目标检测源码

Information =========== Project webpage: http://www.cs.uchicago.edu/~pff/latent/. This is an implementation of our object detection system based on mixtures of deformable part models. The current implementation extends the system in [2] as described in [3]. The models in this implementation are structured using the grammar formalism presented in [4]. The distribution contains object detection and model learning code, as well as models trained on the PASCAL and INRIA Person datasets. This release also includes code for rescoring detections based on contextual information. The system is implemented in Matlab, with a few helper functions written in C/C++ for efficiency reasons. The software was tested on several versions of Linux and Mac OS X using Matlab versions R2009b and R2010a. There may be compatibility issues with other versions of Matlab. For questions concerning the code please contact Ross Girs

DPM4.01_windows-master
.gitignore
COPYING
HOGpicture.m
Makefile
README
VOCdevkit
VOCdevkit_18-May-2011_2.tar
bboxpred_data.m
bboxpred_get.m
bboxpred_input.m
bboxpred_rescore.m
bboxpred_train.m
boxoverlap.m
changelog
clipboxes.m
color.m
compile.m
croppos.m
demo.asv
demo.m
documentation.txt
dt.cc
dt.mexw64
fconv.cc
fconv.mexw64
fconvMT.cc
fconvblas.cc
fconvblasMT.cc
fconvsse.cc
featpyramid.m
features.asv
features.cc
features.mexw64
flipfeat.m
foldHOG.m
gdetect.m
gdetectwrite.m
getcontextlabels.m
getdetections.cc
getdetections.mexw64
getpadding.m
globals.m
imgdetect.m
imreadx.m
initmodel.m
initrand.m
labeldata.m
learn.cc
learn.exe
lrmodel.m
lrsplit.m
mergemodels.m
mkpartfilters.m
model_addblock.m
model_addfilter.m
model_addmirroredfilter.m
model_addnonterminal.m
model_addparts.m
model_addrule.m
model_addsymbol.m
model_create.m
model_setdetwindow.m
model_sort.m
nms.m
parsemodel.m
pascal.m
pascal_data.m
pascal_eval.m
pascal_init.m
pascal_test.m
pascal_train.m
process.m
procid.m
readinfo.m
readmodel.m
reduceboxes.m
rescore_data.m
rescore_labels.m
rescore_test.m
rescore_train.m
resize.cc
resize.mexw64
rewritedat.m
rules_with_lhs.m
showboxes.m
split.m
subarray.m
test.txt
train.m
trainval.m
visualizeHOG.m
visualizemodel.m
warppos.m
writecomponentinfo.m
writeheader.m
writelob.m
writemodel.m