How to setup with CPU ONLY mode #123

eakbas · 2016-03-22T13:24:34Z

I'd like to install py-faster-rcnn in CPU ONLY mode. Is this possible? Which configuration files should I modify?

Thanks.

happyharrycn · 2016-03-22T22:44:57Z

It is definitely possible but not recommended. CPU version is almost two magnitude slower than GPU as I tested a few months ago. Here is a quick list of modifications.

Set USE_GPU_NMS in ./lib/fast_rcnn/config.py (or your YAML file) to False.
In ./tools/test_net.py / train_net.py, replace caffe.set_mode_gpu() with caffe_set_mode_cpu().
Plus, if you do not have a GPU, you can compile Caffe in CPU_ONLY mode (and also ignore the GPU nms code).

eakbas · 2016-03-23T08:47:33Z

I made the changes you mentioned. When I try to build the cython modules, i.e. after running

cd $FRCN_ROOT/lib; make

I get:

python setup.py build_ext --inplace
Traceback (most recent call last):
File "setup.py", line 58, in
CUDA = locate_cuda()
File "setup.py", line 46, in locate_cuda
raise EnvironmentError('The nvcc binary could not be '
EnvironmentError: The nvcc binary could not be located in your $PATH. Either add it to your path, or set $CUDAHOME
make: *** [all] Error 1

happyharrycn · 2016-03-23T17:43:11Z

As I said, you will need to ignore GPU nms code. You can do so by removing 'nms.gpu_nms' module in ./libs/setup.py.

dumka · 2016-04-05T13:50:32Z

@eakbas, I did everything as @happyharrycn recommended, including his last recommendation, but, anyway, I got the same error message as you did. But after that I removed line "CUDA = locate_cuda()" in ./lib/setup.py, after that I executed "cd $FRCN_ROOT/lib; make" and it went without error messages.

Mengmengbai · 2016-06-14T02:42:47Z

cd $FRCN_ROOT/lib， modify setup.py，annotate these code that are correlative GPU, then make

...
#CUDA = locate_cuda()
...
...
#self.set_executable('compiler_so', CUDA['nvcc'])
...
...
#Extension('nms.gpu_nms',

['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'],

library_dirs=[CUDA['lib64']],

libraries=['cudart'],

language='c++',

runtime_library_dirs=[CUDA['lib64']],

# this syntax is specific to this build system

# we're only going to use certain compiler args with nvcc and not with

# gcc the implementation of this trick is in customize_compiler() below

extra_compile_args={'gcc': ["-Wno-unused-function"],

'nvcc': ['-arch=sm_35',

'--ptxas-options=-v',

'-c',

'--compiler-options',

"'-fPIC'"]},

include_dirs = [numpy_include, CUDA['include']]

)

shubh-agrawal · 2016-08-25T16:45:39Z

@happyharrycn @eakbas @SrCMpink @dumka
I am trying to implement CPU_ONLY mode. I have followed this complete issue and made a clean make for ./lib. It gave no error. But upon running the demo from ./tools/demo.py it gave error as:

F0825 21:46:15.782125 7066 common.cpp:55] Cannot use GPU in CPU-only Caffe: check mode.

All modifications are made by me given in the post. Please suggest some solution.

mcdickenson · 2016-08-25T19:55:00Z

@shubh-agrawal Are you running demo.py with the --cpu option specified?

shubh-agrawal · 2016-08-26T01:49:54Z

No I haven't. I tried it out but came up with this error now,

[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 350:21: Message type "caffe.LayerParameter" has no field named "roi_pooling_param".
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0826 11:47:10.569231 2981 upgrade_proto.cpp:928] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: /home/shubh/py-faster-rcnn/models/pascal_voc/VGG16/faster_rcnn_alt_opt/faster_rcnn_test.pt
*** Check failure stack trace: ***
Aborted (core dumped)

Any idea about this?

sandeeppalakkal · 2016-08-26T11:41:30Z

Can you try for --net zf and update the results?

