The codes you see in the video are listed below for you to copy/paste (for your convenience)
$>
sudo apt-get install build-essential
$>
sudo apt-get install linux-headers-`uname -r`
**not necessary unless you have GPU installed and want to use CUDA**
$>
curl -O "http://developer.download.nvidia.com/compute/cuda/6_5/rel/installers/cuda_6.5.14_linux_64.run"
$>
chmod +x cuda_6.5.14_linux_64.run
$>
sudo cuda_6.5.14_linux_64.run --kernel-source-path=/usr/src/linux-headers-`uname -r`/
$> echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.bashrc
$> echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/lib' >> ~/.bashrc
$> source ~/.bashrc
$> echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.bashrc
$> echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/lib' >> ~/.bashrc
$> source ~/.bashrc
$>
sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev protobuf-compiler gfortran libjpeg62 libfreeimage-dev libatlas-base-dev git python-dev python-pip libgoogle-glog-dev libbz2-dev libxml2-dev libxslt1-dev libffi-dev libssl-dev libgflags-dev liblmdb-dev
$>
sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev protobuf-compiler gfortran libjpeg62 libfreeimage-dev libatlas-base-dev git python-dev python-pip libgoogle-glog-dev libbz2-dev libxml2-dev libxslt1-dev libffi-dev libssl-dev libgflags-dev liblmdb-dev
$>
git clone https://github.com/BVLC/caffe.git
$>
cd caffe
$>
cat python/requirements.txt | xargs -L 1 sudo pip install
$>
sudo ln -s /usr/include/python2.7/ /usr/local/include/python2.7
$>
sudo ln -s /usr/local/lib/python2.7/dist-packages/numpy/core/include/numpy /usr/local/include/python2.7/numpy
$> cp Makefile.config.example Makefile.config
$> vi Makefile.config
......
......
CPU_ONLY := 1
PYTHON_INCLUDE := /usr/local/include/python2.7 \
/usr/local/include/python2.7/numpy
$> make pycaffe
$> make all
$> make test
$> python scripts/download_model_binary.py models/bvlc_reference_caffenet
$> sh data/ilsvrc12/get_ilsvrc_aux.sh
**
import pandas as pd
parser.add_argument(
...
)
parser.add_argument(
"--print_results",
action='store_true',
help="Write output text to stdout rather than serializing to a file."
)
parser.add_argument(
"--labels_file",
default=os.path.join(pycaffe_dir,"../data/ilsvrc12/synset_words.txt"),
help="Readable label definition file."
)
...
#Classify
start = time.time()
scores = classifier.predict(inputs, not args.center_only).flatten()
print("Done in %.2f s."(time.time() - start))
if args.print_results:
with open(args.labels_file) as f:
labels_df = pd.DataFrame([{'synset_id':l.strip().split(' ')[0], 'name': ' '.join(l.strip().split(' ')[1:]).split(',')[0]} for l in f.readlines()])
labels = labels_df.sort('synset_id')['name'].values
indices =(-scores).argsort()[:5]
predictions = labels[indicies]
meta = [(p, '%.5f % scores[i]) for i,p in zip(indices, predictions)]
print meta
**
$> python python/classify.py --print_results examples/images/cat.jpg foo
--error fix codes--
1. fatal error: gflags/gflags.h:No such file or directory
$> wget https://github.com/schuhschuh/gflags/archive/master.zip
$> unsip master.zip
$> cd gflags-master
$> mkdir build && cd build
$> export CXXFLAGS="-fPIC" && cmake .. && make VERBOSE=1
$> make
$> sudo make install
2. ImportError: No module named google.protobuf.internal
$> pip install protobuf
3. ImportError: No module named skimage
$> pip install scikit-image
4. ValueError: Mean shape incompatible with input shape
if ms != self.inputs[in_] :
print(self.inputs[in_])
in_shape = self.inputs[in_][1:]
m_min, m_max = mean.min(), mean.max()
normal_mean = (mean - m_min) / (m_max - m_min)
mean = resize_image(normal_mean.transpose((1,2,0)), in_shape[1:]).transpose((2,0,1)) * (m_max - m_min) + m_min
Credit goes to :
http://yujuwon.tistory.com/entry/DeepLearning-%EC%9A%B0%EB%B6%84%ED%88%AC-1404%EC%97%90-Caffe-%EC%84%A4%EC%B9%98-%ED%95%98%EA%B8%B0
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