CXX/LD -o .build_release/examples/cpp_classification/classification.bin
CXX/LD -o .build_release/examples/siamese/convert_mnist_siamese_data.bin
CXX/LD -o .build_release/examples/cifar10/convert_cifar_data.bin
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:562: recipe for target '.build_release/tools/caffe.bin' failed
make: *** [.build_release/tools/caffe.bin] Error 1
make: *** 正在等待未完成的任务....
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:562: recipe for target '.build_release/tools/upgrade_net_proto_text.bin' failed
make: *** [.build_release/tools/upgrade_net_proto_text.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:567: recipe for target '.build_release/examples/cifar10/convert_cifar_data.bin' failed
make: *** [.build_release/examples/cifar10/convert_cifar_data.bin] Error 1
.build_release/examples/cpp_classification/classification.o：在函数‘main’中：
classification.cpp:(.text.startup+0x22d)：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:567: recipe for target '.build_release/examples/cpp_classification/classification.bin' failed
make: *** [.build_release/examples/cpp_classification/classification.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:567: recipe for target '.build_release/examples/mnist/convert_mnist_data.bin' failed
make: *** [.build_release/examples/mnist/convert_mnist_data.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:562: recipe for target '.build_release/tools/extract_features.bin' failed
make: *** [.build_release/tools/extract_features.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对Makefile:562: recipe for target '.build_release/tools/upgrade_net_proto_binary.bin' failed
‘cv:make: *** [.build_release/tools/upgrade_net_proto_binary.bin] Error 1
:imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:562: recipe for target '.build_release/tools/convert_imageset.bin' failed
make: *** [.build_release/tools/convert_imageset.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:562: recipe for target '.build_release/tools/compute_image_mean.bin' failed
make: *** [.build_release/tools/compute_image_mean.bin] Error 1
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&, int)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)’未定义的引用
.build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
collect2: error: ld returned 1 exit status
Makefile:567: recipe for target '.build_release/examples/siamese/convert_mnist_siamese_data.bin' failed
make: *** [.build_release/examples/siamese/convert_mnist_siamese_data.bin] Error 1

 
 那是因为你用了opencv 3.x的缘故，只需在Makefile的最后一行加上： 
 LIBRARIES += glog gflags protobuf leveldb snappy \
  lmdb boost_system boost_filesystem hdf5_hl hdf5 m \
  opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs opencv_videoio
 
make clean 
make -j16 && make pycaffe

 就可以重新运行通过了哈，亲测可用
                    当你执行如下命令的时候：make -j16 && make pycaffe你会不小心的报一个错误：CXX/LD -o .build_release/examples/cpp_classification/classification.binCXX/LD -o .build_release/examples/siamese/convert_mnist_siamese_data.bin
				
在编译caffe时报错
.build_release/lib/libcaffe.so：对‘cv::imread(cv::String const&amp;, int)’未定义的引用
查资料说报错原因是，caffe默认使用opencv2.X版本，但是我安装的是opencv 3.1.0。
一改个有效的解决方案是，把opencv需要的lib添加到Makefile文件中，找到LIBRARIES（在PY...
.build_release/lib/libcaffe.so: undefined reference to `cv::imread(cv::String const&, int)'
.build_release/lib/libcaffe.so: undefined reference to `cv::imencode(cv::String const&, cv::...
				
dp@dp:~/ZX/iccv2019-fmeasure-master/caffe-master$ make all -j8
CXX/LD -o .build_release/tools/upgrade_net_proto_binary.bin
CXX/LD -o .build_release/tools/compute_image_mean.bin
CXX/LD -o .build_relea...
装了opencv 3之后，以前可以编译成功的的caffe总是出现错误，现记录下来，作为备份：
 1、build_release/lib/libcaffe.so：对‘cv::imdecode(cv::_InputArray const&, int)’未定义的引用
 对于各种cv出错：
 解决方法：
 修改Makefile:
 LIB...
				
最近在学习PCL点云库相关内容，参考https://www.cnblogs.com/li-yao7758258/p/6437440.html的kdtree代码，发现出现如下bug：
kdtree.cpp:(.text+0x223)：对‘pcl::KdTreeFLANN<pcl::PointXYZ,
flann::L2_Simple >::KdTreeFLANN(bool)’未定义在这里插入代码片的引用
kdtree.cpp:(.text+0x275)：对‘pcl::KdTreeFLANN&lt
				
编译caffe需要安装的东西：
install libatlas-base-dev
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev
sudo apt-get install libgflags-dev libgoog...
上篇博文提到的那个教程是比较好用的，我安装完后编译程序来测试opencv
g++show_image.c -o show_image `pkg -config –cflags –libs opencv`
有以下错误：
error while loading shared libraries:libxxx.so.x:cannot open share objec
					
build_release/lib/libcaffe.so: undefined reference to cv::imread(cv::String const&, int)'
                2022年几款前沿的文本语义检索/Sentence Embedding方法：Gradient Cache, SGPT,ART,DPTDR,RocketQAv2, ERNIE-Search等
                    农民小飞侠: 
                    一般来说需要，需要在自己的领域数据集上训练。直接使用相当于zero-shot，需要自己测试
                2022年几款前沿的文本语义检索/Sentence Embedding方法：Gradient Cache, SGPT,ART,DPTDR,RocketQAv2, ERNIE-Search等
                    20222926徐少飞: 
                    请问hugging face上直接下载的那些基于PLM（一般是BERT-base）进行fune-tuning的模型，比如判断句子相似度的ESimCse，还需要用户自己找数据集再训练吗？
那些模型的参数在发布前应该就是已经用足量的数据集训练好的吧？
                spark 2.2:jupyter notebook NameError: name 'sc' is not defined
                    糖醋排骨十年专家厨师: 
                    可我只开了这一个啊……
                No matching distribution found for setuptools_scm
                    holycun: 
                    牛，感谢大佬
                【PaddlePaddle】动手实现Focal Loss
                    101lucky: 
                    你好 这个代码可以直接用在多分类上吗