msracver / deep-image-analogy Goto Github PK

I already have preinstalled caffe docker bvlc/caffe and trying to make the project, but get this error:

deep_image_analogy/source/lbfgs.cu:17:9: warning: #pragma once in main file
 #pragma once
         ^
/usr/bin/ld: cannot find -lcaffe
collect2: error: ld returned 1 exit status

How can I fix it? I have caffe path exported to LD.

After successfully building Caffe, correctly configurating CUDA versions (see #15 if you have trouble), and making sure CommonSettings.props is copied over from Caffe, the build still fails.

Could find Eigen/Sparse, referenced in WLS.cpp.

when running "./deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0
"
on windows i am getting protobuf errors: https://gist.github.com/aycgit/fcd70d15eb48ea701291dc04256716bf

I am likely just very silly but i found this project interesting and wanted to try it

First off, thanks to the whole team for sharing the project!

Unfortunately (only concerning this particular project) i have a desktop machine with macOS and couldn't find a way to open/convert the .vcxproj files. I've tried MS Visual Studio and Visual Studio Code for Mac, but it didn't let me compile the project. These Apps are only shrinked down versions of the original Visual Studio .

Then i tried some tricks and tools to convert the .vcxproj content to regular make or cmake instruction files:

• vcxproj2cmake
• How to support both vcxproj to cmake on a project?
  

All ended with errors, some didn't even get past the first few files in the compile queue... Sadly i have no idea how to write a makefile (or make-config) myself – otherwise i wouldn't bother you.

So my question is: Did anyone of your team try to compile and run it on Linux or macOS?
If so, could you please ask them to write down a few steps or a small guide on how to compile it on other systems?

I've waited eagerly to try out the project since the first announcement of the paper on reddit and was a little bit disappointed when i saw that the files were only usable on Windows. But don't get me wrong – i'm still glad that the source files are available!

I have already compiled Caffe (from the official site) a few times with python2 & 3.x support, but for some reason with this project's version i can't get past the last steps of the build (some problem with missing functions for hdf5: "Undefined symbols for architecture x86_64: "_H5LTfind_dataset" and more).

And even if i did get Caffe running, i wouldn't know how to configure and make/compile the files in the windows/deep_image_analogy/source folder. I've tried to compile everything with nvcc but its either missing some include files – or when i include them manually it throws a lot of errors.

So any kind of help is deeply appreciated!

Hello,

I have been playing around with the pre-built demo provided and have had some success with it. However when I start to increase the weights on certain photos my system will hard crash. I have had success with ratio's up to around .6 and .7 but then it starts to be more likely that my system will crash.

I had disabled the TDR which allowed me to run ratios up to around .6 since before I was only able to get it to run around .2 or .3.

The system I am using has an 2 x Nvidia M6000 Quadro GPUs so I would imagine that memory should not be an issue, but after much debugging I am out of ideas.

Would there be any additional reason that would cause the crash or any additional settings I could play with?

Many thanks

when I run sh scripts/make_deep_image_analogy.sh, I encountered an error as below:
/usr/bin/ld: /tmp/tmpxft_00002d53_00000000-41_DeepAnalogy.o: undefined reference to symbol '_ZN2cv7imwriteERKNS_6StringERKNS_11_InputArrayERKSt6vectorIiSaIiEE' /usr/local/lib/libopencv_imgcodecs.so.3.2: error adding symbols: DSO missing from command line
opencv version: 3.2.0
caffe: up to date.
cuda: 7.5

when I loop many datas, I find my GPU memory become higher and higher! I hope someone could my issue.

I have installed caffe with CUDA successfully, but when i compile deep_image_analogy by
sh scripts/make_deep_image_analogy.sh
Error occurs:
/usr/bin/ld: /tmp/tmpxft_00001a5c_00000000-41_DeepAnalogy.o: undefined reference to symbol '_ZN2cv7imwriteERKNS_6StringERKNS_11_InputArrayERKSt6vectorIiSaIiEE' /usr/local/lib/libopencv_imgcodecs.so.3.2: error adding symbols: DSO missing from command line collect2: error: ld returned 1 exit status
I search it on the Net, it said that this may be related to my multy opencv version. I had opencv 2.4 and 3.2 in my ubuntu.
Below are files in "/usr/local/lib" related to libopencv_improc:

But i built caffe with opencv3.2.
How can i solve it ? I've been stucked here for 2 days.

