Analyzes regarding Duplicate Reimbursements #286
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…-amor # Conflicts: # conda_requirements.txt # research/Dockerfile # research/requirements.txt
# Including pdf > png # png > sift descriptors # png > keras classifier
PDF to PNG ok PNG to SIFT (error in opencv)
Change the workflow for png references
Download files OK Split Files ok Testing trianing ...
…-amor # Conflicts: # research/Dockerfile
# Building Reference Dataset ok # Building Keras model and evaluation OK # PDF-> PNG OK
# Using dhash to detect near duplications.
silviodc
changed the title
# Inclusion of Fourier transformation to detect rotation, zoom, and filters.
silviodc
changed the title
|
Hi @silviodc, thanks for the contribuition! What I did to test this PR:
$ git clone git@github.com:datasciencebr/serenata-de-amor.git
$ cd serenata-de-amor
$ git checkout -b silviodc-silvio-cardoso master
$ git pull https://github.com/silviodc/serenata-de-amor.git silvio-cardoso
$ conda update conda
$ conda create --name serenata_de_amor python=3
$ source activate serenata_de_amor
$ ./setup
$ jupyter notebook
I really liked your work on it, looks real impressive! There is only one thing that I'll ask you, and then for me we can merge it! |
anaschwendler
requested changes
Oct 11, 2017
research/requirements.txt
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| tensorflow>=1.2.1 | ||
| h5py>=2.7.0 | ||
| Pillow>=4.2.1 | ||
| opencv-python |
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Can you add the version of the libraries that you are using? It helps in case they change something that make it not working ;)
No. I guess i finished with these analyses. |
anaschwendler
approved these changes
Oct 11, 2017
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Detecting duplicate Reimbursements using dhash.
The last commit has the notebook to detect duplicate Reimbursements. It uses hash and hamming distance.
The other files concerns future implementation as: CFMT block (Compact Fourier Mellin Transform) to be more precise during the detection.
It is related to issue: #32