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pydata2017's Introduction

Reverse Image Search

This repo is for my presentation at PyData 2017.

It demonstrates how to utilize Keras' pretrained ResNet50 convolutional neural network and scikit-learns K-nearest neighbors for a reverse image search enginer.

There is no requirements.txt file, becuase configuring tensorflow and keras can be finicky.
I ran the code use Keras with Tensorflow and just one nvidia k80 GPU.

Here is a video.

Copyright

Copyright (c) 2018 Leon Yin. All Rights Reserved.

Research Outputs

If you use this method in your research please cite this as:

@booklet{key,
author = {Leon Yin},
title = {Reverse Image Search Using Out-of-the-box Machine Learning Libraries},
howpublished= {Paper presented at PyData 2017, New York NY},
year = {2017}
}

Conversely if this software was helpful you can cite it as:

@software{ReverseImageSearch,
  author = {Leon Yin},
  title = {ReverseImageSearch},
  year = {2017}
  howpublished = {https://github.com/yinleon/pydata2017},
}

Next Steps

I am trying to build a UI for this to be used at Data & Society and journalists.

Conclusion

Thanks for stopping by! Please contact me over social media or elsewhere if you have any questions, concerns, or post an Issue if anything looks funky.

pydata2017's People

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pydata2017's Issues

swig/python detected a memory leak of type 'int64_t *', no destructor found.

Hello there, thank you for this repo.
I am currently trying your script out, but facing difficulties while running it. I am getting a swig/python detected a memory leak of type 'int64_t *', no destructor found., normally this means AFAIK that a certain object type has not been defined and the memory is not being reallocated.

Do you know if this is in your script or in some pip dependency?
Do you have any clue on how to solve this?

Error

$ python fit_knn_on_imgs.py
Using TensorFlow backend.
C:\Users\oss-dev\AppData\Local\conda\conda\envs\py36\lib\site-packages\keras_applications\resnet50.py:263: UserWarning: The output shape of `ResNet50(include_top=False)` has been changed since Keras 2.2.0.
  warnings.warn('The output shape of `ResNet50(include_top=False)` '
0
swig/python detected a memory leak of type 'int64_t *', no destructor found.

Installed Packages and their versions

$ conda list
# packages in environment at C:\Users\oss-dev\AppData\Local\conda\conda\envs\py36:
#
absl-py                   0.6.1                 py36_1000    conda-forge
annoy                     1.15.0                    <pip>
astor                     0.7.1                      py_0    conda-forge
astroid                   1.5.3                    py36_0
backports                 1.0                        py_2    conda-forge
backports.weakref         1.0rc1                   py36_1    conda-forge
beautifulsoup4            4.6.1                     <pip>
blas                      1.0                         mkl
bleach                    1.5.0                    py36_0    conda-forge
ca-certificates           2018.11.29           ha4d7672_0    conda-forge
certifi                   2016.2.28                py36_0
colorama                  0.3.9                     <pip>
gast                      0.2.0                      py_0    conda-forge
grpcio                    1.16.0          py36hbb4b082_1000    conda-forge
h5py                      2.9.0                     <pip>
h5py                      2.9.0           py36hf098a70_1000    conda-forge
hdf5                      1.10.4          nompi_hcc15c50_1105    conda-forge
html5lib                  0.9999999                py36_0    conda-forge
init                      0.1.0                     <pip>
isort                     4.2.15                   py36_0
keras                     2.2.4                    py36_0    conda-forge
Keras                     2.2.4                     <pip>
Keras-Applications        1.0.6                     <pip>
keras-applications        1.0.4                      py_1    conda-forge
keras-preprocessing       1.0.2                      py_1    conda-forge
Keras-Preprocessing       1.0.5                     <pip>
lazy-object-proxy         1.3.1                    py36_0
libflang                  5.0.0           h6538335_20180525    conda-forge
libgpuarray               0.7.6             hfa6e2cd_1003    conda-forge
libprotobuf               3.6.1             h1a1b453_1000    conda-forge
llvm-meta                 5.0.0                         0    conda-forge
m2w64-gcc-libgfortran     5.3.0                         6
m2w64-gcc-libs            5.3.0                         7
m2w64-gcc-libs-core       5.3.0                         7
m2w64-gmp                 6.1.0                         2
m2w64-libwinpthread-git   5.0.0.4634.697f757               2
mako                      1.0.7                      py_1    conda-forge
markdown                  2.6.11                     py_0    conda-forge
markupsafe                1.1.0           py36hfa6e2cd_1000    conda-forge
mkl                       2017.0.3                      0
mock                      2.0.0                 py36_1000    conda-forge
msys2-conda-epoch         20160418                      1
nltk                      3.4                       <pip>
numpy                     1.13.1                   py36_0
openblas                  0.3.3             h535eed3_1001    conda-forge
openmp                    5.0.0                    vc14_1  [vc14]  conda-forge
openssl                   1.0.2p            hfa6e2cd_1001    conda-forge
panda                     0.3.1                     <pip>
pandas                    0.23.4                    <pip>
pbr                       4.2.0                      py_0    conda-forge
Pillow                    5.3.0                     <pip>
pip                       9.0.1                    py36_1
pip                       18.1                      <pip>
pipenv                    2018.7.1                  <pip>
protobuf                  3.6.1           py36he025d50_1001    conda-forge
psutil                    5.4.8                     <pip>
pygpu                     0.7.6           py36h452e1ab_1000    conda-forge
pylint                    1.7.2                    py36_0
pyreadline                2.1                   py36_1000    conda-forge
python                    3.6.2                         0
python-dateutil           2.7.5                     <pip>
pytz                      2018.7                    <pip>
pyyaml                    3.13            py36hfa6e2cd_1001    conda-forge
PyYAML                    3.13                      <pip>
requests                  2.14.2                   py36_0
scikit-learn              0.20.2                    <pip>
scipy                     0.19.1              np113py36_0
scipy                     1.2.0                     <pip>
setuptools                36.4.0                   py36_1
singledispatch            3.4.0.3                  py36_0
singledispatch            3.4.0.3                   <pip>
six                       1.12.0                py36_1000    conda-forge
sklearn                   0.0                       <pip>
tensorboard               1.10.0                   py36_0    conda-forge
tensorflow                1.3.0                    py36_0    conda-forge
termcolor                 1.1.0                      py_2    conda-forge
terminal                  0.4.0                     <pip>
theano                    1.0.3           py36h6538335_1001    conda-forge
vc                        14                            0
virtualenv                16.0.0                    <pip>
virtualenv-clone          0.3.0                     <pip>
vs2015_runtime            14.0.25420                    0
vs2015_win-64             14.0.25123           h17c34da_3    conda-forge
webencodings              0.5.1                      py_1    conda-forge
werkzeug                  0.14.1                     py_0    conda-forge
wheel                     0.29.0                   py36_0
wincertstore              0.2                      py36_0
wrapt                     1.10.11                  py36_0
yaml                      0.1.7             hfa6e2cd_1001    conda-forge
zlib                      1.2.11            h2fa13f4_1003    conda-forge

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