Check failed: ReadProtoFromBinaryFile(param_file, param) Failed to parse NetParameter file: ../models/vgg19/VGG_ILSVRC_19_layers.caffemodel

hello and thanks for the code
this is happening on KDE neon user (Ubuntu 16.04)
I tried to recompile caffe without cudnn but same problem happens

./demo deep_image_analogy/models/ deep_image_analogy/demo/content.png deep_image_analogy/demo/style.png deep_image_analogy/demo/output/ 0 0.1 2 1
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:537] Reading dangerously large protocol message.  If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons.  To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:537] Reading dangerously large protocol message.  If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons.  To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING google/protobuf/io/coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Refining photo transfer.
Saving flow result.
Finished finding ann. Time : 121.885
*** Error in `./demo': free(): invalid pointer: 0x0000000002281d10 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7f00373a67e5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8037a)[0x7f00373af37a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7f00373b353c]
/usr/lib/x86_64-linux-gnu/libprotobuf.so.9(_ZN6google8protobuf8internal28DestroyDefaultRepeatedFieldsEv+0x1f)[0x7f002eb5e8af]
/usr/lib/x86_64-linux-gnu/libprotobuf.so.9(_ZN6google8protobuf23ShutdownProtobufLibraryEv+0x8b)[0x7f002eb5db3b]
/usr/lib/x86_64-linux-gnu/libmirprotobuf.so.3(+0x233b9)[0x7f001d3ea3b9]
/lib64/ld-linux-x86-64.so.2(+0x10de7)[0x7f003cdc9de7]
/lib/x86_64-linux-gnu/libc.so.6(+0x39ff8)[0x7f0037368ff8]
/lib/x86_64-linux-gnu/libc.so.6(+0x3a045)[0x7f0037369045]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf7)[0x7f003734f837]
./demo[0x407729]

I have downloaded the model and installed CUDA, but the demo still does not run. In another issue, it was mentioned that this project doesn't need cuDNN, but I have it extracted anyway.

>C:\Deep-Image-Analogy\windows\deep_image_analogy\exe>deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message.  If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons.  To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message.  If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons.  To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
F0705 13:44:12.492667 10008 cudnn_conv_layer.cu:28] Check failed: status == CUDNN_STATUS_SUCCESS (8 vs. 0)  CUDNN_STATUS_EXECUTION_FAILED

I got this error while running the exe, the last few output messages are as follows:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total num
ber of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
F0525 12:35:32.850440 182776 cudnn_conv_layer.cu:28] Check failed: status == CUD
NN_STATUS_SUCCESS (8 vs. 0) CUDNN_STATUS_EXECUTION_FAILED
*** Check failure stack trace: ***

I am getting some fascinating results with this (quite amazing at times), but the resolution is somewhat limited. When I attempt higher resolutions (near the 700x700 limit) or ratios (over 1.0) I get what I assume are GPU out of memory errors like: "cudnn_conv_layer.cu:28] Check failed: status == CUDNN_STATUS_SUCCESS (8 vs. 0) CUDNN_STATUS_EXECUTION_FAILED)". These occur at the later layers of PatchMatch (usually layer:conv2_1).

Are there any possible avenues to increase the resolution of content and style and output? Where are the main memory bottlenecks? Is it within PatchMatch or elsewhere? It's a little confusing because my GPU memory consumption seems quite low (2-3GB) even right before the error occurs.

I am running on a 1080ti (11GB), and I would love to be able to generate higher resolution output if at all possible. Any further guidance or info would be much appreciated.

or it can only use pre-trained models?

Calling the problem as:
.\deep_image_analogy.exe .\models\ .\demo\content.png .\demo\style.png .\demo\output\ 0 0.2 2 0

results following output:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the
message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To
increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the
message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Saving flow result.
Finished finding ann. Time : 18.003
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0821 10:30:06.521260 7252 syncedmem.hpp:31] Check failed: error == cudaSuccess (30 vs. 0) unknown error
*** Check failure stack trace: ***

I have built the source myself successfuly, using
compute_20,sm_20;compute_30,sm_30;compute_35,sm_35;compute_50,sm_50
Some sort of result is generated, but it doesn't look in any way how it should.

I am using GeForce GT770 GPU, nvidia-smi -a output:

