imagededup

Package for image deduplication

Project description

imagededup is a python package that provides functionality to find duplicates in a collection of images using a variety of algorithms. Additionally, an evaluation and experimentation framework, is also provided. Following details the functionality provided by the package:

Finding duplicates in a directory using one of the following algorithms:
- Convolutional Neural Network
- Perceptual hashing
- Difference hashing
- Wavelet hashing
- Average hashing
Generation of features for images using one of the above stated algorithms.
Framework to evaluate effectiveness of deduplication given a ground truth mapping.
Plotting duplicates found for a given image file.

Read the documentation at: https://idealo.github.io/imagededup/

imagededup is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows. It is distributed under the Apache 2.0 license.

Project details

Release history Release notifications | RSS feed

This version

0.2.2

Dec 11, 2019

0.2.1

Nov 3, 2019

0.2.0

Oct 30, 2019

0.1.0

Oct 4, 2019

0.0.4

Oct 2, 2019

0.0.3

Sep 30, 2019

0.0.2

Sep 26, 2019

0.0.1

Sep 26, 2019

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

imagededup-0.2.2.tar.gz (60.6 kB view hashes)

Uploaded Dec 11, 2019 source

Built Distributions

imagededup-0.2.2-cp37-cp37m-win_amd64.whl (50.7 kB view hashes)

Uploaded Dec 11, 2019 cp37

imagededup-0.2.2-cp37-cp37m-manylinux1_x86_64.whl (42.6 kB view hashes)

Uploaded Dec 11, 2019 cp37

imagededup-0.2.2-cp37-cp37m-macosx_10_6_intel.whl (61.3 kB view hashes)

Uploaded Dec 11, 2019 cp37

imagededup-0.2.2-cp36-cp36m-win_amd64.whl (50.6 kB view hashes)

Uploaded Dec 11, 2019 cp36

imagededup-0.2.2-cp36-cp36m-manylinux1_x86_64.whl (42.6 kB view hashes)

Uploaded Dec 11, 2019 cp36

imagededup-0.2.2-cp36-cp36m-macosx_10_6_intel.whl (61.2 kB view hashes)

Uploaded Dec 11, 2019 cp36

Hashes for imagededup-0.2.2.tar.gz

Hashes for imagededup-0.2.2.tar.gz
Algorithm	Hash digest
SHA256	`55725df6151404ae7d7a245dc59a2c2edabce234b7a026199017a7a019e7f6d1`
MD5	`4ed81526292d222d9e218f5267dac06e`
BLAKE2-256	`d8dd0cbe53897fca40fef44a9b9db9cf753bca369870affa31788cc5b617dcfb`

Hashes for imagededup-0.2.2-cp37-cp37m-win_amd64.whl

Hashes for imagededup-0.2.2-cp37-cp37m-win_amd64.whl
Algorithm	Hash digest
SHA256	`7ac7cb278c091a2dc9dac7d43472872f5255cdf00399af4ac3fb5682de418a66`
MD5	`3502f591262b120ab74dd82a07732452`
BLAKE2-256	`dbe016cb1695d541b6aa85f5753b0065a88f5c04238f518d72548dee603d1e7c`

Hashes for imagededup-0.2.2-cp37-cp37m-manylinux1_x86_64.whl

Hashes for imagededup-0.2.2-cp37-cp37m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`7a5da217552ab14954c7804cace2007106fc20daee1f7dc3c06fc9db13818009`
MD5	`ffad2a2264af4f2d32b881d54532c53c`
BLAKE2-256	`06af013a2e6953d2a745481d21d4db9ec7f9b574d1da9379a8583bcfa6df311a`

Hashes for imagededup-0.2.2-cp37-cp37m-macosx_10_6_intel.whl

Hashes for imagededup-0.2.2-cp37-cp37m-macosx_10_6_intel.whl
Algorithm	Hash digest
SHA256	`62bd38acf1c5920ee3d3dda1257ef7d372ee9e22519b42a7acb5d046a4685150`
MD5	`5610cb588e7d8b9b1678d84e4e007173`
BLAKE2-256	`4894ebcce1b065084acdcca91f4c47e1ab29e9c950bf138b38f429644cc919da`

Hashes for imagededup-0.2.2-cp36-cp36m-win_amd64.whl

Hashes for imagededup-0.2.2-cp36-cp36m-win_amd64.whl
Algorithm	Hash digest
SHA256	`51d70ad2898bdf58d3eef7189d25f27ce0459d80cc5275da5991cbe7ae557355`
MD5	`8c5e1695bfee5a4e1ec17e8f8a7d6645`
BLAKE2-256	`5876a66ab3815d259abd5491d71ffa5e01e7280e46a7ff8ecce4bbfdfd05d0ff`

Hashes for imagededup-0.2.2-cp36-cp36m-manylinux1_x86_64.whl

Hashes for imagededup-0.2.2-cp36-cp36m-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`90f37743b32886afc76bef69af704e8eb5151a8141c86fd870fb5bdd15cdf76e`
MD5	`85335edf8be9787e22bf946b9f557bdd`
BLAKE2-256	`5b9878ca693e13aa58d77365dd78f10e84f0561eb8fbfcff689fa52995edefaf`

Hashes for imagededup-0.2.2-cp36-cp36m-macosx_10_6_intel.whl

Hashes for imagededup-0.2.2-cp36-cp36m-macosx_10_6_intel.whl
Algorithm	Hash digest
SHA256	`a35e644224736b4b20c04ab6c0a49162fdb358335347de98b4c87ff47be6516c`
MD5	`e672c872ddabc71b2ac0f0b7140e435e`
BLAKE2-256	`2cec5232d4a0e0a72e548ba03f75e3bc36467c2eda3f9b7b1d6d77f9c3f197d9`