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This repository was a fork of BVLC/caffe and includes the upsample, bn, dense_image_data and softmax_with_loss (with class weighting) layers of caffe-segnet (https://github.com/alexgkendall/caffe-segnet) to run SegNet with cuDNN version 5.

License: Other

CMake 2.72% Makefile 0.69% Shell 0.34% C++ 79.43% Cuda 6.03% MATLAB 0.88% M 0.01% Python 8.25% Protocol Buffer 1.66%
caffe segnet cudnn5 titan-x-pascal

caffe-segnet-cudnn5's Introduction

Caffe SegNet cuDNN5

This is a modified version of Caffe which supports the SegNet architecture

As described in SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan, Alex Kendall and Roberto Cipolla [http://arxiv.org/abs/1511.00561]

Please refer to Alex Kendalls caffe-segnet for tutorial and a guide how to use it (https://github.com/alexgkendall/caffe-segnet).

Since the original caffe-segnet supports just cuDNN v2, which is not supported for new pascal based GPUs, it was possible to decrease the inference time by 25 % to 35 % with caffe-segnet-cudnn5 using Titan X Pascal.

I recommend to use my trained weights (CityScapes Model) for semantic segmenation of traffic scenes, which you can find in segnet model zoo: https://github.com/alexgkendall/SegNet-Tutorial/blob/master/Example_Models/segnet_model_zoo.md

If you like to speed up SegNet even further, you can run the BN-absorber.py script. It merges the batch normalization layer into convolutional layer by modyfing its weights and biases. In doing so, it is possible to accelerate it by around 30 %. Please find BN-absorber.py in the script folder.

If you like to use SegNet with C++, the test_segmentation.cpp might be helpful. https://github.com/alexgkendall/SegNet-Tutorial/blob/master/Scripts/test_segmentation.cpp

News

  • If SegNet is too slow for you, try out the ENet in Caffe. It's much faster! (May the 30th, 2017)

  • Speed up SegNet by merging batch normalization and convolutional layer with BN-absorber.py in the script folder. (May the 12th, 2017)

  • cuDNN v.6 has been released. I have tested it using Titan X Pascal. It doesn't bring any noticeable improvements for SegNet. For that reason I will not update the repository to cuDNN6.

Publications

If you use this software in your research, please cite their publications:

http://arxiv.org/abs/1511.02680 Alex Kendall, Vijay Badrinarayanan and Roberto Cipolla "Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding." arXiv preprint arXiv:1511.02680, 2015.

http://arxiv.org/abs/1511.00561 Vijay Badrinarayanan, Alex Kendall and Roberto Cipolla "SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation." arXiv preprint arXiv:1511.00561, 2015.

License

This extension to the Caffe library is released under a creative commons license which allows for personal and research use only. For a commercial license please contact the authors. You can view a license summary here: http://creativecommons.org/licenses/by-nc/4.0/

caffe-segnet-cudnn5's People

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caffe-segnet-cudnn5's Issues

Caffe not using GPU even though Caffe::set_mode(Caffe::GPU) is executed

When I tried to my C++ program with caffe-segnet-cudnn-5, the inference speed is pretty slow even though Caffe::GPU is set, which is around 2 seconds per image. It is the same speed when only CPU is used (Caffe:CPU is set). This problem only happens for caffe-segnet-cudnn-5. It does not happen for the original caffe-segnet with cudnn version 2.

The caffe-segnet-cudnn-5 is compiled with CUDA 8 with CUDNN 5.1..

Your system configuration

Operating system: Ubuntu 16.04
GPU: NVIDIA GTX 1060
CUDA version (if applicable): 8.0
CUDNN version (if applicable): 5.1
BLAS: OpenBLAS

News announcements

If SegNet is too slow for you, try out the ENet in Caffe. It's much faster with very similar quality! (May the 30th, 2017)

test_segmentation.cpp Failed to parse NetParameter file

Issue summary

Hello
I tried to run the code test_segmentation.cpp CPU_ONLY . I get the error

./test_segmentation.bin Example_Models/bayesian_segnet_camvid.prototxt weights/bayesian_segnet_camvid.caffemodel CamVid/test/Seq05VD_f01230.png Scripts/camvid12.png

[libprotobuf ERROR google/protobuf/text_format.cc:274] Error parsing text-format caffe.NetParameter: 450:24: Message type "caffe.DropoutParameter" has no field named "sample_weights_test".
F0411 15:32:52.484048 26838 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: Example_Models/bayesian_segnet_camvid.prototxt

Any suggestions on getting this working?

thank you!

Operating system: ubuntu 16.04

Segmentation fault

I'm getting the following segmentation fault when running "make runtest". It works fine in the case of the original caffe-segnet (with cuDNN 3.0.8).