nvidia-smi -a

==============NVSMI LOG==============

Timestamp : Mon Aug 21 10:37:11 2017
Driver Version : 385.28

Attached GPUs : 1
GPU 00000000:01:00.0
Product Name : GeForce GTX 770
Product Brand : GeForce
Display Mode : N/A
Display Active : N/A
Persistence Mode : N/A
Accounting Mode : N/A
Accounting Mode Buffer Size : N/A
Driver Model
Current : WDDM
Pending : WDDM
Serial Number : N/A
GPU UUID : GPU-9121e671-08cd-817a-2db6-405946935dda
Minor Number : N/A
VBIOS Version : 80.04.EB.00.4C
MultiGPU Board : N/A
Board ID : N/A
GPU Part Number : N/A
Inforom Version
Image Version : N/A
OEM Object : N/A
ECC Object : N/A
Power Management Object : N/A
GPU Operation Mode
Current : N/A
Pending : N/A
GPU Virtualization Mode
Virtualization mode : N/A
PCI
Bus : 0x01
Device : 0x00
Domain : 0x0000
Device Id : 0x118410DE
Bus Id : 00000000:01:00.0
Sub System Id : 0x28251462
GPU Link Info
PCIe Generation
Max : N/A
Current : N/A
Link Width
Max : N/A
Current : N/A
Bridge Chip
Type : N/A
Firmware : N/A
Replays since reset : 0
Tx Throughput : N/A
Rx Throughput : N/A
Fan Speed : 34 %
Performance State : P8
Clocks Throttle Reasons : N/A
FB Memory Usage
Total : 2048 MiB
Used : 245 MiB
Free : 1803 MiB
BAR1 Memory Usage
Total : N/A
Used : N/A
Free : N/A
Compute Mode : Default
Utilization
Gpu : N/A
Memory : N/A
Encoder : N/A
Decoder : N/A
Encoder Stats
Active Sessions : N/A
Average FPS : N/A
Average Latency : N/A
Ecc Mode
Current : N/A
Pending : N/A
ECC Errors
Volatile
Single Bit
Device Memory : N/A
Register File : N/A
L1 Cache : N/A
L2 Cache : N/A
Texture Memory : N/A
Texture Shared : N/A
CBU : N/A
Total : N/A
Double Bit
Device Memory : N/A
Register File : N/A
L1 Cache : N/A
L2 Cache : N/A
Texture Memory : N/A
Texture Shared : N/A
CBU : N/A
Total : N/A
Aggregate
Single Bit
Device Memory : N/A
Register File : N/A
L1 Cache : N/A
L2 Cache : N/A
Texture Memory : N/A
Texture Shared : N/A
CBU : N/A
Total : N/A
Double Bit
Device Memory : N/A
Register File : N/A
L1 Cache : N/A
L2 Cache : N/A
Texture Memory : N/A
Texture Shared : N/A
CBU : N/A
Total : N/A
Retired Pages
Single Bit ECC : N/A
Double Bit ECC : N/A
Pending : N/A
Temperature
GPU Current Temp : 39 C
GPU Shutdown Temp : N/A
GPU Slowdown Temp : N/A
Memory Temp : N/A
Power Readings
Power Management : N/A
Power Draw : N/A
Power Limit : N/A
Default Power Limit : N/A
Enforced Power Limit : N/A
Min Power Limit : N/A
Max Power Limit : N/A
Clocks
Graphics : N/A
SM : N/A
Memory : N/A
Video : N/A
Applications Clocks
Graphics : N/A
Memory : N/A
Default Applications Clocks
Graphics : N/A
Memory : N/A
Max Clocks
Graphics : N/A
SM : N/A
Memory : N/A
Video : N/A
Max Customer Boost Clocks
Graphics : N/A
Clock Policy
Auto Boost : N/A
Auto Boost Default : N/A
Processes : N/A

Hi,
When I run demo file on system, single command uses 1.5GB.
My Nvidia card is gtx 1070 having 8 GB GPU memrory.
So I can only run maximum 5 commands at a time (in multiple terminals) otherwise other wise the usage of GPU exceeds from 8GB so more command cannot executed.
I want to execute at least 70 to 80 commands at once(through web service).
So is it possible with this Card...?
Thanks and regards

I am currently reading the paper and confused on what is actually considered as an attribute to transfer. It lists three things: color transfer, texture transfer, and style transfer.

In the example image of monalisa and avatar, looking at the image A', I made the following observation:

• it transferred the color, eyes and lips.

Then why didn't it transfer ears and nose?

What I understand is, it should only transfer color in this set of images. Eyes, lips, ears and nose are individual attributes of that person itself and it shouldn't change. Yes, it may be able to transfer style, i.e. if B' is a photo of girl with tiara headband, then it should transfer this style to A producing A'. But this isn't the case here..

In short, are we actually controlling the attributes to transfer? Or the model takes decisions on its own?

Thank you..

I am currently trying to run the demo on a computer with GTX770 GPU (2GB memory) and I fail immidiately after launching with this error:

deep_image_analogy.exe ./models/ ./demo/content.png ./demo/style.png ./demo/output/ 0 0.5 2 0
(tried lowering the 0.5 to 0.2 and 0.1, same error each time)

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dang
erously large protocol message. If the message turns out to be larger than 2147
483647 bytes, parsing will be halted for security reasons. To increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in
google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total num
ber of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dang
erously large protocol message. If the message turns out to be larger than 2147
483647 bytes, parsing will be halted for security reasons. To increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in
google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total num
ber of bytes read was 574671192
F0815 08:27:29.018703 876 pooling_layer.cu:212] Check failed: error == cudaSuc
cess (8 vs. 0) invalid device function
*** Check failure stack trace: ***

I have been reading through some of the other issues and I concluded that I'm running out of memory, since some other users have been having similar problems with much better GPUs than the one I have. Is there a minimal GPU requirement to run this program? I had a feeling that that my GPU was written somewhere on a list of GPUs used to test this app, but apparently that is not the case.
Also, is my conclusion correct, or is this a complety different error?

