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It seams to be, that the project can be compiled in two different ways: by starting make in the project root or to use cmake (better in build directory). This may result in inconsistence. What is the better way to compile it?

I am getting out of memory error while running the demo using the following command. I am using GeForce GTX 1070.

python ./pose_demo.py image.png --out_name=prediction

INFO:estimate_pose:Done!
F1028 23:43:02.663663 10368 syncedmem.cpp:56] Check failed: error == cudaSuccess (2 vs. 0)  out of memory
*** Check failure stack trace: ***
Aborted (core dumped)

your deepercut is about mulit person ,but u give single-person model,too.I want to know can i use your single-person model to meet mulit-person task? And when training detection,Is datasets must be a mulit-person dataset for mulit-person task?
please help me

Did you meet similar error before?

src/caffe/pose/transform_image.cpp:163:5: warning: ‘auto’ changes meaning in C++11; please remove it [-Wc++0x-compat]
auto t1_p = pad_to_3x3(t1);
^
src/caffe/pose/transform_image.cpp:163:10: error: ‘t1_p’ does not name a type
auto t1_p = pad_to_3x3(t1);
^
src/caffe/pose/transform_image.cpp:164:5: warning: ‘auto’ changes meaning in C++11; please remove it [-Wc++0x-compat]
auto t2_p = pad_to_3x3(t2);
^
src/caffe/pose/transform_image.cpp:164:10: error: ‘t2_p’ does not name a type
auto t2_p = pad_to_3x3(t2);
^
src/caffe/pose/transform_image.cpp:165:19: error: ‘t1_p’ was not declared in this scope
cv::Mat res = t1_p * t2_p;

where is this file,can you share it?

When I run "make all pycaffe", I get the following error:

src/caffe/layers/pose_data_layer.cpp: In member function ‘virtual void caffe::PoseDataLayer::DataLayerSetUp(const std::vector<caffe::Blob>&, const std::vector<caffe::Blob>&)’:
src/caffe/layers/pose_data_layer.cpp:294:3: warning: ‘auto’ changes meaning in C++11; please remove it [-Wc++0x-compat]
auto joint_stats_file = this->layer_param().pose_data_param().has_joint_pairs_stats() ?
^
src/caffe/layers/pose_data_layer.cpp:294:8: error: ‘joint_stats_file’ does not name a type
auto joint_stats_file = this->layer_param().pose_data_param().has_joint_pairs_stats() ?
^
src/caffe/layers/pose_data_layer.cpp:298:43: error: ‘joint_stats_file’ was not declared in this scope
neighbour_stats_ = readMatricesFromFile(joint_stats_file);
^
src/caffe/layers/pose_data_layer.cpp: In member function ‘virtual void caffe::PoseDataLayer::load_batch(caffe::MultiBatch)’:
src/caffe/layers/pose_data_layer.cpp:515:9: error: ‘iota’ is not a member of ‘std’
std::iota(data_indices_.begin(), data_indices_.end(), 0);
^
src/caffe/layers/pose_data_layer.cpp: In instantiation of ‘void caffe::PoseDataLayer::DataLayerSetUp(const std::vector<caffe::Blob>&, const std::vector<caffe::Blob>&) [with Dtype = float]’:
src/caffe/layers/pose_data_layer.cpp:937:1: required from here
src/caffe/layers/pose_data_layer.cpp:290:7: warning: unused variable ‘num_labels’ [-Wunused-variable]
int num_labels = this->num_labels_;
^
src/caffe/layers/pose_data_layer.cpp: In instantiation of ‘void caffe::PoseDataLayer::load_batch(caffe::MultiBatch) [with Dtype = float]’:
src/caffe/layers/pose_data_layer.cpp:937:1: required from here
src/caffe/layers/pose_data_layer.cpp:573:9: warning: unused variable ‘num_labels’ [-Wunused-variable]
int num_labels = this->num_labels_;
^
src/caffe/layers/pose_data_layer.cpp:420:14: warning: unused variable ‘sequential’ [-Wunused-variable]
const bool sequential = this->layer_param_.pose_data_param().sequential();
^
src/caffe/layers/pose_data_layer.cpp: In instantiation of ‘void caffe::PoseDataLayer::DataLayerSetUp(const std::vector<caffe::Blob>&, const std::vector<caffe::Blob>&) [with Dtype = double]’:
src/caffe/layers/pose_data_layer.cpp:937:1: required from here
src/caffe/layers/pose_data_layer.cpp:290:7: warning: unused variable ‘num_labels’ [-Wunused-variable]
int num_labels = this->num_labels_;
^
src/caffe/layers/pose_data_layer.cpp: In instantiation of ‘void caffe::PoseDataLayer::load_batch(caffe::MultiBatch*) [with Dtype = double]’:
src/caffe/layers/pose_data_layer.cpp:937:1: required from here
src/caffe/layers/pose_data_layer.cpp:573:9: warning: unused variable ‘num_labels’ [-Wunused-variable]
int num_labels = this->num_labels_;
^
src/caffe/layers/pose_data_layer.cpp:420:14: warning: unused variable ‘sequential’ [-Wunused-variable]
const bool sequential = this->layer_param_.pose_data_param().sequential();
^
Makefile:563: recipe for target '.build_release/src/caffe/layers/pose_data_layer.o' failed
make: *** [.build_release/src/caffe/layers/pose_data_layer.o] Error 1