[ RUN ] LayerFactoryTest/2.TestCreateLayer
*** Aborted at 1483730734 (unix time) try "date -d @1483730734" if you are using GNU date ***
PC: @ 0x7fe5c0d9cf25 caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
*** SIGSEGV (@0x208) received by PID 8650 (TID 0x7fe5c15d5ac0) from PID 520; stack trace: ***
@ 0x7fe5c033a390 (unknown)
@ 0x7fe5c0d9cf25 caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x7fe5c0e55099 caffe::DataLayer<>::~DataLayer()
@ 0xb49c08 caffe::LayerFactoryTest_TestCreateLayer_Test<>::TestBody()
@ 0xde7453 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0xde038a testing::Test::Run()
@ 0xde04d8 testing::TestInfo::Run()
@ 0xde05e5 testing::TestCase::Run()
@ 0xde217f testing::internal::UnitTestImpl::RunAllTests()
@ 0xde24a3 testing::UnitTest::Run()
@ 0x8905cd main
@ 0x7fe5ba028830 __libc_start_main
@ 0x8973a9 _start
@ 0x0 (unknown)
Segmentation fault (core dumped)
src/caffe/test/CMakeFiles/runtest.dir/build.make:57: recipe for target 'src/caffe/test/CMakeFiles/runtest' failed
make[3]: *** [src/caffe/test/CMakeFiles/runtest] Error 139
CMakeFiles/Makefile2:328: recipe for target 'src/caffe/test/CMakeFiles/runtest.dir/all' failed
make[2]: *** [src/caffe/test/CMakeFiles/runtest.dir/all] Error 2
CMakeFiles/Makefile2:335: recipe for target 'src/caffe/test/CMakeFiles/runtest.dir/rule' failed
make[1]: *** [src/caffe/test/CMakeFiles/runtest.dir/rule] Error 2
Makefile:240: recipe for target 'runtest' failed
make: *** [runtest] Error 2

Problems building

Hello, I am trying to run SegNet, so I cloned this repo. I am trying to build it and I am getting the following errors. I have modified the Makefile.config by uncommenting USE_CUDNN := 1 , then I have run the following commands:

mkdir build
cd build
cmake ..

After running cmake I get the following printed to terminal :

-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Looking for pthread_create
-- Looking for pthread_create - not found
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE
-- Boost version: 1.58.0
-- Found the following Boost libraries:
-- system
-- thread
-- filesystem
-- chrono
-- date_time
-- atomic
-- Found GFlags: /usr/include
-- Found gflags (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libgflags.so)
-- Found Glog: /usr/include
-- Found glog (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libglog.so)
-- Found Protobuf: /usr/lib/x86_64-linux-gnu/libprotobuf.so
-- Found PROTOBUF Compiler: /usr/bin/protoc
-- Found HDF5: /usr/lib/x86_64-linux-gnu/hdf5/serial/lib/libhdf5_hl.so;/usr/lib/x86_64-linux-gnu/hdf5/serial/lib/libhdf5.so;/usr/lib/x86_64-linux-gnu/libpthread.so;/usr/lib/x86_64-linux-gnu/libsz.so;/usr/lib/x86_64-linux-gnu/libz.so;/usr/lib/x86_64-linux-gnu/libdl.so;/usr/lib/x86_64-linux-gnu/libm.so (found version "1.8.16")
-- Found LMDB: /usr/include
-- Found lmdb (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/liblmdb.so)
-- Found LevelDB: /usr/include
-- Found LevelDB (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libleveldb.so)
-- Found Snappy: /usr/include
-- Found Snappy (include: /usr/include, library: /usr/lib/x86_64-linux-gnu/libsnappy.so)
-- CUDA detected: 8.0
-- Found cuDNN: ver. 6.0.21 found (include: /usr/local/cuda-8.0/include, library: /usr/local/cuda-8.0/lib64/libcudnn.so)
-- Added CUDA NVCC flags for: sm_61
-- OpenCV found (/opt/ros/kinetic/share/OpenCV-3.3.1)
-- Found Atlas: /usr/include
-- Found Atlas (include: /usr/include, library: /usr/lib/libatlas.so)
-- Found PythonInterp: /usr/bin/python2.7 (found suitable version "2.7.12", minimum required is "2.7")
-- Found PythonLibs: /usr/lib/x86_64-linux-gnu/libpython2.7.so (found suitable version "2.7.12", minimum required is "2.7")
-- Found NumPy: /home/shastriram23/.local/lib/python2.7/site-packages/numpy/core/include (found suitable version "1.14.2", minimum required is "1.7.1")
-- NumPy ver. 1.14.2 found (include: /home/shastriram23/.local/lib/python2.7/site-packages/numpy/core/include)
-- Boost version: 1.58.0
-- Found the following Boost libraries:
-- python
-- Could NOT find Doxygen (missing: DOXYGEN_EXECUTABLE)
-- Found Git: /usr/bin/git (found version "2.7.4")

-- ******************* Caffe Configuration Summary *******************
-- General:
-- Version : 1.0.0-rc3
-- Git : abcf30d
-- System : Linux
-- C++ compiler : /usr/bin/c++
-- Release CXX flags : -O3 -DNDEBUG -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Debug CXX flags : -g -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Build type : Release

-- BUILD_SHARED_LIBS : ON
-- BUILD_python : ON
-- BUILD_matlab : OFF
-- BUILD_docs : ON
-- CPU_ONLY : OFF
-- USE_OPENCV : ON
-- USE_LEVELDB : ON
-- USE_LMDB : ON
-- ALLOW_LMDB_NOLOCK : OFF

-- Dependencies:
-- BLAS : Yes (Atlas)
-- Boost : Yes (ver. 1.58)
-- glog : Yes
-- gflags : Yes
-- protobuf : Yes (ver. 2.6.1)
-- lmdb : Yes (ver. 0.9.17)
-- LevelDB : Yes (ver. 1.18)
-- Snappy : Yes (ver. 1.1.3)
-- OpenCV : Yes (ver. 3.3.1)
-- CUDA : Yes (ver. 8.0)

-- NVIDIA CUDA:
-- Target GPU(s) : Auto
-- GPU arch(s) : sm_61
-- cuDNN : Yes (ver. 6.0.21)

