multi object tracking py.txt

# USAGE # python --video videos/soccer_01.mp4 --tracker csrt # import the necessary packages from 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 = 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()