thank your code and how to train?

[zilesazoyi2]

Hi @tensorboy,
your paper and code helps me a lot !thank you !

Could you please give me an guidance about how to train the model on pytorch ?

I did this and the result is here
Training

cd training; bash getData.sh to obtain the COCO images in dataset/COCO/images/, keypoints annotations in dataset/COCO/annotations/ and COCO official toolbox in `dataset/COCO/coco/ .
cd training/dataset/COCO/coco/PythonAPI; sudo python setup.py install to install pycocotools

sun@sunwin:~/0newcodedown/pytorchRealtime/training/dataset/COCO/coco/PythonAPI$ sudo python setup.py install
[sudo] sun 的密码：
Compiling pycocotools/_mask.pyx because it changed.
[1/1] Cythonizing pycocotools/_mask.pyx
running install
running build
running build_py
creating build
creating build/lib.linux-x86_64-2.7
creating build/lib.linux-x86_64-2.7/pycocotools
copying pycocotools/cocoeval.py -> build/lib.linux-x86_64-2.7/pycocotools
copying pycocotools/coco.py -> build/lib.linux-x86_64-2.7/pycocotools
copying pycocotools/init.py -> build/lib.linux-x86_64-2.7/pycocotools
copying pycocotools/mask.py -> build/lib.linux-x86_64-2.7/pycocotools
running build_ext
building 'pycocotools._mask' extension
creating build/temp.linux-x86_64-2.7
creating build/temp.linux-x86_64-2.7/pycocotools
creating build/common
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/numpy/core/include -I../common -I/usr/include/python2.7 -c pycocotools/_mask.c -o build/temp.linux-x86_64-2.7/pycocotools/_mask.o -Wno-cpp -Wno-unused-function -std=c99
x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -fno-strict-aliasing -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -fPIC -I/usr/local/lib/python2.7/dist-packages/numpy/core/include -I../common -I/usr/include/python2.7 -c ../common/maskApi.c -o build/temp.linux-x86_64-2.7/../common/maskApi.o -Wno-cpp -Wno-unused-function -std=c99
x86_64-linux-gnu-gcc -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -fno-strict-aliasing -DNDEBUG -g -fwrapv -O2 -Wall -Wstrict-prototypes -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security -Wl,-Bsymbolic-functions -Wl,-z,relro -Wdate-time -D_FORTIFY_SOURCE=2 -g -fstack-protector-strong -Wformat -Werror=format-security build/temp.linux-x86_64-2.7/pycocotools/_mask.o build/temp.linux-x86_64-2.7/../common/maskApi.o -o build/lib.linux-x86_64-2.7/pycocotools/_mask.so
running install_lib
creating /usr/local/lib/python2.7/dist-packages/pycocotools
copying build/lib.linux-x86_64-2.7/pycocotools/cocoeval.py -> /usr/local/lib/python2.7/dist-packages/pycocotools
copying build/lib.linux-x86_64-2.7/pycocotools/_mask.so -> /usr/local/lib/python2.7/dist-packages/pycocotools
copying build/lib.linux-x86_64-2.7/pycocotools/coco.py -> /usr/local/lib/python2.7/dist-packages/pycocotools
copying build/lib.linux-x86_64-2.7/pycocotools/init.py -> /usr/local/lib/python2.7/dist-packages/pycocotools
copying build/lib.linux-x86_64-2.7/pycocotools/mask.py -> /usr/local/lib/python2.7/dist-packages/pycocotools
byte-compiling /usr/local/lib/python2.7/dist-packages/pycocotools/cocoeval.py to cocoeval.pyc
byte-compiling /usr/local/lib/python2.7/dist-packages/pycocotools/coco.py to coco.pyc
byte-compiling /usr/local/lib/python2.7/dist-packages/pycocotools/init.py to init.pyc
byte-compiling /usr/local/lib/python2.7/dist-packages/pycocotools/mask.py to mask.pyc
running install_egg_info
Writing /usr/local/lib/python2.7/dist-packages/pycocotools-2.0.egg-info

and what to do next ? I want to train the model on my own laptop . but you caffe version ZheC/Realtime_Multi-Person_Pose_Estimation#70 just cant work .
thanks you a lot!

[tensorboy]

You may need a GPU server to train the model. :)
And I didn't implement the training part.

[MoonBunnyZZZ]

You didn't implement the training part.So how did you know the trained model is good or not?
@tensorboy

[tensorboy]

Try train.py