-- Python:
-- Interpreter : /usr/bin/python2.7 (ver. 2.7.12)
-- Libraries : /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.12)
-- NumPy : /home/shastriram23/.local/lib/python2.7/site-packages/numpy/core/include (ver 1.14.2)

-- Documentaion:
-- Doxygen : No
-- config_file :

-- Install:
-- Install path : /media/shastriram23/Data/UbuntuData/deepLearningTutorials/segNet/caffe-segnet-cudnn5/build/install

-- Configuring done
-- Generating done
-- Build files have been written to: /media/shastriram23/Data/UbuntuData/deepLearningTutorials/segNet/caffe-segnet-cudnn5/build

When I run make all I get the following:

[ 0%] Running C++/Python protocol buffer compiler on /media/shastriram23/Data/UbuntuData/deepLearningTutorials/segNet/caffe-segnet-cudnn5/src/caffe/proto/caffe.proto
Scanning dependencies of target proto
[ 1%] Building CXX object src/caffe/CMakeFiles/proto.dir///include/caffe/proto/caffe.pb.cc.o
[ 1%] Linking CXX static library ../../lib/libproto.a
[ 1%] Built target proto
[ 1%] Building NVCC (Device) object src/caffe/CMakeFiles/cuda_compile.dir/util/cuda_compile_generated_math_functions.cu.o
/media/shastriram23/Data/UbuntuData/deepLearningTutorials/segNet/caffe-segnet-cudnn5/include/caffe/util/cudnn.hpp(112): error: too few arguments in function call

1 error detected in the compilation of "/tmp/tmpxft_00007817_00000000-5_math_functions.cpp4.ii".
CMake Error at cuda_compile_generated_math_functions.cu.o.cmake:266 (message):
Error generating file
/media/shastriram23/Data/UbuntuData/deepLearningTutorials/segNet/caffe-segnet-cudnn5/build/src/caffe/CMakeFiles/cuda_compile.dir/util/./cuda_compile_generated_math_functions.cu.o

src/caffe/CMakeFiles/caffe.dir/build.make:483: recipe for target 'src/caffe/CMakeFiles/cuda_compile.dir/util/cuda_compile_generated_math_functions.cu.o' failed
make[2]: *** [src/caffe/CMakeFiles/cuda_compile.dir/util/cuda_compile_generated_math_functions.cu.o] Error 1
CMakeFiles/Makefile2:272: recipe for target 'src/caffe/CMakeFiles/caffe.dir/all' failed
make[1]: *** [src/caffe/CMakeFiles/caffe.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2

Can someone help me out here? I really have no idea what's going wrong. I have previously installed caffe on my system and it build and runs fine. I am having problems with this caffe-segnet. I would really appreciate any help I could get since this is for my research. Thank you so much

Does anyone compile this caffe-SegNet-cudnn5 under Windows10 successfully?

Does anyone compile this caffe-SegNet-cudnn5 under Windows10 successfully?
My platform: Win10,cuda8.0,cudnn5.1,vs2013
Until now, I haven't succeeded yet.

The error is:

error LNK2001: unresolved external symbol "protected: virtual void __cdecl caffe::BasePrefetchingDataLayer::InternalThreadEntry(void)" (?InternalThreadEntry@?$BasePrefetchingDataLayer@N@caffe@@MEAAXXZ) E:\caffe-master_for_segnet\windows\caffe\image_data_layer.obj caffe

Segmentation fault (core dumped)

When I used "ImageData" layer in this version of Caffe to read an image and a label, I received the error of "Segmentation fault (core dumped)". There is no such an error for the original official version of Caffe. I doubt maybe when you added the denseImageData layer, you ruined the original ImageData layer. Could you check this issue? Thanks!

accuracy decreases with weights finetuned on cityscapes

Hy @TimoSaemann,
I am very new to SegNet as well as Caffe. I tried to use the weights of the webdemo of SegNet as well as the weights that you finetuned on Cityscapes.
My results looked like this:
segnet Webdemo
segnet citiyscapes finetuned on Cityscapes

Do you know why in this test the classes are less distinct with the weights finetuned on Cityscapes?
I expected it to be the other way around.
Did I get some settings wrong or does the input video have an impact or maybe does it work better with videos from inside a city? I used one from a highway.

I used @alexgkendall 's caffe-segnet and followed the tutorial. As a model filed I used the segnet_model_driving_webdemo.prototxt and just changed the weights.

Operating system: Ubuntu 14.04
Compiler: gcc 4.8.4
CPU_ONLY
BLAS: ATLAS
Python: 2.7

transform_param fails

I am finetuning a pre-trained model (initially trained on cityscapes dataset) using my own dataset. When I incorporate "mirror:true" in transform_param{} in the net.prototxt, I get the following error:
error_1
@TimoSaemann Does the dense_image_data_layer support transform_param?

Error with compute_bn_statistics.py

When I run the compute_bn_statistics.py, I get the following error:
screenshot from 2018-04-01 19 46 43
I realize that the MaxTopBlobs() is set to 1 and it has to be increased to 3 to accommodate mean and variance blobs.
@TimoSaemann Can you please help me with this problem?