I'm using CUDA 7.5, cuDNN 4, Visual Studio 2013 and Windows 7

The file does exist, and I have also compiled the source file, it doesn't go wrong.

Branch -> Linux leads to a 404 error from github. Can view the Master branch and the Linux branch

After I compiled caffe and tested it successfully, and then I followed the Configure & Build(Linux version).
While I executing "sh scripts/config_deep_image_analogy.sh", the error prompt is like this:

nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
./include/caffe/parallel.hpp(99): warning: type qualifier on return type is meaningless

./include/caffe/parallel.hpp(99): warning: type qualifier on return type is meaningless

deep_image_analogy/source/lbfgs.cu:17:9: warning: #pragma once in main file
#pragma once
^
deep_image_analogy/source/lbfgs.cu:17:9: warning: #pragma once in main file
#pragma once
^
/tmp/tmpxft_00002e95_00000000-29_Classifier.o：在函数‘Classifier::Classifier(std::string const&, std::string const&)’中：
Classifier.cpp:(.text+0xa8)：对‘caffe::Net::Net(std::string const&, caffe::Phase, int, std::vector<std::string, std::allocatorstd::string > const*, caffe::Net const*)’未定义的引用
Classifier.cpp:(.text+0xe7)：对‘caffe::Net::CopyTrainedLayersFrom(std::string)’未定义的引用
/tmp/tmpxft_00002e95_00000000-29_Classifier.o：在函数‘Classifier::Predict(cv::Mat const&, std::vector<std::string, std::allocatorstd::string >&, std::vector<float*, std::allocator<float*> >&, std::vector<float*, std::allocator<float*> >&, std::vector<Dim, std::allocator >&)’中：
Classifier.cpp:(.text+0x5bb)：对‘caffe::Net::blob_by_name(std::string const&) const’未定义的引用
/tmp/tmpxft_00002e95_00000000-29_Classifier.o：在函数‘std::string* google::MakeCheckOpString<int, int>(int const&, int const&, char const*)’中：
Classifier.cpp:(.text._ZN6google17MakeCheckOpStringIiiEEPSsRKT_RKT0_PKc[_ZN6google17MakeCheckOpStringIiiEEPSsRKT_RKT0_PKc]+0x7b)：对‘google::base::CheckOpMessageBuilder::NewString()’未定义的引用
/tmp/tmpxft_00002e95_00000000-30_Deconv.o：在函数‘my_cost_function::f_gradf(float const*, float*, float*)’中：
Deconv.cpp:(.text+0x7e)：对‘caffe::Net::blob_by_name(std::string const&) const’未定义的引用
Deconv.cpp:(.text+0xc4)：对‘caffe::Net::blob_by_name(std::string const&) const’未定义的引用
Deconv.cpp:(.text+0x1b2)：对‘caffe::Net::blob_by_name(std::string const&) const’未定义的引用
collect2: error: ld returned 1 exit status

I am a green hand to caffe and this project, so how should I fix this error?
Thanks a lot!

I got 2 1080Ti, is it possible to use both of it to speed it up ?
Thanks in advance

I followed all the procedure as proposed in Linux and run the demo. But the demo keeps running for over 10 minutes. And the gpu usage stays at 0%. What could be the problem?

I follow your step to run source code, but the resultAB.PNG resultBA.png not change,and flowAB.txt flowBA.txt data are all 0,what's happen?

Below is my setting,

windows/deep_image_analogy/models/ windows/deep_image_analogy/demo/content.png windows/deep_image_analogy/demo/style.png windows/deep_image_analogy/demo/output/ 0 0.5 2 0

and execute result,

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Saving flow result.
Finished finding ann. Time : 7.695

hi ,first of all,thanks for your great job ,I am trying to build your linux version Deep-Image-Analogy,I following your build scripts,but some errors come:
Do u know what problem is ,I am using the cmake ,the cmake command is something like this:

cmake .. -DCUDA_NVCC_FLAGS=" -D_MWAITXINTRIN_H_INCLUDED -D_FORCE_INLINES -D__STRICT_ANSI__" -DCMAKE_CXX_FLAGS=' -D_MWAITXINTRIN_H_INCLUDED -D_FORCE_INLINES -D__STRICT_ANSI__'