mcdickenson · 2016-08-26T16:46:14Z

@shubh-agrawal That looks to me like the caffe-fast-rcnn submodule is on the wrong branch. If you cd into that directory and run git checkout faster-rcnn and then rerun the demo (with the ZF net as @sandeeppalakkal suggests) what happens?

shubh-agrawal · 2016-08-26T20:21:17Z

You guys solved the problem. Thank you guys. The demo worked seamlessly. @mcdickenson @sandeeppalakkal

But I would update one more modification, here, so that other fellows following similar problem could follow up. There is nms_wrapper.py which still uses nms_gpu module. Hence, it was necessary to comment out piece of code related to that in $FRCN_ROOT/lib/fast_rcnn/nms_wrapper.py.
Uncomment the import module for nms_gpu. Rest making modification as discusses in this issue will solve the problem.

I wonder, why not any documentation with much needed modification for ONLY_CPU is found over the air.

divamgupta · 2016-09-27T14:44:54Z

@mcdickenson I all the things mentioned above but I got the floowing error

[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 47:11: Message type "caffe.LRNParameter" has no field named "engine".

How should I go about this?

mcdickenson · 2016-09-27T15:09:40Z

@divamgupta I'm not sure, I haven't encountered that before. It might be worth opening a separate issue for that. Are you building from master?

shubh-agrawal · 2016-09-27T16:35:01Z

@divamgupta I had encountered this error before. It occurs if you are on master branch of caffe-fast-rcnn. Please checkout to other branch that will be enlisted in git branch.
I hope this helps !

divamgupta · 2016-09-28T04:03:12Z

I used the faster-rcnn branch. This problem is only arising in the zf model only. vgg16 is working fine.

brisker · 2016-10-02T12:45:53Z

@divamgupta
Have you solved this problem?
[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 47:11: Message type "caffe.LRNParameter" has no field named "engine".

mcdickenson · 2017-02-22T06:58:08Z

The meaning of `git checkout faster-rcnn` is to checkout the "faster-rcnn" branch. See the above discussion about the issue on the master branch.

…

On Wed, Feb 22, 2017 at 12:06 PM IvyGongoogle ***@***.***> wrote: @mcdickenson <https://github.com/mcdickenson> @shubh-agrawal <https://github.com/shubh-agrawal> @sandeeppalakkal <https://github.com/sandeeppalakkal> when I run 'tools/demo.py', I get the same error [libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 350:21: Message type "caffe.LayerParameter" has no field named "roi_pooling_param". WARNING: Logging before InitGoogleLogging() is written to STDERR F0222 14:23:16.447522 29479 upgrade_proto.cpp:88] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: /home/ztgong/objectDetectionAndRecognition/py-faster-rcnn/models/pascal_voc/VGG16/faster_rcnn_alt_opt/ faster_rcnn_test.pt *** Check failure stack trace: *** but I do not understand the meaning of git checkout faster-rcnn' how to solve this error? thankyou very much! — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub <#123 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABC0-K3bjhUfm8PPWHDNRbIQx-qY9MTXks5re9dYgaJpZM4H2FbP> .

Anhaoxu · 2017-03-05T05:06:55Z

@happyharrycn @dumka @SrCMpink @shubh-agrawal @eakbas
Can you help me to see this problem,thanks!
http://stackoverflow.com/questions/42604481/faster-rcnn-demo-py-all-300-object-proposals-without-output-results#

GongXinyuu · 2017-03-22T05:20:30Z

Hey guys, I found this solution works.
Comment these code in lib/setup.py
`#CUDA = locate_cuda()`

`#self.set_executable('compiler_so', CUDA['nvcc'])`

`
#Extension('nms.gpu_nms',

#['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'],

#library_dirs=[CUDA['lib64']],

#libraries=['cudart'],

#language='c++',

#runtime_library_dirs=[CUDA['lib64']],

#this syntax is specific to this build system

#we're only going to use certain compiler args with nvcc and not with

#gcc the implementation of this trick is in customize_compiler() below

#extra_compile_args={'gcc': ["-Wno-unused-function"],

#'nvcc': ['-arch=sm_35',

#'--ptxas-options=-v',

#'-c',

#'--compiler-options',

#"'-fPIC'"]},

#include_dirs = [numpy_include, CUDA['include']]

#),

`

And then
make

Anhaoxu · 2017-03-22T06:34:34Z

@GloryDream
Did you find there are lots of repetitive bbox in the result pictures displayed in demo.py?
I just make it in windows10 and use CPU mode,too.