A problem when make runtest

Issue summary

[----------] 1 test from LayerFactoryTest/2, where TypeParam = caffe::GPUDevice
[ RUN ] LayerFactoryTest/2.TestCreateLayer
*** Aborted at 1483801360 (unix time) try "date -d @1483801360" if you are using GNU date ***
PC: @ 0x7f3458fca962 (unknown)
*** SIGSEGV (@0x118) received by PID 1777 (TID 0x7f346b689800) from PID 280; stack trace: ***
@ 0x7f3459321390 (unknown)
@ 0x7f3458fca962 (unknown)
@ 0x7f3459cd67a5 caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x7f3459d99e09 caffe::DataLayer<>::~DataLayer()
@ 0x4ec5e8 caffe::LayerFactoryTest_TestCreateLayer_Test<>::TestBody()
@ 0x8f63d3 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x8f01ea testing::Test::Run()
@ 0x8f0338 testing::TestInfo::Run()
@ 0x8f0415 testing::TestCase::Run()
@ 0x8f162f testing::internal::UnitTestImpl::RunAllTests()
@ 0x8f1943 testing::UnitTest::Run()
@ 0x46dacd main
@ 0x7f3458f67830 (unknown)
@ 0x475509 _start
Makefile:526: recipe for target 'runtest' failed
make: *** [runtest] Segmentation fault (core dumped)

Steps to reproduce

make runtest -j16

Your system configuration

Operating system:Ubuntu16.04
Compiler:GCC5.3
CUDA version (if applicable):8.0
CUDNN version (if applicable):v5.1
BLAS:atlas
Python or MATLAB version (for pycaffe and matcaffe respectively):Python2.7

compute_bn_statistics.py fails

Issue summary

When following the Segnet tutorial, the following error is experienced when running the compute_bn_statistics.py script after training a model for Segnet:

Building BN calc net...
Traceback (most recent call last):
File "Scripts/compute_bn_statistics.py", line 175, in
testable_msg = make_testable(args.train_model)
File "Scripts/compute_bn_statistics.py", line 38, in make_testable
text_format.Merge(train_str, train_net)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 476, in Merge
descriptor_pool=descriptor_pool)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 526, in MergeLines
return parser.MergeLines(lines, message)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 559, in MergeLines
self._ParseOrMerge(lines, message)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 574, in _ParseOrMerge
self._MergeField(tokenizer, message)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 675, in _MergeField
merger(tokenizer, message, field)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 764, in _MergeMessageField
self._MergeField(tokenizer, sub_message)
File "/usr/local/lib/python2.7/dist-packages/google/protobuf/text_format.py", line 643, in _MergeField
(message_descriptor.full_name, name))
google.protobuf.text_format.ParseError: 7:3 : Message type "caffe.LayerParameter" has no field named "dense_image_data_param".

Steps to reproduce

  1. Train using the segnet solver model: ./caffe-segnet-cudnn5/build/tools/caffe train -gpu all -solver Models/segnet_solver.prototxt
  2. Run nnuser@gsd-pc2:~/SegNet-Tutorial$ python Scripts/compute_bn_statistics.py Models/segnet_train.prototxt Models/Training/segnet_iter_100000.caffemodel Models/Inference/

I have attached my Makefile.config and cmake output:
Makefile .txt
cmake_output.txt

System configuration

Operating system: Ubuntu 16.04 LTS
Compiler: CMake
CUDA version (if applicable): 8.0
CUDNN version (if applicable): 5.1
BLAS: Attlas
Python or MATLAB version (for pycaffe and matcaffe respectively): Python 2.7

Crash on SegNet tutorial

Please use the caffe-users list for usage, installation, or modeling questions, or other requests for help.
Do not post such requests to Issues. Doing so interferes with the development of Caffe.

Please read the guidelines for contributing before submitting this issue.

Issue summary

Segnet training according to their tutorial fails; works fine with the original version of caffe-segnet

Steps to reproduce

~/SegNet$ ./caffe-segnet-cudnn5/build/tools/caffe train -gpu 0 -solver ./Models/segnet_solver.prototxt -weights ~/SegNet/Models/VGG_ILSVRC_16_layers.caffemodel

I1216 09:13:55.123234 3520 caffe.cpp:217] Using GPUs 0
I1216 09:13:55.129607 3520 caffe.cpp:222] GPU 0: Tesla K40c
E1216 09:13:55.404479 3520 common.cpp:113] Cannot create Cublas handle. Cublas won't be available.
E1216 09:13:55.609668 3520 common.cpp:120] Cannot create Curand generator. Curand won't be available.
I1216 09:13:55.609848 3520 solver.cpp:48] Initializing solver from parameters:
test_iter: 1
test_interval: 10000000
base_lr: 0.001
display: 20
max_iter: 40000
lr_policy: "step"
gamma: 1
momentum: 0.9
weight_decay: 0.0005
stepsize: 10000000
snapshot: 1000
snapshot_prefix: "/home/XXX/SegNet/Models/Training/segnet"
solver_mode: GPU
device_id: 0
net: "/home/XXX/SegNet/Models/segnet_train.prototxt"
train_state {
level: 0
stage: ""
}
test_initialization: false
I1216 09:13:55.616778 3520 solver.cpp:91] Creating training net from net file: /home/XXX/SegNet/Models/segnet_train.prototxt
[libprotobuf ERROR google/protobuf/text_format.cc:274] Error parsing text-format caffe.NetParameter: 7:26: Message type "caffe.LayerParameter" has no field named "dense_image_data_param".
F1216 09:13:55.616905 3520 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: /home/XXX/SegNet/Models/segnet_train.prototxt
*** Check failure stack trace: ***
@ 0x7f6aed6ab5cd google::LogMessage::Fail()
@ 0x7f6aed6ad433 google::LogMessage::SendToLog()
@ 0x7f6aed6ab15b google::LogMessage::Flush()
@ 0x7f6aed6ade1e google::LogMessageFatal::~LogMessageFatal()
@ 0x7f6aeddd3d61 caffe::ReadNetParamsFromTextFileOrDie()
@ 0x7f6aedc2468b caffe::Solver<>::InitTrainNet()
@ 0x7f6aedc25a77 caffe::Solver<>::Init()
@ 0x7f6aedc25e1a caffe::Solver<>::Solver()
@ 0x7f6aedd901f3 caffe::Creator_SGDSolver<>()
@ 0x40c20a train()
@ 0x4088d8 main
@ 0x7f6aebf39830 __libc_start_main
@ 0x4091a9 _start
@ (nil) (unknown)
Aborted (core dumped)

