KCF tracker in Python

Python implementation of

High-Speed Tracking with Kernelized Correlation Filters
J. F. Henriques, R. Caseiro, P. Martins, J. Batista
TPAMI 2015

It is fix version for python 3 of KCFpy.

It is translated from KCFcpp (Authors: Joao Faro, Christian Bailer, Joao F. Henriques), a C++ implementation of Kernelized Correlation Filters. Find more references and code of KCF at http://www.robots.ox.ac.uk/~joao/circulant/

To install dependencies run requirements.sh script.

KCF Tracker without cnn

Requirements

• Python 3
• NumPy
• Numba (needed if you want to use the hog feature)
• OpenCV (ensure that you can import cv2 in python)

Execute these lines

Download the sources and execute

git clone https://github.com/Sshanu/KCFpy.git
cd KCFpy
python run_updated.py

It will open the default camera of your computer, you can also open a video

python run_updated.py -inv test.avi  

KCF Tracker with cnn

Theano version

Requirements

• Python 3
• NumPy
• Numba (needed if you want to use the hog feature)
• OpenCV (ensure that you can import cv2 in python)
• Theano
• Pickle
• Lasagne

For KCF Tracker with Vggnet 16

Download pretrained weights from: https://s3.amazonaws.com/lasagne/recipes/pretrained/imagenet/vgg16.pkl and save in new_vgg16 folder. Then execute

python run_cnn.py -inv test.avi -opt Output_Folder -mo cnn

For Webcam

python run_cnn.py -opt Output_Folder -mo cnn

For using GPU to compute conv layer : change line 14 of vgg16.py in new_vgg16 folder

from lasagne.layers import Conv2DLayer as ConvLayer

to

from lasagne.layers.dnn import Conv2DDNNLayer as ConvLayer

Caffe version

Requirements

• Python 2.7
• NumPy
• OpenCV (ensure that you can import cv2 in python)
• Caffe

Download the Vgg16 caffe model from: http://www.robots.ox.ac.uk/~vgg/software/very_deep/caffe/VGG_ILSVRC_16_layers.caffemodel and save in vgg16 folder. Edit the ground_truth.txt file with original coordinates of image. Save images in 'img'folder. Then execute these:

python2.7 caffe_run.py -inp img -mo cnn