[ 18%] Building NVCC (Device) object src/caffe/CMakeFiles/cuda_compile.dir/layers/cuda_compile_generated_recurrent_layer.cu.o
/usr/include/c++/5/bits/stl_iterator_base_types.h(154): error: name followed by "::" must be a class or namespace name
detected during:
instantiation of class "std::__iterator_traits<_Iterator, void> [with _Iterator=int]"
(163): here
instantiation of class "std::iterator_traits<_Iterator> [with _Iterator=int]"
/home/public/git/LDeep-Image-Analogy/src/caffe/layers/box_annotator_ohem_layer.cu(55): here

/usr/include/c++/5/bits/stl_iterator_base_types.h(155): error: name followed by "::" must be a class or namespace name
detected during:
instantiation of class "std::__iterator_traits<_Iterator, void> [with _Iterator=int]"
(163): here
instantiation of class "std::iterator_traits<_Iterator> [with _Iterator=int]"
/home/public/git/LDeep-Image-Analogy/src/caffe/layers/box_annotator_ohem_layer.cu(55): here

/usr/include/c++/5/bits/stl_iterator_base_types.h(156): error: name followed by "::" must be a class or namespace name
detected during:
instantiation of class "std::__iterator_traits<_Iterator, void> [with _Iterator=int]"
(163): here
instantiation of class "std::iterator_traits<_Iterator> [with _Iterator=int]"
/home/public/git/LDeep-Image-Analogy/src/caffe/layers/box_annotator_ohem_layer.cu(55): here

/usr/include/c++/5/bits/stl_iterator_base_types.h(157): error: name followed by "::" must be a class or namespace name

Hello,

What are the minimal requirements for the GPU to run the demo:
deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0
?

I have nVIdia GTX 970 and Windows 8.1, and it crashes unfortunately somewhere in CUDA with the log:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dang
erously large protocol message. If the message turns out to be larger than 2147
483647 bytes, parsing will be halted for security reasons. To increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in
google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total num
ber of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dang
erously large protocol message. If the message turns out to be larger than 2147
483647 bytes, parsing will be halted for security reasons. To increase the limi
t (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in
google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total num
ber of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Saving flow result.
Finished finding ann. Time : 37.588
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0827 15:12:08.460532 6884 syncedmem.hpp:31] Check failed: error == cudaSuccess
(30 vs. 0) unknown error

This is both for exe-from-git, and for build by myself.

In Debug build I see the error:
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
F0827 15:41:30.334332 4332 pooling_layer.cu:212] Check failed: error == cudaSuc
cess (7 vs. 0) too many resources requested for launch

Best regards,
Fedor

<sorry, duplicate>

At first, I install protoc-2.6.1, but I get an error:

In file included from .build_release/src/caffe/proto/caffe.pb.cc:4:0:
.build_release/src/caffe/proto/caffe.pb.h:12:2: error: #error This file was generated by a newer version of protoc which is
#error This file was generated by a newer version of protoc which is
^
.build_release/src/caffe/proto/caffe.pb.h:13:2: error: #error incompatible with your Protocol Buffer headers. Please update
#error incompatible with your Protocol Buffer headers. Please update
^
.build_release/src/caffe/proto/caffe.pb.h:14:2: error: #error your headers.
#error your headers.
^
In file included from .build_release/src/caffe/proto/caffe.pb.cc:4:0:
.build_release/src/caffe/proto/caffe.pb.h:23:35: fatal error: google/protobuf/arena.h: No such file or directory
compilation terminated.
Makefile:582: recipe for target '.build_release/src/caffe/proto/caffe.pb.o' failed
make: *** [.build_release/src/caffe/proto/caffe.pb.o] Error 1

Then I install protoc-3.6.1 instead, but the error still exists.

I think this is because the protocol compiler (protoc) and the library header (/usr/include/google/protobuf) are inconsistent.

% protoc --version
libprotoc 3.6.1
% grep GOOGLE_PROTOBUF_VERSION /usr/include/google/protobuf/stubs/common.h
#define GOOGLE_PROTOBUF_VERSION 2006001

I am not the user of root, and the protoc is installed at my own dir.
So anyone could help me solve this problem?
Thanks!

I was unable to find any code relating to the sigmoid blending.
What are you using instead ?

Hi,

I've successfully built and now rebuilt Caffe with the following parameters:

        <CpuOnlyBuild>false</CpuOnlyBuild>
        <UseCuDNN>true</UseCuDNN>
        <CudaVersion>7.5</CudaVersion>
        <!-- NOTE: If Python support is enabled, PythonDir (below) needs to be
         set to the root of your Python installation. If your Python installation
         does not contain debug libraries, debug build will not work. -->
        <PythonSupport>true</PythonSupport>
        <!-- NOTE: If Matlab support is enabled, MatlabDir (below) needs to be
         set to the root of your Matlab installation. -->
        <MatlabSupport>true</MatlabSupport>
        <CudaDependencies></CudaDependencies>

        <!-- Set CUDA architecture suitable for your GPU.
         Setting proper architecture is important to mimize your run and compile time. -->
        <CudaArchitecture>compute_30,sm_30;compute_35,sm_35;compute_50,sm_50</CudaArchitecture>

        <!-- CuDNN 4 and 5 are supported -->
        <CuDnnPath></CuDnnPath>

I left empty but I unpacked the CuDNNv4 downloaded zip to the %CUDA_PATH% location (in my case C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5).