Your system configuration

Operating system: Ubuntu x64 16.04.1 LTS
Compiler:
CUDA version (if applicable): 8.0
CUDNN version (if applicable): 5.1
BLAS:
Python or MATLAB version (for pycaffe and matcaffe respectively):

test_data_layer.bin fails

Issue summary

while running "make runtest" various errors are experienced
The error looks like "floating"...

================= ERROR 1 ======================================
[----------] 4 tests from NetUpgradeTest
[ RUN ] NetUpgradeTest.TestAllParams
[ OK ] NetUpgradeTest.TestAllParams (1 ms)
[ RUN ] NetUpgradeTest.TestUpgradeV1LayerType
*** Error in `.build_release/test/test_all.testbin': munmap_chunk(): invalid pointer: 0x0000000000f00fe0 ***
*** Aborted at 1483030739 (unix time) try "date -d @1483030739" if you are using GNU date ***
PC: @ 0x7f70b5875267 (unknown)
*** SIGABRT (@0x3e800000bb1) received by PID 2993 (TID 0x7f70b895ba40) from PID 2993; stack trace: ***
@ 0x7f70b5c1ad10 (unknown)
@ 0x7f70b5875267 (unknown)
@ 0x7f70b5876eca (unknown)
@ 0x7f70b58b8c53 (unknown)
@ 0x7f70b58c49f8 (unknown)
@ 0x7f70b64c426b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x7f70b652b562 boost::detail::sp_counted_impl_p<>::dispose()
@ 0x65e589 caffe::NetUpgradeTest_TestUpgradeV1LayerType_Test::TestBody()
@ 0x726993 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x71eaca testing::Test::Run()
@ 0x71ec18 testing::TestInfo::Run()
@ 0x71ecf5 testing::TestCase::Run()
@ 0x71f688 testing::internal::UnitTestImpl::RunAllTests()
@ 0x71f953 testing::UnitTest::Run()
@ 0x45aec2 main
@ 0x7f70b5860a40 (unknown)
@ 0x461fc9 _start
@ 0x0 (unknown)
Aborted (core dumped)
Makefile:526: recipe for target 'runtest' failed

========================= ERROR 2 ================================
[----------] 12 tests from DataLayerTest/0, where TypeParam = caffe::CPUDevice
[ RUN ] DataLayerTest/0.TestReshapeLevelDB
*** Aborted at 1483030926 (unix time) try "date -d @1483030926" if you are using GNU date ***
PC: @ 0x7fce07cae29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
*** SIGSEGV (@0x18) received by PID 3372 (TID 0x7fce0a145a40) from PID 24; stack trace: ***
@ 0x7fce07404d10 (unknown)
@ 0x7fce07cae29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x5e86c8 caffe::DataLayerTest<>::TestReshape()
@ 0x726993 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x71eaca testing::Test::Run()
@ 0x71ec18 testing::TestInfo::Run()
@ 0x71ecf5 testing::TestCase::Run()
@ 0x71f688 testing::internal::UnitTestImpl::RunAllTests()
@ 0x71f953 testing::UnitTest::Run()
@ 0x45aec2 main
@ 0x7fce0704aa40 (unknown)
@ 0x461fc9 _start
@ 0x0 (unknown)
Segmentation fault (core dumped)
Makefile:526: recipe for target 'runtest' failed
make: *** [runtest] Error 139

======================= ERROR 3 =======================================
[----------] 12 tests from DataLayerTest/0, where TypeParam = caffe::CPUDevice
[ RUN ] DataLayerTest/0.TestReshapeLevelDB
*** Aborted at 1483030926 (unix time) try "date -d @1483030926" if you are using GNU date ***
PC: @ 0x7fce07cae29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
*** SIGSEGV (@0x18) received by PID 3372 (TID 0x7fce0a145a40) from PID 24; stack trace: ***
@ 0x7fce07404d10 (unknown)
@ 0x7fce07cae29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x5e86c8 caffe::DataLayerTest<>::TestReshape()
@ 0x726993 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x71eaca testing::Test::Run()
@ 0x71ec18 testing::TestInfo::Run()
@ 0x71ecf5 testing::TestCase::Run()
@ 0x71f688 testing::internal::UnitTestImpl::RunAllTests()
@ 0x71f953 testing::UnitTest::Run()
@ 0x45aec2 main
@ 0x7fce0704aa40 (unknown)
@ 0x461fc9 _start
@ 0x0 (unknown)
Segmentation fault (core dumped)
Makefile:526: recipe for target 'runtest' failed
make: *** [runtest] Error 139

