the bounding box and add it
# to our multi-object tracker
tracker = OPENCV_OBJECT_TRACKERS[args["tracker"]]()
trackers.add(tracker, frame, box)

# if the `q` key was pressed, break from the loop
elif 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()