GongXinyuu · 2017-03-26T11:41:31Z

@Anhaoxu
Sorry, I didn't run it successfully on my mac.

danielaRiesgo · 2017-09-26T20:12:54Z

@divamgupta could you solve it? I get a segmentation fault even when I don't specify --net zf.

rbgirshick#123 (comment)

PapaMadeleine2022 · 2017-11-22T08:38:20Z

for test, you just need too run './tools/demo.py --cpu'.
for end2end train, as there is only Forward_gpu implementation in smooth_L1_loss_layer.cu for SmoothL1LossLayer, so it seems that you only can use GPU mode.

Mypathissional · 2018-08-20T16:22:57Z

How many seconds on average needed for CPU-run only on a single image,say of size (224,224) ?

LP308210365 · 2019-04-19T08:09:09Z

C:\Users\lenovo\Anaconda3\python.exe D:/tf-faster-rcnn-master/lib/setup.py
usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...]
or: setup.py --help [cmd1 cmd2 ...]
or: setup.py --help-commands
or: setup.py cmd --help

error: no commands supplied

I modified setup.py file ,but reported a new error

muhammad-hassan-shakeel · 2019-11-02T08:37:18Z

after above changes I'm getting this:

python setup.py build_ext --inplace
Traceback (most recent call last):
File "setup.py", line 12, in
from Cython.Distutils import build_ext
ImportError: No module named Cython.Distutils
Makefile:2: recipe for target 'all' failed
make: *** [all] Error 1

When I executed pip install Cython it says:
Requirement already satisfied: cython in /usr/lib/python3/dist-packages (0.26.1)

eakbas closed this as completed Apr 8, 2016

dbrazey mentioned this issue Jul 8, 2016

c++ CPU mode how to use nms #247

Open

jamiezeminzhang mentioned this issue Jul 25, 2016

make test fails on cpu_only context #264

Open

marifnst mentioned this issue Jul 27, 2016

Many bounding boxes when running demo.py #276

Closed

RudyChin mentioned this issue Sep 20, 2016

Building without GPU fails #337

Open

radhikat mentioned this issue Sep 29, 2016

Installing py-faster-rcnn without CUDA (CPU only) on windows #356

Closed

anusharao55 mentioned this issue Mar 7, 2017

nms.mv missing - Running MNC under CPU mode daijifeng001/MNC#47

Open

grobman mentioned this issue Mar 23, 2017

compiling CPU only version sanghoon/pva-faster-rcnn#68

Open

KojiShiono mentioned this issue Jun 20, 2017

CPU Mode? CharlesShang/TFFRCNN#81

Open

NaxAlpha pushed a commit to NaxAlpha/py-faster-rcnn that referenced this issue Nov 7, 2017

disable GPU compile module

a57dc40

rbgirshick#123 (comment)

ghost mentioned this issue Jan 25, 2018

CPU only? facebookresearch/Detectron#39

Closed

rnsandeep mentioned this issue Oct 5, 2018

OSError: The nvcc binary could not be located in your $PATH. Either add it to your path, or set $CUDAHOME endernewton/tf-faster-rcnn#391

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How to setup with CPU ONLY mode #123

