【ACF學習】ACF安裝、訓練及檢測初探

使用環境說明:Win10+VS2013+MATLAB R2016a

1,dollar工具箱下載編譯

https://pdollar.github.io/toolbox/,最新版本是Version3.5

For version history click here. This code is licensed under the Simplified BSD License.

下載後添加目錄、編譯即可使用

addpath(genpath('ROOT\piotr_toolbox\toolbox\'))

savepath

toolboxCompile

注意編譯前需要配置好VS編譯器

工具箱包含七大部分,channels、classify、detector、filter、images、matlab、videos,後續會對每部分做詳細的說明介紹


2,測試已訓練模型

可以準備好Inria或者Caltech數據使用detector中acfDemoInria.m或者acfDemoCal.m測試,也可以直接用圖片測試

load('detector/models/AcfInriaDetector.mat')

加載的detector分爲三部分:opts、clf、info

opts保存模型相關信息

clf保存分類器信息

info保存特徵通道信息


image = imread('test.jpg')

box = acfDetect(image, detector)

figure;

im(image);

bbApply('draw', box);



% The detector was introduced and described through the following papers:
%  [1] P. Doll醨, Z. Tu, P. Perona and S. Belongie
%   "Integral Channel Features", BMVC 2009.
%  [2] P. Doll醨, S. Belongie and P. Perona
%   "The Fastest Pedestrian Detector in the West," BMVC 2010.
%  [3] P. Doll醨, R. Appel and W. Kienzle
%   "Crosstalk Cascades for Frame-Rate Pedestrian Detection," ECCV 2012.
%  [4] P. Doll醨, R. Appel, S. Belongie and P. Perona
%   "Fast Feature Pyramids for Object Detection," PAMI 2014.
%  [5] W. Nam, P. Doll醨, and J.H. Han
%   "Local Decorrelation For Improved Pedestrian Detection," NIPS 2014.
% Please see: http://vision.ucsd.edu/~pdollar/research.html#ObjectDetection

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