========================= ERROR 4 ==========================================
[----------] 12 tests from DataLayerTest/0, where TypeParam = caffe::CPUDevice
[ RUN ] DataLayerTest/0.TestReadCropTrainSequenceUnseededLevelDB
*** Aborted at 1483031372 (unix time) try "date -d @1483031372" if you are using GNU date ***
PC: @ 0x7fbc78edd29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
*** SIGSEGV (@0x10) received by PID 5684 (TID 0x7fbc7b374a40) from PID 16; stack trace: ***
@ 0x7fbc78633d10 (unknown)
@ 0x7fbc78edd29b caffe::BasePrefetchingDataLayer<>::~BasePrefetchingDataLayer()
@ 0x5ea549 caffe::DataLayerTest<>::TestReadCropTrainSequenceUnseeded()
@ 0x726993 testing::internal::HandleExceptionsInMethodIfSupported<>()
@ 0x71eaca testing::Test::Run()
@ 0x71ec18 testing::TestInfo::Run()
@ 0x71ecf5 testing::TestCase::Run()
@ 0x71f688 testing::internal::UnitTestImpl::RunAllTests()
@ 0x71f953 testing::UnitTest::Run()
@ 0x45aec2 main
@ 0x7fbc78279a40 (unknown)
@ 0x461fc9 _start
@ 0x0 (unknown)
Segmentation fault (core dumped)
Makefile:526: recipe for target 'runtest' failed
make: *** [runtest] Error 139

Not able to reproduce results after following Segnet tutorial

I have gone thru tutorials given on SEGNET from the site http://mi.eng.cam.ac.uk/projects/segnet/tutorial.html.

I did exactly the same steps for SEGNET_BASIC and BAYGNET_SEGNET_BASIC since i had only 4GB GPU. Apart from that i have given only batch size of 1 instead of 4 to avoid out of memory bound. Results of SEGNET_BASIC and BAYGNET_SEGNET_BASIC are very from ground truth. Kindly requesting you to let me know what mistake i have done so that i can get decent results compared to ground truth Regards K S Chidanand Kumar

Comping with CUDA8 - CuDNN5

Hi, I am getting this error while compiling. Is the port complete ?
"int" is incompatible with parameter of type "cudnnNanPropagation_t"

Using CMake to configure build:

-- CUDA detected: 8.0
-- Found cuDNN: ver. 5.0.5 found (include: /usr/local/cuda/include, library: /usr/local/cuda/lib64/libcudnn.so)
-- Added CUDA NVCC flags for: sm_52 sm_30

The screen just turn off and I am not able to use it, Caffe-Segnet Cuda 8.0, cuddnn 5, webcam_demo.py

Issue summary

My caffe-segnet is build and working with cuda, But when I run it with
webcam_demo.py, It shows output for a while and then display is turned off, And The system is hang. I have to manually power off and turn on again.

I am unable to use segnet.

GPU = GTX 960
RAM = 4GB DDR3
CPU = i3 4th gen

Your system configuration

Operating system: Ubuntu 16.04
Compiler:
CUDA version (if applicable): 8.0
CUDNN version (if applicable): 5
BLAS: atlas
Python or MATLAB version (for pycaffe and matcaffe respectively): py27

make error! my GPU compute is 75 maybe too high to run? how can i solve this

Building NVCC (Device) object src/caffe/CMakeFiles/cuda_compile_1.dir/util/cuda_compile_1_generated_math_functions.cu.o
nvcc fatal : Unsupported gpu architecture 'compute_75'
CMake Error at cuda_compile_1_generated_math_functions.cu.o.Release.cmake:220 (message):
Error generating
/home/lyx/caffe-segnet-cudnn7-b37d681223c15cb7a65181ad675fca54f7b02e9d/cmake_build/src/caffe/CMakeFiles/cuda_compile_1.dir/util/./cuda_compile_1_generated_math_functions.cu.o

src/caffe/CMakeFiles/caffe.dir/build.make:495: recipe for target 'src/caffe/CMakeFiles/cuda_compile_1.dir/util/cuda_compile_1_generated_math_functions.cu.o' failed
make[2]: *** [src/caffe/CMakeFiles/cuda_compile_1.dir/util/cuda_compile_1_generated_math_functions.cu.o] Error 1
CMakeFiles/Makefile2:336: recipe for target 'src/caffe/CMakeFiles/caffe.dir/all' failed
make[1]: *** [src/caffe/CMakeFiles/caffe.dir/all] Error 2
Makefile:135: recipe for target 'all' failed
make: *** [all] Error 2

Training problem

Hi,

I have a problem about training.

I want to use your model to train my task. And I just replace your dataset with mine (I also change the output to 2). When I train the model, I found if I loaded the pretrianed model (e.g., vgg16), there would be a constant loss (5.723e6). And the results rea always the same class.

Do you have any idea about the problem?

Thanks,

Training segnet with city Scapes Data set

Hi,
I was trying to train the segnet using the city scapes data set However i faced issues.
like
out of memory

for which I thought I will resize the image to 480x360
Then the next issue was
annotations_problem

which is yet to be solved. is it because of the annotations provided by city scapes dataset has a problem with segnet if so how can i solve it.

In short i would like to know how to train the segnet using the city scapes data set.

Thank You!
savio

Using Validation Dataset as a part of training Segnet

Hi,

I wish to use val.txt file and validate my data during training process. If I have to add validation during training process, how do I handle Batch Normalization ? with respect to that what kind of changes are needed in the train.prototxt ?

Use with cudnn v6 and v7

Hello

I can use remote nvidia-gpu system that I do not have root and can't install software (so apt-get or dpkg).
The system admin installed then-lastest version of drivers, cuda8 and cudnn v6. (now the v7 is already out).

