Metadata-Version: 2.2
Name: imagededup-gml
Version: 0.3.2
Summary: Package for image deduplication
Author: Tanuj Jain, Christopher Lennan, Zubin John, Dat Tran
Author-email: tanuj.jain.10@gmail.com, christopherlennan@gmail.com, zrjohn@yahoo.com, datitran@gmail.com
Maintainer-email: build@gimletlabs.ai
License: Apache 2.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: Pillow>=9.0
Requires-Dist: tqdm
Requires-Dist: scikit-learn
Requires-Dist: PyWavelets
Requires-Dist: matplotlib
Provides-Extra: tests
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Requires-Dist: codecov; extra == "tests"
Provides-Extra: docs
Requires-Dist: mkdocs; extra == "docs"
Requires-Dist: mkdocs-material; extra == "docs"
Provides-Extra: dev
Requires-Dist: bumpversion; extra == "dev"
Requires-Dist: twine; extra == "dev"
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: license
Dynamic: maintainer-email
Dynamic: provides-extra
Dynamic: requires-dist
Dynamic: summary


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 3.8+ and runs on Linux, MacOS X and Windows. 
It is distributed under the Apache 2.0 license.
