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MDnet

MDnet visual tracking algorithm implementation version 3. A trainded model mdnetv3.pt which is trained on vot2016 and one result, vot2016/marching are also uploaded, in which blue windows are groundtruth boundingboxes while green ones are tracking results. Better performance with respect to fps, precision and success has achieved

How to run:

	python srcv3.py online0
	
	the program asks you to input a video name and you need to download and prepare vot2016 datasets

Files:

	libv3.py: contains all classes and most functions

	options.py: contains all parameters we need to modify

	srcv3.py: offline_training, online_tracking

Folder paths organization:

-vot2016/

-mdnet/
	
	-libv3.py
	
	-srcv3.py
	
	-options.py
	
	-vot2016.txt
	
	-results/
	
	-trained_nets/
	
		-mdnetv3.pt

Dependencies:

	(1)python3.5

	(2)opencv,numpy

	(3)pytorch

	(4)scikit-learn

Hardware:

	Nvidia GTX TITAN X(recommended), but it can also run without gpu. Offline training needs 1390 M graphics memory and online tracking needs about 8000 M graphics memory

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