Caffe項目外使用classification.cpp

caffe項目中自帶了一個classification.cpp文件,能夠用訓練好的模型進行直接分類,不過須要在caffe項目外使用的話就須要本身寫編譯代碼。html

能夠參考一下這篇文章,找了很久才找到http://blog.sina.com.cn/s/blog_534497fd0102wf2t.html 裏面寫的很全。而後根據這篇簡單總結了一下cmakelists.txt的簡單寫法python

cmake_minimum_required(VERSION 2.8)
project(classification)

find_package(OpenCV REQUIRED)
find_package(Caffe REQUIRED)

include_directories( ${Caffe_INCLUDE_DIRS} )
add_definitions(${Caffe_DEFINITIONS}) # ex. -DCPU_ONLY
add_executable(caffeClassify classification.cpp)
target_link_libraries(caffeClassify ${OpenCV_LIBS} ${Caffe_LIBRARIES})

注意caffe必定要make install。 用make的方法或者cmake方法編譯的都要install一下,注意!

若是要在qt中使用的話推薦一下這個https://github.com/withwsf/Image_detection/blob/master/Image_detection.pro,裏面有用qt管理的caffe項目,我把他的.pro複製出來。c++

QT       += core gui
CONFIG +=c++11

greaterThan(QT_MAJOR_VERSION, 4): QT += widgets

TARGET = Image_detection
TEMPLATE = app
SOURCES += main.cpp\
        mainwindow.cpp \
    image_detection.cpp \
    nms.cpp \
    dockwidget.cpp \
    detector_warpper.cpp

HEADERS  += mainwindow.h \
        image_detection.h \
    nms.h \
    dockwidget.h \
    detector_warpper.h

FORMS    += mainwindow.ui \
    dockwidget.ui

INCLUDEPATH += /home/vcc/caffe_depen/caffe-fast-rcnn/include \
               /usr/include/opencv /usr/include/opencv2 \



LIBS += -L/home/vcc/caffe_depen/lib -lcaffe -lcblas -latlas

LIBS+= -L/usr/local/lib  -lglog -lgflags -lprotobuf -lleveldb -lsnappy -llmdb -lboost_system -lhdf5_hl -lhdf5 -lm -lopencv_core -lopencv_highgui -lopencv_imgproc -lboost_thread -lstdc++  -lprotobuf
INCLUDEPATH +=/usr/include/python2.7/
INCLUDEPATH +=/usr/include/
LIBS += -lboost_python -lpython2.7 -lboost_system

這是這個做者的工程,能夠借鑑着改。git


想要在windows中使用caffe項目,推薦這個githubhttps://github.com/happynear/caffe-windows/tree/ms到這個目錄中https://github.com/happynear/caffe-windows/tree/ms/windows/caffe.binding,你們也能夠借鑑着改。github

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