# KCFpy

**Repository Path**: dong_zhou/KCFpy

## Basic Information

- **Project Name**: KCFpy
- **Description**: Python implementation of KCF tracking algorithm
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-01-18
- **Last Updated**: 2022-01-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# KCF tracker in Python

Python implementation of
> [High-Speed Tracking with Kernelized Correlation Filters](http://www.robots.ox.ac.uk/~joao/publications/henriques_tpami2015.pdf)<br>
> J. F. Henriques, R. Caseiro, P. Martins, J. Batista<br>
> TPAMI 2015

It is translated from [KCFcpp](https://github.com/joaofaro/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/

### Requirements
- Python 2.7
- NumPy
- Numba (needed if you want to use the hog feature)
- OpenCV (ensure that you can `import cv2` in python)

Actually, I have installed Anaconda(for Python 2.7), and OpenCV 3.1(from [opencv.org](http://opencv.org/)).

### Use
Download the sources and execute
```shell
git clone https://github.com/uoip/KCFpy.git
cd KCFpy
python run.py
```
It will open the default camera of your computer, you can also open a different camera or a video
```shell
python run.py 2
```
```shell
python run.py ./test.avi  
```
Try different options (hog/gray, fixed/flexible window, singlescale/multiscale) of KCF tracker by modifying the arguments in line `tracker = kcftracker.KCFTracker(False, True, False)  # hog, fixed_window, multiscale` in run.py.


### Peoblem
I have struggled to make this python implementation as fast as possible, but it's still 2 ~ 3 times slower than its C++ counterpart, furthermore, the use of Numba introduce some unpleasant delay when initializing tracker (***NEW:*** the problem has been solved in [KCFnb](https://github.com/uoip/KCFnb) by using AOT compilation).

***NEWER:*** I write a python wrapper for KCFcpp, see [KCFcpp-py-wrapper](https://github.com/uoip/KCFcpp-py-wrapper), so we can benefit from C++'s speed in python now.