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#!/usr/bin/env python
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'''
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Tracker demo
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For usage download models by following links
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For GOTURN:
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goturn.prototxt and goturn.caffemodel: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking
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For DaSiamRPN:
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network: https://www.dropbox.com/s/rr1lk9355vzolqv/dasiamrpn_model.onnx?dl=0
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kernel_r1: https://www.dropbox.com/s/999cqx5zrfi7w4p/dasiamrpn_kernel_r1.onnx?dl=0
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kernel_cls1: https://www.dropbox.com/s/qvmtszx5h339a0w/dasiamrpn_kernel_cls1.onnx?dl=0
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USAGE:
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tracker.py [-h] [--input INPUT] [--tracker_algo TRACKER_ALGO]
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[--goturn GOTURN] [--goturn_model GOTURN_MODEL]
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[--dasiamrpn_net DASIAMRPN_NET]
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[--dasiamrpn_kernel_r1 DASIAMRPN_KERNEL_R1]
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[--dasiamrpn_kernel_cls1 DASIAMRPN_KERNEL_CLS1]
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[--dasiamrpn_backend DASIAMRPN_BACKEND]
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[--dasiamrpn_target DASIAMRPN_TARGET]
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'''
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# Python 2/3 compatibility
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from __future__ import print_function
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import sys
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import numpy as np
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import cv2 as cv
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import argparse
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from video import create_capture, presets
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class App(object):
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def __init__(self, args):
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self.args = args
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def initializeTracker(self, image, trackerAlgorithm):
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while True:
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if trackerAlgorithm == 'mil':
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tracker = cv.TrackerMIL_create()
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elif trackerAlgorithm == 'goturn':
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params = cv.TrackerGOTURN_Params()
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params.modelTxt = self.args.goturn
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params.modelBin = self.args.goturn_model
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tracker = cv.TrackerGOTURN_create(params)
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elif trackerAlgorithm == 'dasiamrpn':
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params = cv.TrackerDaSiamRPN_Params()
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params.model = self.args.dasiamrpn_net
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params.kernel_cls1 = self.args.dasiamrpn_kernel_cls1
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params.kernel_r1 = self.args.dasiamrpn_kernel_r1
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tracker = cv.TrackerDaSiamRPN_create(params)
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else:
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sys.exit("Tracker {} is not recognized. Please use one of three available: mil, goturn, dasiamrpn.".format(trackerAlgorithm))
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print('==> Select object ROI for tracker ...')
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bbox = cv.selectROI('tracking', image)
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print('ROI: {}'.format(bbox))
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try:
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tracker.init(image, bbox)
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except Exception as e:
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print('Unable to initialize tracker with requested bounding box. Is there any object?')
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print(e)
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print('Try again ...')
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continue
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return tracker
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def run(self):
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videoPath = self.args.input
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trackerAlgorithm = self.args.tracker_algo
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camera = create_capture(videoPath, presets['cube'])
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if not camera.isOpened():
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sys.exit("Can't open video stream: {}".format(videoPath))
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ok, image = camera.read()
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if not ok:
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sys.exit("Can't read first frame")
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assert image is not None
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cv.namedWindow('tracking')
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tracker = self.initializeTracker(image, trackerAlgorithm)
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print("==> Tracking is started. Press 'SPACE' to re-initialize tracker or 'ESC' for exit...")
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while camera.isOpened():
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ok, image = camera.read()
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if not ok:
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print("Can't read frame")
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break
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ok, newbox = tracker.update(image)
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#print(ok, newbox)
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if ok:
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cv.rectangle(image, newbox, (200,0,0))
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cv.imshow("tracking", image)
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k = cv.waitKey(1)
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if k == 32: # SPACE
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tracker = self.initializeTracker(image)
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if k == 27: # ESC
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break
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print('Done')
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if __name__ == '__main__':
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print(__doc__)
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parser = argparse.ArgumentParser(description="Run tracker")
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parser.add_argument("--input", type=str, default="vtest.avi", help="Path to video source")
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parser.add_argument("--tracker_algo", type=str, default="mil", help="One of three available tracking algorithms: mil, goturn, dasiamrpn")
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parser.add_argument("--goturn", type=str, default="goturn.prototxt", help="Path to GOTURN architecture")
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parser.add_argument("--goturn_model", type=str, default="goturn.caffemodel", help="Path to GOTERN model")
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parser.add_argument("--dasiamrpn_net", type=str, default="dasiamrpn_model.onnx", help="Path to onnx model of DaSiamRPN net")
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parser.add_argument("--dasiamrpn_kernel_r1", type=str, default="dasiamrpn_kernel_r1.onnx", help="Path to onnx model of DaSiamRPN kernel_r1")
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parser.add_argument("--dasiamrpn_kernel_cls1", type=str, default="dasiamrpn_kernel_cls1.onnx", help="Path to onnx model of DaSiamRPN kernel_cls1")
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parser.add_argument("--dasiamrpn_backend", type=int, default=0, help="Choose one of computation backends:\
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0: automatically (by default),\
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1: Halide language (http://halide-lang.org/),\
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2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit),\
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3: OpenCV implementation")
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parser.add_argument("--dasiamrpn_target", type=int, default=0, help="Choose one of target computation devices:\
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0: CPU target (by default),\
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1: OpenCL,\
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2: OpenCL fp16 (half-float precision),\
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3: VPU")
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args = parser.parse_args()
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App(args).run()
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cv.destroyAllWindows()
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