I have not done any of the deep_image_analogy build steps:

• Edit deep_image_analogy.vcxproj under windows/deep_image_analogy to make the CUDA version in it match yours .
• Open solution Caffe and add deep_image_analogy project.
• Build project deep_image_analogy.

When executing the provided pre-built executable file:

deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0

It results in the following error:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
F1005 13:11:47.450531 6872 pooling_layer.cu:212] Check failed: error == cudaSuccess (8 vs. 0) invalid device function
*** Check failure stack trace: ***

I'm running CUDA 7.5, cuDNN 4, Visual Studio 2013, MATLAB R2014b and Windows 10 with GeForce GTX 770 GPU.

From what I've read invalid device function indicates a CUDA / GPU incompatibility.

The GeForce GTX 770 GPU has compute capability 3.0 https://developer.nvidia.com/cuda-gpus, so when building Caffe, setting <CudaArchitecture>compute_30,sm_30;compute_35,sm_35;compute_52,sm_52</CudaArchitecture> should be correct, no?

Any info or assistance resolving this would be greatly appreciated.

Hi,

we were not able to start the ... application,
because of missing dll files.
They probably compiled for a other version.

Thanks
Patrick

Is it possibly o run in CPU model only?

I have installed caffe before.
So what can I do to run your demo without install caffe again?

Hi,
I have installed all required dependencies for Deep-Image-Analogy for cuda.
Now when I tried to compile project with this command
sh scripts/make_deep_image_analogy.sh
following error appear after a while...

/usr/bin/ld: /usr/lib/gcc/x86_64-linux-gnu/5/../../../../lib/libcaffe.a(common.o
//usr/lib/x86_64-linux-gnu/libgflags.so.2: error adding symbols: DSO missing fro
collect2: error: ld returned 1 exit status

can any one help me to resolve this problem
Thanks and regards

C:\deep_image_analogy\exe>deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Saving flow result.
Finished finding ann. Time : 43.575
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0526 19:49:36.182569 10584 syncedmem.hpp:31] Check failed: error == cudaSuccess (4 vs. 0) unspecified launch failure
*** Check failure stack trace: ***

hello，

when i run "sh scripts/make_deep_image_analogy.sh" to compile deep_image_analogy, there is an error happened:

/lib64/libgdk-x11-2.0.so.0: undefined reference to `XRRFreeMonitors'
/lib64/libgdk-x11-2.0.so.0: undefined reference to `XRRGetMonitors'

how should I fix this error?

thanks

deep_image_analogy.exe ../models/ ../demo/content.png ../demo/style.png ../demo/output/ 0 0.5 2 0
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
F1024 12:10:34.443341 32020 cudnn_conv_layer.cu:28] Check failed: status == CUDNN_STATUS_SUCCESS (8 vs. 0) CUDNN_STATUS_EXECUTION_FAILED
*** Check failure stack trace: ***

In the build description point 3 states:
"Open solution Caffe and add deep_image_analogy project."

What does 'solution Caffe' refer to?

Thank you.

When I run the demo on my GPU to generate the style image using the parameter 0 0.5 2 0, it cost totally 54s. And if I increase the 'Ratio' to 1, it will cost even 250s. Although the results are fantastic, the generation cost too much time.

So I want to ask that is there any method to increase the generation speed? I have change the VGG-19 to VGG-16 or ResNet-50. But their generation results are not pleased and the time can not decrease too much.

Any further guidance or info would be much appreciated.

I can't compile this no matter what I try with macOS 10.12.4.

sh scripts/make_deep_image_analogy.sh fails with deep_image_analogy/source/Classifier.h:3:10: fatal error: 'caffe/caffe.hpp' file not found no matter which I try to include caffe. I've compiled caffe that comes with this and I have compiled and tried caffe straight from the repo. I have tried to include caffe from both caffe build locations with relative paths and with absolute paths just to make sure but nothing works. caffe/caffe.hpp file always exists but the compiler just doesn't find it and I'm out of ideas what to try. Caffe runs its tests so the build should be ok.

I hope somebody would be kind and throw out some ideas what to try next to include caffe.hpp.

