f4334277
 Hu Chunming
提交3rdparty
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#!/usr/bin/env python
'''
Tracker demo
For usage download models by following links
For GOTURN:
goturn.prototxt and goturn.caffemodel: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking
For DaSiamRPN:
network: https://www.dropbox.com/s/rr1lk9355vzolqv/dasiamrpn_model.onnx?dl=0
kernel_r1: https://www.dropbox.com/s/999cqx5zrfi7w4p/dasiamrpn_kernel_r1.onnx?dl=0
kernel_cls1: https://www.dropbox.com/s/qvmtszx5h339a0w/dasiamrpn_kernel_cls1.onnx?dl=0
USAGE:
tracker.py [-h] [--input INPUT] [--tracker_algo TRACKER_ALGO]
[--goturn GOTURN] [--goturn_model GOTURN_MODEL]
[--dasiamrpn_net DASIAMRPN_NET]
[--dasiamrpn_kernel_r1 DASIAMRPN_KERNEL_R1]
[--dasiamrpn_kernel_cls1 DASIAMRPN_KERNEL_CLS1]
[--dasiamrpn_backend DASIAMRPN_BACKEND]
[--dasiamrpn_target DASIAMRPN_TARGET]
'''
# Python 2/3 compatibility
from __future__ import print_function
import sys
import numpy as np
import cv2 as cv
import argparse
from video import create_capture, presets
class App(object):
def __init__(self, args):
self.args = args
def initializeTracker(self, image, trackerAlgorithm):
while True:
if trackerAlgorithm == 'mil':
tracker = cv.TrackerMIL_create()
elif trackerAlgorithm == 'goturn':
params = cv.TrackerGOTURN_Params()
params.modelTxt = self.args.goturn
params.modelBin = self.args.goturn_model
tracker = cv.TrackerGOTURN_create(params)
elif trackerAlgorithm == 'dasiamrpn':
params = cv.TrackerDaSiamRPN_Params()
params.model = self.args.dasiamrpn_net
params.kernel_cls1 = self.args.dasiamrpn_kernel_cls1
params.kernel_r1 = self.args.dasiamrpn_kernel_r1
tracker = cv.TrackerDaSiamRPN_create(params)
else:
sys.exit("Tracker {} is not recognized. Please use one of three available: mil, goturn, dasiamrpn.".format(trackerAlgorithm))
print('==> Select object ROI for tracker ...')
bbox = cv.selectROI('tracking', image)
print('ROI: {}'.format(bbox))
try:
tracker.init(image, bbox)
except Exception as e:
print('Unable to initialize tracker with requested bounding box. Is there any object?')
print(e)
print('Try again ...')
continue
return tracker
def run(self):
videoPath = self.args.input
trackerAlgorithm = self.args.tracker_algo
camera = create_capture(videoPath, presets['cube'])
if not camera.isOpened():
sys.exit("Can't open video stream: {}".format(videoPath))
ok, image = camera.read()
if not ok:
sys.exit("Can't read first frame")
assert image is not None
cv.namedWindow('tracking')
tracker = self.initializeTracker(image, trackerAlgorithm)
print("==> Tracking is started. Press 'SPACE' to re-initialize tracker or 'ESC' for exit...")
while camera.isOpened():
ok, image = camera.read()
if not ok:
print("Can't read frame")
break
ok, newbox = tracker.update(image)
#print(ok, newbox)
if ok:
cv.rectangle(image, newbox, (200,0,0))
cv.imshow("tracking", image)
k = cv.waitKey(1)
if k == 32: # SPACE
tracker = self.initializeTracker(image)
if k == 27: # ESC
break
print('Done')
if __name__ == '__main__':
print(__doc__)
parser = argparse.ArgumentParser(description="Run tracker")
parser.add_argument("--input", type=str, default="vtest.avi", help="Path to video source")
parser.add_argument("--tracker_algo", type=str, default="mil", help="One of three available tracking algorithms: mil, goturn, dasiamrpn")
parser.add_argument("--goturn", type=str, default="goturn.prototxt", help="Path to GOTURN architecture")
parser.add_argument("--goturn_model", type=str, default="goturn.caffemodel", help="Path to GOTERN model")
parser.add_argument("--dasiamrpn_net", type=str, default="dasiamrpn_model.onnx", help="Path to onnx model of DaSiamRPN net")
parser.add_argument("--dasiamrpn_kernel_r1", type=str, default="dasiamrpn_kernel_r1.onnx", help="Path to onnx model of DaSiamRPN kernel_r1")
parser.add_argument("--dasiamrpn_kernel_cls1", type=str, default="dasiamrpn_kernel_cls1.onnx", help="Path to onnx model of DaSiamRPN kernel_cls1")
parser.add_argument("--dasiamrpn_backend", type=int, default=0, help="Choose one of computation backends:\
0: automatically (by default),\
1: Halide language (http://halide-lang.org/),\
2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit),\
3: OpenCV implementation")
parser.add_argument("--dasiamrpn_target", type=int, default=0, help="Choose one of target computation devices:\
0: CPU target (by default),\
1: OpenCL,\
2: OpenCL fp16 (half-float precision),\
3: VPU")
args = parser.parse_args()
App(args).run()
cv.destroyAllWindows()
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