How can I fix that?

Thanks!

Is it possible to have ResNet-50 for this approach?

When I run "make all", I get the following error:

CXX src/caffe/layers/pose_data_layer.cpp
src/caffe/layers/pose_data_layer.cpp: In member function ‘virtual void caffe::PoseDataLayer::load_batch(caffe::MultiBatch*)’:
src/caffe/layers/pose_data_layer.cpp:615:59: error: there are no arguments to ‘DecodeDatumToCVMat’ that depend on a template parameter, so a declaration of ‘DecodeDatumToCVMat’ must be available [-fpermissive]
image = DecodeDatumToCVMat(image_cached.second, true);

src/caffe/layers/pose_data_layer.cpp: In instantiation of ‘void caffe::PoseDataLayer::load_batch(caffe::MultiBatch*) [with Dtype = float]’:
src/caffe/layers/pose_data_layer.cpp:937:1: required from here
src/caffe/layers/pose_data_layer.cpp:615:59: error: ‘DecodeDatumToCVMat’ was not declared in this scope
image = DecodeDatumToCVMat(image_cached.second, true);

How can I fix that?

Thanks!

a lot of warnings are thrown:

warning: ‘auto’ changes meaning in C++11

ubuntu 14.04:

/home/willi/deepcut-cnn/src/caffe/pose/segment_parts.cpp:157:20: error: ‘jnt’ was not declared in this scope

ubuntu 16.04:

/usr/include/string.h:652:42: error: ‘memcpy’ was not declared in this scope

ubuntu 16.04 after adding set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -D_FORCE_INLINES") to CMakeLists.txt:

/home/gdv/deepcut-cnn/src/caffe/layers/pose_data_layer.cpp:298:43: error: ‘joint_stats_file’ was not declared in this scope

there are some other errors, but I think that are the main one

i tried to compile it amd got some error in post_data_layer.cpp
i think the problem is from because of the compiler that i use.
There are some unused variable inside that code too.

Hi, I build the caffe successful and add the pose directory to the caffe dir,
when I test the image.png ,everything is ok.
but when i choose some pictures of mine,
it shows INFO:estimate_pose:Done!,and then
IndexError: boolean index did not match indexed array along dimension 0; dimension is 0 but corresponding boolean dimension is 16
how can i solve it .

Hi. Poses for single persons work great, however, I cannot seem to get it to correctly estimate the poses of more than 1 person. This should be possible right?

can you send the train code?thank you

Hello,

I can get prediction.npz file from image.png using pose_demo.py.

I want to get array of joints estimation npz file from many images.
for example, image0000.png, image0001.png, image0002,png, image####.png, ...
How can I get output prediction.npz file from this many images.

matrix shape of pose.npy in prediction.npz will be changed (number, 14) -> (number, 14, image_count)
I tested my own one image, I get pose.npy shape (5,14). But I want to many images at once.

I tried to input image as input folder.
I put all input images to images/ folder
and call
python pose_demo.py images/ --out_name=estimation

then I can get output file in estimation/ folder. but separated file image0001.png_pose.npz, image0002.png_pose.npz, ...

I want to put all pose.npy file to one estimation.npz file.

Please let me know which line I have to modify.

Thank you.

I have followed all procedures in README. However, when I finally try to run the demo.py, I get an error.
IndexError: boolean index did not match indexed array along dimension 0; dimension is 0 but corresponding boolean dimension is 16

I notice that an issue is similar with my problem, but I meet this error with the demo picture (image.png), so do someone can help me? Really appreciated.

Just ran your demo. Thanks for sharing!

Is there a simple way to identify which body parts are being detected for each dot? For instance, I'm trying to ID which body parts are being labelled by model in this image:

Is there anybody successfully build this code in window?

how to crop a single person img from the src image(MPII dataset)
I have read the annot mat,how to crop the single person from the infos
x1 y1 x2 y2 annopoints scale objpos ,how to calc the bound rect?
thank you