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분류 전체보기에 해당되는 글 183건
- 2015.02.27 k-means clustering
- 2015.02.27 딥러닝 Deep Learning
- 2015.02.10 이미지 비율 유지 크기 조절
- 2015.02.06 python pytables error
- 2015.01.24 ImportError: No module named selective_search_ijcv_with_python
- 2015.01.09 ubuntu pyexiv2 install
- 2015.01.06 fatal error: numpy/arrayobject.h
- 2015.01.06 HDF5
- 2015.01.06 anaconda make error /usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to `__exp_finite@GLIBC_2.15'
- 2015.01.03 vmware 키젠
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k-means clustering
'패턴인식 & 기계학습' 카테고리의 다른 글
딥러닝 framework Theano 설치 (0) | 2015.09.21 |
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에이다부스트(adaboost) (0) | 2015.02.27 |
딥러닝 Deep Learning (0) | 2015.02.27 |
SVM(Support Vector Machine) (0) | 2014.11.04 |
Heap theory(헵 이론) (0) | 2014.11.04 |
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딥러닝 Deep Learning
'패턴인식 & 기계학습' 카테고리의 다른 글
에이다부스트(adaboost) (0) | 2015.02.27 |
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k-means clustering (0) | 2015.02.27 |
SVM(Support Vector Machine) (0) | 2014.11.04 |
Heap theory(헵 이론) (0) | 2014.11.04 |
신경망 이론 (0) | 2014.11.04 |
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이미지 비율 유지 크기 조절
Width 고정
Height 고정
'컴퓨터비전/영상처리' 카테고리의 다른 글
해리스 코너(Harris Corner) (2) | 2015.04.03 |
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직선 검출 허프 변환 (0) | 2015.04.03 |
Tracking Learning and Detection(TLD) (0) | 2014.10.30 |
random tree(임의 숲) (0) | 2014.10.25 |
영상처리 색공간 변환 (0) | 2014.10.20 |
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python pytables error
1. easy_install tables 설치
2. 설치시
- Python >= 2.6 including Python 3.x
- HDF5 >= 1.8.4 (>=1.8.7 is strongly recommended),
- NumPy >= 1.4.1,
- Numexpr >= 2.0 and
- Cython >= 0.13
- argparse (only Python 2.6, it is used by the pt2to3 utility)
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ImportError: No module named selective_search_ijcv_with_python
ImportError: No module named selective_search_ijcv_with_python
1. https://github.com/sergeyk/selective_search_ijcv_with_python에서 다운로드
2. 실행 모듈 폴더 안에 압축 해제
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ubuntu pyexiv2 install
. virtualenv/bin/activatesudo apt-get install scons libexiv2-dev libboost-dev libboost-python-devmkdir buildcd buildwget http://launchpad.net/pyexiv2/0.3.x/0.3.2/+download/pyexiv2-0.3.2.tar.bz2 -O-| tar -xpvjcd pyexiv2*sconsscons install$ nano ~/.bashrc
add two lines
export PYTHONPATH=${HOME}/pyexiv2:$PYTHONPATH
export PYTHONPATH=${HOME}/pyexiv2/src:$PYTHONPATH
pyexiv2/build/libexiv2python.so file move to pyexiv2 folder(PYTHONPATH)
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fatal error: numpy/arrayobject.h
python/caffe/_caffe.hpp:8:31: fatal error: numpy/arrayobject.h: 그런 파일이나 디렉터리가 없습니다
#include <numpy/arrayobject.h>
$ sudo apt-get install python-numpy
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HDF5
HDF5
Amuse can work with HDF5 versions 1.6.* and 1.8.3. Ubuntu 9.04 comes with HDF5 version 1.6.6. To install it, do:
https://github.com/BVLC/caffe/issues/1463
I had this same problem. I found that libhdf5-dev created the files
/usr/lib/x86_64-linux-gnu/libhdf5_hl.so.7
/usr/lib/x86_64-linux-gnu/libhdf5.so.7
After copying them to the new names
/usr/lib/x86_64-linux-gnu/libhdf5_hl.so.8
/usr/lib/x86_64-linux-gnu/libhdf5.so.8
make runtest
worked fine. I'm a Linux neophyte though so couldn't tell you why it was looking for the .8 files rather than the .7 files (or why my version of libhdf5-dev installed the .7 files rather than the .8 ones)
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anaconda make error /usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to `__exp_finite@GLIBC_2.15'
I get following errors while trying to build on Ubuntu 14.04:
g++ tools/extract_features.cpp -pthread -fPIC -DNDEBUG -O2 -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 -Wall -Wno-sign-compare -c -o .build_release/tools/extract_features.o 2> .build_release/tools/extract_features.o.warnings.txt \
|| (cat .build_release/tools/extract_features.o.warnings.txt; exit 1)
g++ .build_release/tools/extract_features.o .build_release/lib/libcaffe.a -o .build_release/tools/extract_features.bin -fPIC -DNDEBUG -O2 -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 -Wall -Wno-sign-compare -L/home/mender/anaconda/lib -L/usr/local/lib -L/usr/lib -L/usr/local/cuda/lib64 -L/usr/local/cuda/lib -lcudart -lcublas -lcurand -lglog -lgflags -lpthread -lprotobuf -lleveldb -lsnappy -llmdb -lboost_system -lhdf5_hl -lhdf5 -lopencv_core -lopencv_highgui -lopencv_imgproc -lcblas -latlas
//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to __exp_finite@GLIBC_2.15'//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to
__log10_finite@GLIBC_2.15'
//usr/lib/x86_64-linux-gnu/libxvidcore.so.4: undefined reference to __logf_finite@GLIBC_2.15'//usr/lib/x86_64-linux-gnu/libvorbis.so.0: undefined reference to
__acosf_finite@GLIBC_2.15'
//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to __pow_finite@GLIBC_2.15'//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to
__log2_finite@GLIBC_2.15'
//usr/lib/x86_64-linux-gnu/libxvidcore.so.4: undefined reference to __log10f_finite@GLIBC_2.15'//usr/lib/x86_64-linux-gnu/libxvidcore.so.4: undefined reference to
__log_finite@GLIBC_2.15'
//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to __powf_finite@GLIBC_2.15'//usr/lib/x86_64-linux-gnu/libx264.so.142: undefined reference to
__log2f_finite@GLIBC_2.15'
collect2: ld returned 1 exit status
make: *** [.build_release/tools/extract_features.bin] Error 1
My Makefile.config setting likes this:
CUDA_DIR := /usr/local/cuda
CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
-gencode arch=compute_20,code=sm_21 \
-gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=sm_50 \
-gencode arch=compute_50,code=compute_50
BLAS := atlas
MATLAB_DIR := /usr/local/MATLAB/R2012b
PYTHON_INCLUDE := $(HOME)/anaconda/include \
$(HOME)/anaconda/include/python2.7 \
$(HOME)/anaconda/lib/python2.7/site-packages/numpy/core/include
PYTHON_LIB := $(HOME)/anaconda/lib
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
TEST_GPUID := 0
g++ --version
g++ (Ubuntu/Linaro 4.6.4-6ubuntu2) 4.6.4
echo $LD_LIBRARY_PATH
/home/anaconda/lib:/usr/local/cuda-6.0/lib64:/usr/local/lib:/usr/lib:
This problem seems like #757, but I don't know how to get ride of the error. Where things go wrong?
Thanks.
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Ask installation questions on the caffe-users mailing list please!
Some versions of Anaconda seem to come with a bad libm. rm ~/anaconda/lib/libm.*
takes care of this by reverting to the system libm.