Today’s my first test on Bundler http://phototour.cs.washington.edu/
I didn’t use the source cause there are many packages needed to be set up first, so I follow the recommendation using the binary package (bundler-v0.3-binary.zip).
There are some error I encountered cause I carelessly NOT copying the libANN_char.so into the the required path. Well this can be easily fixed by changing/adding the dir-path of libANN_char.so to your LD_LIBRARY_PATH. In my case, the LD_LIBRARY_PATH is empty, so I simply create this env-variable.
This should be the directory path to the libANN_char.so, otherwise you will get error that ‘error while loading shared libraries: libANN_char.so: cannot open shared object file: No such file or directory’.
So read carefully for the ‘Before you begin’ section. Also, if you are trying older version, e.g. v0.2, you will need to change the BASE_PATH for multiple files, such as the sift.txt. Just check if there is BASE_PATH for your ‘TO-DO’.
Find my gtk version on ubuntu
$ dpkg -s libgtk2.0-0|grep ‘^Version’
# [Vision] Depth estimation from Blur estimation
#Camera Calibration Toolbox for Matlab
Install OpenSceneGraph on Windows: http://dwightdesign.com/2009/05/installing-openscenegraph-280/
Install on Ubuntu:
apt-get build-dep openscenegraph
apt-get install openscenegraph
First few things to check out for openCV:
Just update Ubuntu to 11.10. I was afraid that Unity desk cause I don’t like it very much. It’s so hard to find things and get installed software organized. Thanks God, you can choose whether to use the unity desktop or the classic version. Just click the ‘gear’ button when you login into your account, change the default ‘unity’ back to classic version. Then you are all set.
I use the classic desktop for 11.04, and back that time I did install the some gnome related package. If you can’t find the ‘gear’ option. Try this:
Some useful links for AWS:
- Simple Monthly Calculator: provides the estimate of the actual cost
- Faqs : very comprehensive, where you can find information for managing clusters, and using hive
- Hadoop cluster configuration
- All other configuration: Hive, Performance tuning
- Use Bootstrap Actions to do the configuration
- All jobs should be mapper+reducer, no mapper only jobs in AWS, so use a ‘pass-through’ as your reducer
The cache-file option provides a good way for using AWS Elastic MapReduce when you have extra data (rather than input data — where input data will be processed via stdin to mapper) , such as parameter file or other kind of information. Also using GZipped input in the extra arguments to let Hadoop decompress data on the fly before passing data to mapper: -jobconf stream.recordreader.compression=gzip . Here’s an example of how to specify the cache-file in boto:
mapper = 's3://<your-code-bucket>/mapper.py' reducer = 's3://<your-code-bucket>/reducer.py' input_mr = 's3://<your-input-data-bucket>' output_mr = 's3://<your-output-bucket>' + job_name step_args = ['-jobconf', 'mapred.reduce.tasks=1', '-jobconf', 'mapred.map.tasks=2', '-jobconf', 'stream.recordreader.compression=gzip'] cache_files=['s3://<your-cache-file-bucket>/randomForest-model-1.txt#rf1.txt', s3://<your-cache-file-bucket>/randomForest-model-1.txt#rf2.txt'] step = StreamingStep(name = "my-step", mapper = mapper, reducer = reducer, input = input_mr, output = output_mr, step_args = step_args, cache_files= cache_files)
Some limitations of AWS:It was dated Jan, 2011, not test it for the current system. But I guess I have to pay attention to or test it a little bit.
1. Not good for input data > 5GB
2. Not running more than 20 instances.
boostrap is really a noisy thing for me, since it’s hard to predict the output. Here’s the code for installing R(randomForest), Python(simple json).
# turn on logging and exit on error
set -e -x
sudo apt-get install python-setuptools
sudo easy_install simplejson
#debian R upgrade The R version used by Amazon is really old. The solution is to update it with the following script
echo "deb http://streaming.stat.iastate.edu/CRAN/bin/linux/debian lenny-cran/" | sudo tee -a /etc/apt/sources.list
sudo apt-get update
sudo apt-get -t lenny-cran install –yes –force-yes r-base r-base-dev
echo "install.packages(‘randomForest’,repos=’http://cran.r-project.org‘)" | sudo R –no-save
PAKDD workshop on “Multi-view data, High-dimensionality, External Knowledge: Striving for a Unified Approach to Clustering”
Figure 1 – Concept map of major research themes in advanced data clustering