How to setup with CPU ONLY mode #123

eakbas commented Mar 22, 2016

happyharrycn commented Mar 22, 2016

eakbas commented Mar 23, 2016

happyharrycn commented Mar 23, 2016

dumka commented Apr 5, 2016

Mengmengbai commented Jun 14, 2016

shubh-agrawal commented Aug 25, 2016 •

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mcdickenson commented Aug 25, 2016

shubh-agrawal commented Aug 26, 2016 •

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sandeeppalakkal commented Aug 26, 2016

mcdickenson commented Aug 26, 2016

shubh-agrawal commented Aug 26, 2016

divamgupta commented Sep 27, 2016

mcdickenson commented Sep 27, 2016

shubh-agrawal commented Sep 27, 2016

divamgupta commented Sep 28, 2016

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mcdickenson commented Feb 22, 2017 via email

Anhaoxu commented Mar 5, 2017 •

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GongXinyuu commented Mar 22, 2017 •

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Anhaoxu commented Mar 22, 2017

GongXinyuu commented Mar 26, 2017

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PapaMadeleine2022 commented Nov 22, 2017 •

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Mypathissional commented Aug 20, 2018

LP308210365 commented Apr 19, 2019

muhammad-hassan-shakeel commented Nov 2, 2019

How to setup with CPU ONLY mode #123

How to setup with CPU ONLY mode #123

Comments

eakbas commented Mar 22, 2016

happyharrycn commented Mar 22, 2016

eakbas commented Mar 23, 2016

happyharrycn commented Mar 23, 2016

dumka commented Apr 5, 2016

Mengmengbai commented Jun 14, 2016

['nms/nms_kernel.cu', 'nms/gpu_nms.pyx'],

library_dirs=[CUDA['lib64']],

libraries=['cudart'],

language='c++',

runtime_library_dirs=[CUDA['lib64']],

# this syntax is specific to this build system

# we're only going to use certain compiler args with nvcc and not with

# gcc the implementation of this trick is in customize_compiler() below

extra_compile_args={'gcc': ["-Wno-unused-function"],

'nvcc': ['-arch=sm_35',

'--ptxas-options=-v',

'-c',

'--compiler-options',

"'-fPIC'"]},

include_dirs = [numpy_include, CUDA['include']]

)

shubh-agrawal commented Aug 25, 2016 • edited Loading

mcdickenson commented Aug 25, 2016

shubh-agrawal commented Aug 26, 2016 • edited Loading

sandeeppalakkal commented Aug 26, 2016

mcdickenson commented Aug 26, 2016

shubh-agrawal commented Aug 26, 2016

divamgupta commented Sep 27, 2016

mcdickenson commented Sep 27, 2016

shubh-agrawal commented Sep 27, 2016

divamgupta commented Sep 28, 2016

brisker commented Oct 2, 2016 • edited Loading

mcdickenson commented Feb 22, 2017 via email

Anhaoxu commented Mar 5, 2017 • edited Loading

GongXinyuu commented Mar 22, 2017 • edited Loading

Hey guys, I found this solution works. Comment these code in lib/setup.py #CUDA = locate_cuda()

#self.set_executable('compiler_so', CUDA['nvcc'])

`

Anhaoxu commented Mar 22, 2017

GongXinyuu commented Mar 26, 2017

danielaRiesgo commented Sep 26, 2017 • edited Loading

PapaMadeleine2022 commented Nov 22, 2017 • edited Loading

Mypathissional commented Aug 20, 2018

LP308210365 commented Apr 19, 2019

muhammad-hassan-shakeel commented Nov 2, 2019

shubh-agrawal commented Aug 25, 2016 •

edited

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shubh-agrawal commented Aug 26, 2016 •

edited

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brisker commented Oct 2, 2016 •

edited

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Anhaoxu commented Mar 5, 2017 •

edited

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GongXinyuu commented Mar 22, 2017 •

edited

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Hey guys, I found this solution works.
Comment these code in lib/setup.py
`#CUDA = locate_cuda()`

`#self.set_executable('compiler_so', CUDA['nvcc'])`

danielaRiesgo commented Sep 26, 2017 •

edited

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PapaMadeleine2022 commented Nov 22, 2017 •

edited

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