The version on system is v6 and admin won't downgrade to v5 just because of me (multiple users). Is there any way to install local cudnn and use PATH or some other variable? (ubuntu 16.04 is installed)

Test accuracy changes with test batch size

Issue summary

validation accuracy changes when batch_size value changes.
opened in bvlc caffe. BVLC/caffe#5621 (comment)

Steps to reproduce

see above link.
I'm using caffe-segnet (the newest version). While do validation during training, I found that the test accuracy changes when I change batch size in TEST phase.

weighted softmax loss doesn't work in this version

Hi,

I find that the softmax_loss layer doesn't have the implementation of specifying weights for different classes while the older version contains this implementation. Could you please add it? Thanks!

opencv issue

Please use the caffe-users list for usage, installation, or modeling questions, or other requests for help.
Do not post such requests to Issues. Doing so interferes with the development of Caffe.

Please read the guidelines for contributing before submitting this issue.

Issue summary

Steps to reproduce

If you are having difficulty building Caffe or training a model, please ask the caffe-users mailing list. If you are reporting a build error that seems to be due to a bug in Caffe, please attach your build configuration (either Makefile.config or CMakeCache.txt) and the output of the make (or cmake) command.

-- ******************* Caffe Configuration Summary *******************
-- General:
-- Version : 1.0.0-rc3
-- Git : abcf30d-dirty
-- System : Linux
-- C++ compiler : /bin/c++
-- Release CXX flags : -O3 -DNDEBUG -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Debug CXX flags : -g -fPIC -Wall -Wno-sign-compare -Wno-uninitialized
-- Build type : Release

-- BUILD_SHARED_LIBS : ON
-- BUILD_python : ON
-- BUILD_matlab : OFF
-- BUILD_docs : ON
-- CPU_ONLY : OFF
-- USE_OPENCV : ON
-- USE_LEVELDB : ON
-- USE_LMDB : ON
-- ALLOW_LMDB_NOLOCK : OFF

-- Dependencies:
-- BLAS : Yes (Open)
-- Boost : Yes (ver. 1.53)
-- glog : Yes
-- gflags : Yes
-- protobuf : Yes (ver. 2.5.0)
-- lmdb : Yes (ver. 0.9.18)
-- LevelDB : Yes (ver. 1.12)
-- Snappy : Yes (ver. 1.1.0)
-- OpenCV : Yes (ver. )
-- CUDA : Yes (ver. 8.0)

-- NVIDIA CUDA:
-- Target GPU(s) : Auto
-- GPU arch(s) : sm_37
-- cuDNN : Not found

-- Python:
-- Interpreter : /bin/python2.7 (ver. 2.7.5)
-- Libraries : /usr/lib64/libpython2.7.so (ver 2.7.5)
-- NumPy : /home/bramin/.local/lib/python2.7/site-packages/numpy/core/include (ver 1.7.1)

-- Documentaion:
-- Doxygen : /bin/doxygen (1.8.5)
-- config_file : /scratch/bramin/caffe/SegNet/caffe-segnet-cudnn5/.Doxyfile

-- Install:
-- Install path : /scratch/bramin/caffe/SegNet/caffe-segnet-cudnn5/build/install

-- Configuring done

I am trying to build this using cmake and I have installed opencv 3.1.0 in my .local directory. I have given the OpenCV_DIR in Cmakelist as follows:

set(OpenCV_INCLUDE_DIRS "/home/bramin/.local/lib/opencv/include")
set(OpenCV_LIBS "/home/bramin/.local/lib/opencv/lib/libopencv_core.so")
set(OpenCV_CONFIG_PATH "/home/bramin/.local/lib/opencv/lib/pkgconfig/opencv.pc")

---[ OpenCV

if(USE_OPENCV)
set(OpenCV_DIR "/home/bramin/.local/lib/opencv/")
include_directories(SYSTEM ${OpenCV_INCLUDE_DIRS})
list(APPEND Caffe_LINKER_LIBS ${OpenCV_LIBS})
message(STATUS "OpenCV found (${OpenCV_CONFIG_PATH})")
add_definitions(-DUSE_OPENCV)
endif()

