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:integrate to VOT benchmark: #9

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sydney0zq
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@nrupatunga
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Hi @sydney0zq thank you for you interest in contributing to the project,
Can you please briefly describe your changes and also provide the instructions to test it
Step by step instruction would be much appreciated .
Thank you

@sydney0zq
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How to test our model on VOT benchmark?

  1. Firstly, we need modify this script properly to refer several necessary resource files, such as caffemodel and prototxt file etc, as well as some environment variables
  2. Secondly, clone vot-toolkit repo and set tracker_GOTURN.m associated to our script
  3. Thirdly, follow VOT official documentation to test our tracker on VOT dataset

As a reference, my EAO on VOT2015 is about 20.4

@sydney0zq
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By the way, we need change tracker object. I think our regressor should be consistent over one single video. I will pull another request soon.

if not imagefile:
break
sMatImage = cv2.imread(imagefile)
est_bbox = objTracker.track(sMatImage)
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@sydney0zq sydney0zq Dec 14, 2017

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Here notice I change the class from goturn.tracker.vot_tracker import tracker.

@devyhia
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devyhia commented Jan 6, 2018

@sydney0zq Did you test a trained model against the VOT challenge? If so, could you please share the result as well?

@sydney0zq
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sydney0zq commented Jan 7, 2018

@devyhia No, I just use origin repo’s pretrained model on VOT2015.

@devyhia
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devyhia commented Jan 8, 2018

@sydney0zq Okay, I will use this pull request to test the trained model against the VOT challenge then. I hope it yields close results to those Held achieved.

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3 participants