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when I use "make all -j8", occur this errors #4

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zhengchuansh opened this issue Apr 12, 2016 · 9 comments
Closed

when I use "make all -j8", occur this errors #4

zhengchuansh opened this issue Apr 12, 2016 · 9 comments

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@zhengchuansh
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I has install caffe, and successfully run examples .
erros:
head lines:
make: /usr/local/MATLAB/R2012a/bin/mexext: Command not found
g++ src/caffe/net.cpp -pthread -fPIC -DNDEBUG -O2 -DUSE_MKL -I/usr/include/python2.7 -I/usr/lib/python2.7/dist-packages/numpy/core/include -I/usr/local/include -I.build_release/src -I./src -I./include -I/usr/local/cuda/include -I/opt/intel/mkl/include -Wall -Wno-sign-compare -c -o .build_release/src/caffe/net.o 2> .build_release/src/caffe/net.o.warnings.txt
|| (cat .build_release/src/caffe/net.o.warnings.txt; exit 1)

the last few lines:
compilation terminated.
make: *** [.build_release/src/caffe/blob.o] Error 1
In file included from ./include/caffe/util/math_functions.hpp:11:0,
from ./include/caffe/syncedmem.hpp:7,
from ./include/caffe/blob.hpp:6,
from ./include/caffe/layer.hpp:8,
from src/caffe/layers/absval_layer.cpp:3:
./include/caffe/util/mkl_alternate.hpp:6:17: fatal error: mkl.h: No such file or directory
#include <mkl.h>
^
compilation terminated.
make: *** [.build_release/src/caffe/layers/absval_layer.o] Error 1

@kevinlin311tw
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Caffe has several dependencies. Check this for more information: http://caffe.berkeleyvision.org/installation.html

@zhengchuansh
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after I install dependencies, then run demo.m, occur this error:

In matcaffe_batch_feat at 35
In demo at 29
Invalid MEX-file
'/home/zcs/caffe/examples/caffe-cvprw15-master/matlab/caffe/caffe.mexa64':
/usr/local/MATLAB/R2012b/bin/glnxa64/../../sys/os/glnxa64/libstdc++.so.6:
version `GLIBCXX_3.4.15' not found (required by
/home/zcs/caffe/examples/caffe-cvprw15-master/matlab/caffe/caffe.mexa64)

Error in matcaffe_init_feat (line 27)
caffe('init', model_def_file, model_file)

Error in matcaffe_batch_feat (line 39)
matcaffe_init_feat(use_gpu, model_def_file, model_file);

Error in demo (line 29)
[feat_test , list_im] = matcaffe_batch_feat(test_file_list,
use_gpu, feat_len, model_def_file, model_file);

but I has GLIBCXX_3.4.15
zcs@zcs-Virtual:~$ strings /usr/lib/libstdc++.so.6 | grep GLIBCXX
GLIBCXX_3.4
GLIBCXX_3.4.1
GLIBCXX_3.4.2
GLIBCXX_3.4.3
GLIBCXX_3.4.4
GLIBCXX_3.4.5
GLIBCXX_3.4.6
GLIBCXX_3.4.7
GLIBCXX_3.4.8
GLIBCXX_3.4.9
GLIBCXX_3.4.10
GLIBCXX_3.4.11
GLIBCXX_3.4.12
GLIBCXX_3.4.13
GLIBCXX_3.4.14
GLIBCXX_3.4.15
GLIBCXX_3.4.16
GLIBCXX_3.4.17
GLIBCXX_DEBUG_MESSAGE_LENGTH

@kevinlin311tw
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LD_LIBRARY_PATH=/usr/lib/libstdc++.so.6
or check this: kyamagu/mexopencv#45

@zhengchuansh
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and I also has use: sudo ln -sf /usr/lib/x86_64-linux-gnu/libstdc++.so.6.0.19 /usr/local/MATLAB/R2011a/bin/glnxa64/libstdc++.so.6, so run successfully.
thank you very much!

@kevinlin311tw
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Hope you are well.
If you got "Warning: Problems with file" when running run_cifar10, make sure you have download the images or check this: #1

@zhengchuansh
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when run demo, I got "Warning: Problems with file" , because we must add "." to img_list.txt. like this "./examples/cvprw15-cifar10/imgs/horse2.jpg" ,then everything will be ok. And I also find if I want to run run_cifar10, I must add path for other functions, such as: path(path,'./matlab/caffe/');

But the result is very strange:
Elapsed time is 0.075924 seconds.
Complete Query [Hamming] 0.08 seconds
query 10000
Warning: Converting non-floating point data to double.

In pdist2 at 219
In precision at 20
In run_cifar10 at 61
Elapsed time is 0.081869 seconds.
Complete Query [Hamming] 0.08 seconds
MAP = 0.105777

MAP should be 0.897373

In analysis folder, binary-train.mat and binary-test.mat, they are all one.
so the result is wrong

@kevinlin311tw
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You didn't get the binary codes. Some suggestions as below:

  1. Launch matlab at caffe's root folder, or run startup.m before testing any function.
  2. Add "." to train_file_list.txt and test_file_list.txt. For example, "./examples/cvprw15-cifar10/dataset/batch1/4590.jpg"

@zhengchuansh
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I first run startup.m, and delete other inaccurate .mat data, then got the right result.
thank you!

@kevinlin311tw
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Great!!

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