But while doing make all I am getting following errors:
[ 97%] [ 98%] Building CXX object tools/CMakeFiles/extract_features.dir/extract_features.cpp.o
Building CXX object tools/CMakeFiles/device_query.dir/device_query.cpp.o
Linking CXX executable cifar10/convert_cifar_data
Linking CXX executable device_query
Linking CXX executable siamese/convert_mnist_siamese_data
Linking CXX executable mnist/convert_mnist_data
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [examples/cifar10/convert_cifar_data] Error 1
make[1]: *** [examples/CMakeFiles/convert_cifar_data.dir/all] Error 2
make[1]: *** Waiting for unfinished jobs....
Linking CXX executable compute_image_mean
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [examples/siamese/convert_mnist_siamese_data] Error 1
make[1]: *** [examples/CMakeFiles/convert_mnist_siamese_data.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [examples/mnist/convert_mnist_data] Error 1
make[1]: *** [examples/CMakeFiles/convert_mnist_data.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/compute_image_mean] Error 1
make[1]: *** [tools/CMakeFiles/compute_image_mean.dir/all] Error 2
Linking CXX executable convert_imageset
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/convert_imageset] Error 1
make[1]: *** [tools/CMakeFiles/convert_imageset.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/device_query] Error 1
make[1]: *** [tools/CMakeFiles/device_query.dir/all] Error 2
[ 98%] [ 98%] [100%] Building CXX object tools/CMakeFiles/caffe.bin.dir/caffe.cpp.o
Building CXX object examples/CMakeFiles/test_segmentation.dir/SegNet_with_C++/test_segmentation.cpp.o
Building CXX object tools/CMakeFiles/test_net.dir/test_net.cpp.o
Linking CXX executable upgrade_solver_proto_text
Linking CXX executable train_net
Linking CXX executable net_speed_benchmark
Linking CXX executable upgrade_net_proto_text
Linking CXX executable upgrade_net_proto_binary
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/upgrade_solver_proto_text] Error 1
make[1]: *** [tools/CMakeFiles/upgrade_solver_proto_text.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/net_speed_benchmark] Error 1
make[1]: *** [tools/CMakeFiles/net_speed_benchmark.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/train_net] Error 1
make[1]: *** [tools/CMakeFiles/train_net.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/upgrade_net_proto_text] Error 1
make[1]: *** [tools/CMakeFiles/upgrade_net_proto_text.dir/all] Error 2
Linking CXX executable finetune_net
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/upgrade_net_proto_binary] Error 1
make[1]: *** [tools/CMakeFiles/upgrade_net_proto_binary.dir/all] Error 2
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/finetune_net] Error 1
make[1]: *** [tools/CMakeFiles/finetune_net.dir/all] Error 2
Linking CXX executable extract_features
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/extract_features] Error 1
make[1]: *** [tools/CMakeFiles/extract_features.dir/all] Error 2
Linking CXX executable cpp_classification/classification
CMakeFiles/classification.dir/cpp_classification/classification.cpp.o: In function Classifier::Preprocess(cv::Mat const&, std::vector<cv::Mat, std::allocator<cv::Mat> >*)': classification.cpp:(.text+0x26a): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
classification.cpp:(.text+0x3bc): undefined reference to cv::resize(cv::_InputArray const&, cv::_OutputArray const&, cv::Size_<int>, double, double, int)' classification.cpp:(.text+0xa47): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
classification.cpp:(.text+0xca5): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)' classification.cpp:(.text+0xd1e): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
CMakeFiles/classification.dir/cpp_classification/classification.cpp.o: In function main': classification.cpp:(.text.startup+0x1ef): undefined reference to cv::imread(cv::String const&, int)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [examples/cpp_classification/classification] Error 1
make[1]: *** [examples/CMakeFiles/classification.dir/all] Error 2
Linking CXX executable test_net
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/test_net] Error 1
make[1]: *** [tools/CMakeFiles/test_net.dir/all] Error 2
Linking CXX executable SegNet_with_C++/test_segmentation
CMakeFiles/test_segmentation.dir/SegNet_with_C++/test_segmentation.cpp.o: In function Classifier::Preprocess(cv::Mat const&, std::vector<cv::Mat, std::allocator<cv::Mat> >*)': test_segmentation.cpp:(.text+0x127): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
test_segmentation.cpp:(.text+0x260): undefined reference to cv::resize(cv::_InputArray const&, cv::_OutputArray const&, cv::Size_<int>, double, double, int)' test_segmentation.cpp:(.text+0x716): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
test_segmentation.cpp:(.text+0x955): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)' test_segmentation.cpp:(.text+0x9ce): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
CMakeFiles/test_segmentation.dir/SegNet_with_C++/test_segmentation.cpp.o: In function Classifier::Visualization(caffe::Blob<float>*, std::string)': test_segmentation.cpp:(.text+0x161a): undefined reference to cv::cvtColor(cv::_InputArray const&, cv::_OutputArray const&, int, int)'
test_segmentation.cpp:(.text+0x16fe): undefined reference to cv::imread(cv::String const&, int)' test_segmentation.cpp:(.text+0x18b1): undefined reference to cv::imshow(cv::String const&, cv::_InputArray const&)'
test_segmentation.cpp:(.text+0x18c0): undefined reference to cv::waitKey(int)' CMakeFiles/test_segmentation.dir/SegNet_with_C++/test_segmentation.cpp.o: In function main':
test_segmentation.cpp:(.text.startup+0x157): undefined reference to cv::imread(cv::String const&, int)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator >&, std::vector<int, std::allocator > const&)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)' collect2: error: ld returned 1 exit status make[2]: *** [examples/SegNet_with_C++/test_segmentation] Error 1 make[1]: *** [examples/CMakeFiles/test_segmentation.dir/all] Error 2 Linking CXX executable caffe ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imread(cv::String const&, int)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imencode(cv::String const&, cv::_InputArray const&, std::vector<unsigned char, std::allocator<unsigned char> >&, std::vector<int, std::allocator<int> > const&)' ../lib/libcaffe.so.1.0.0-rc3: undefined reference to cv::imdecode(cv::_InputArray const&, int)'
../lib/libcaffe.so.1.0.0-rc3: undefined reference to `cv::resize(cv::_InputArray const&, cv::OutputArray const&, cv::Size, double, double, int)'
collect2: error: ld returned 1 exit status
make[2]: *** [tools/caffe] Error 1
make[1]: *** [tools/CMakeFiles/caffe.bin.dir/all] Error 2
Linking CXX shared library ../lib/_caffe.so
Creating symlink /scratch/bramin/caffe/SegNet/caffe-segnet-cudnn5/python/caffe/_caffe.so -> /scratch/bramin/caffe/SegNet/caffe-segnet-cudnn5/build/lib/_caffe.so
[100%] Built target pycaffe
make: *** [all] Error 2

Please help me solve the problem.

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