I've successfully built the project but anytime I run the generated executable with a ratio greater than 0.3, I get an error. I read that building Caffe without CUDNN can save memory, so I did that and then rebuilt the deep_image_analogy project as well:

1>------ Rebuild All started: Project: deep_image_analogy, Configuration: Release x64 ------
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\DeepAnalogy.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\DeepAnalogy.cu" -clean
1> DeepAnalogy.cu
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\GeneralizedPatchMatch.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\GeneralizedPatchMatch.cu" -clean
1> GeneralizedPatchMatch.cu
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\lbfgs.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\lbfgs.cu" -clean
1> lbfgs.cu
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\timer.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\timer.cu" -clean
1> timer.cu
1> Compiling CUDA source file source\DeepAnalogy.cu...
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -gencode=arch=compute_20,code="sm_20,compute_20" --use-local-env --cl-version 2013 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -cudart static -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\DeepAnalogy.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\DeepAnalogy.cu"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(352): warning : using-declaration ignored -- it refers to the current namespace
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(356): warning : using-declaration ignored -- it refers to the current namespace
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1158): warning : field of class type without a DLL interface used in a class with a DLL interface
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::ios_base::~ios_base"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::basic_ios<_Elem, _Traits>::~basic_ios [with _Elem=char, _Traits=std::char_traits]"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::basic_ostream<_Elem, _Traits>::~basic_ostream [with _Elem=char, _Traits=std::char_traits]"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "google::LogMessage::LogStream::~LogStream"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "google::NullStream::~NullStream"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(955): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvForestTree"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(1143): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvBoostTree"
1>C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\include\caffe/parallel.hpp(99): warning : type qualifier on return type is meaningless
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(352): warning : using-declaration ignored -- it refers to the current namespace
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(356): warning : using-declaration ignored -- it refers to the current namespace
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1158): warning : field of class type without a DLL interface used in a class with a DLL interface
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::ios_base::~ios_base"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::basic_ios<_Elem, _Traits>::~basic_ios [with _Elem=char, _Traits=std::char_traits]"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "std::basic_ostream<_Elem, _Traits>::~basic_ostream [with _Elem=char, _Traits=std::char_traits]"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "google::LogMessage::LogStream::~LogStream"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native\include\glog/logging.h(1573): warning : exception specification for virtual function "google::NullStreamFatal::~NullStreamFatal" is incompatible with that of overridden function "google::NullStream::~NullStream"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/core/affine.hpp(280): warning : controlling expression is constant
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(955): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvForestTree"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(1143): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvBoostTree"
1>C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\include\caffe/parallel.hpp(99): warning : type qualifier on return type is meaningless
1> DeepAnalogy.cu
1> Compiling CUDA source file source\GeneralizedPatchMatch.cu...
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -gencode=arch=compute_20,code="sm_20,compute_20" --use-local-env --cl-version 2013 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -cudart static -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\GeneralizedPatchMatch.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\GeneralizedPatchMatch.cu"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(955): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvForestTree"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(1143): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvBoostTree"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/core/affine.hpp(280): warning : controlling expression is constant
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(955): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvForestTree"
1>C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native\include\opencv2/ml/ml.hpp(1143): warning : overloaded virtual function "CvDTree::train" is only partially overridden in class "CvBoostTree"
1> GeneralizedPatchMatch.cu
1> Compiling CUDA source file source\lbfgs.cu...
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -gencode=arch=compute_20,code="sm_20,compute_20" --use-local-env --cl-version 2013 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -cudart static -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\lbfgs.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\lbfgs.cu"
1> lbfgs.cu
1> Compiling CUDA source file source\timer.cu...
1>
1> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy>"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\bin\nvcc.exe" -gencode=arch=compute_20,code="sm_20,compute_20" --use-local-env --cl-version 2013 -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\bin\x86_amd64" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\lmdb-v120-clean.0.9.14.0\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\LevelDB-vc120.1.2.0.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\protobuf-v120.2.6.1\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\boost.1.59.0.0\build\native....\lib\native\include\" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\gflags.2.1.2.1\build\native../..///build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\hdf5-v120-complete.1.8.15.2\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\glog.0.3.3.0\build\native../..//build/native/include/" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenBLAS.0.2.14.1\build\native....\lib\native\include" -I"C:\Projects\Deep-Image-Analogy-master\NugetPackages\OpenCV.2.4.10\build\native../../build/native/include/" -ID:\MSRA\Code\Project\caffe\include -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v7.5\include" --keep-dir x64\Release -maxrregcount=0 --machine 64 --compile -cudart static -DHAS_LMDB -DHAS_HDF5 -DHAS_OPENBLAS -DHAS_OPENCV -DNDEBUG -D_SCL_SECURE_NO_WARNINGS -DUSE_OPENCV -DUSE_LEVELDB -DUSE_LMDB -DMATLAB_MEX_FILE -DWITH_PYTHON_LAYER -DBOOST_PYTHON_STATIC_LIB -D_UNICODE -DUNICODE -Xcompiler "/EHsc /W1 /nologo /Ox /Zi /MD " -o C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\Int\deep_image_analogy\x64\Release\timer.cu.obj "C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows\deep_image_analogy\source\timer.cu"
1> timer.cu
1> Classifier.cpp
1> Deconv.cpp
1> main.cpp
1> WLS.cpp
1> Generating code
1> Finished generating code
1>LevelDb.lib(builder.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(builder.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(dbformat.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(dbformat.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(db_impl.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(db_impl.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(db_iter.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(db_iter.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(filename.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(filename.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(log_reader.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(log_reader.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(log_writer.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(log_writer.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(memtable.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(memtable.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(table_cache.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(table_cache.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(version_edit.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(version_edit.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(version_set.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(version_set.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(write_batch.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(write_batch.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(port_win.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(port_win.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(block.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(block.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(block_builder.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(block_builder.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(format.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(format.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(iterator.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(iterator.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(merger.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(merger.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(table.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(table.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(table_builder.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(table_builder.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(two_level_iterator.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(two_level_iterator.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(arena.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(arena.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(cache.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(cache.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(coding.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(coding.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(comparator.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(comparator.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(crc32c.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(crc32c.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(env.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(env.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(env_boost.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(env_boost.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(hash.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(hash.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(logging.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(logging.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(options.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(options.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(status.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(status.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1>LevelDb.lib(win_logger.obj) : warning LNK4099: PDB 'vc120.pdb' was not found with 'LevelDb.lib(win_logger.obj)' or at 'C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\Build\x64\Release\vc120.pdb'; linking object as if no debug info
1> deep_image_analogy.vcxproj -> C:\Projects\Deep-Image-Analogy-master\Deep-Image-Analogy-master\windows..\Build\x64\Release\deep_image_analogy.exe
========== Rebuild All: 1 succeeded, 0 failed, 0 skipped ==========

