Metadata-Version: 2.1
Name: kakaimagededup
Version: 0.3.4
Summary: Package for image deduplication, kaka version
Author: chessy247
Author-email: chessywang247@gmail.com
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: dev
Requires-Dist: bumpversion ; extra == 'dev'
Requires-Dist: twine ; extra == 'dev'
Provides-Extra: docs
Requires-Dist: mkdocs ; extra == 'docs'
Requires-Dist: mkdocs-material ; extra == 'docs'
Provides-Extra: tests
Requires-Dist: pytest ; extra == 'tests'
Requires-Dist: pytest-cov ; extra == 'tests'
Requires-Dist: pytest-mock ; extra == 'tests'
Requires-Dist: codecov ; extra == 'tests'


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.
