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133 lines
5.8 KiB
133 lines
5.8 KiB
#!/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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