But still when executing the freshly built executable file at ratios greater than 0.3, it results in the following error:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
F1009 10:37:00.308190 6016 im2col.cu:61] Check failed: error == cudaSuccess (30 vs. 0) unknown error
*** Check failure stack trace: ***

I've seen this error as well:

[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:537] Reading dangerously large protocol message. If the message turns out to be larger than 2147483647 bytes, parsing will be halted for security reasons. To increase the limit (or to disable these warnings), see CodedInputStream::SetTotalBytesLimit() in google/protobuf/io/coded_stream.h.
[libprotobuf WARNING ..\src\google\protobuf\io\coded_stream.cc:78] The total number of bytes read was 574671192
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv5_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv4_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv3_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv2_1.
Finding nearest neighbor field using PatchMatch Algorithm at layer:conv1_1.
Refining photo transfer.
Saving flow result.
Finished finding ann. Time : 42.502
WARNING: Logging before InitGoogleLogging() is written to STDERR
F1009 12:23:23.964454 816 syncedmem.hpp:31] Check failed: error == cudaSuccess (4 vs. 0) unspecified launch failure
*** Check failure stack trace: ***

Does anyone have any insights into what may be happening?

I'm running CUDA 7.5, Visual Studio 2013, MATLAB R2014b and Windows 10 with GeForce GTX 770 GPU w/2GB.

Hi! I want to know how to output the correspondence map with deep image analogy, similar to the figures described in the paper. Thank you!

Hi，Just notice from the code that sth different between the code and the paper, is there any intend behind that ?

1. when deconv the next_layer = curr_layer +2 in the code, it means the conv4_1 is deconv by conv2_1 instead of conv3_1, but according to the paper next_layer should be equals curr_layer +1

2. because of the above implementation, the layer 1 ("conv4_1") is not computed by deconv.

i met a problem when run make_deep_image_analogy.sh
/usr/bin/ld: /tmp/tmpxft_000079ab_00000000-29_Classifier.o: undefined reference to symbol '_ZN2cv6String10deallocateEv'
//usr/local/lib/libopencv_core.so.3.2: error adding symbols: DSO missing from command line
collect2: error: ld returned 1 exit status
not like the libopencv_imgcodecs, I met the libopencv_core problem.
OPENCV version:3.2
Please help me.

I cannot find executable file "demo" in folder. (UBUNTU 16.04)
I have installed all dependencies, with cuda and cudnn. Now I want to execute demo file to get test result by using command
./demo deep_image_analogy/models/ deep_image_analogy/demo/content.png deep_image_analogy/demo/style.png deep_image_analogy/demo/output/ 0 0.5 2 0
as you mentioned ...
but I cannot find executable file "demo" in folder...
Can u help me to find its location...
Or How can i build it...
Thanks and regards