imagededup VS DeepCreamPy

Compare imagededup vs DeepCreamPy and see what are their differences.

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imagededup DeepCreamPy
7 19
4,951 10,828
1.2% -
1.5 0.4
4 days ago about 3 years ago
Python Python
Apache License 2.0 GNU Affero General Public License v3.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

imagededup

Posts with mentions or reviews of imagededup. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-22.

DeepCreamPy

Posts with mentions or reviews of DeepCreamPy. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-03-19.

What are some alternatives?

When comparing imagededup and DeepCreamPy you can also consider the following projects:

image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

hent-AI - Automation of censor bar detection

floc-simhash - A fast python implementation of the SimHash algorithm.

image-quality-assessment - Convolutional Neural Networks to predict the aesthetic and technical quality of images.

Enma - Enma is a Python library designed to fetch and download manga and doujinshi data from many sources including Manganato and NHentai.

alipay - An Unofficial Alipay API for Python

Spectrum - Spectrum is an AI that uses machine learning to generate Rap song lyrics

Duplicate-Image-Finder - difPy - Python package for finding duplicate or similar images within folders

kurby - A modern CLI to download animes automatically from Twist

TensorPipe - High Performance Tensorflow Data Pipeline with State of Art Augmentations and low level optimizations.

co-mod-gan - [ICLR 2021, Spotlight] Large Scale Image Completion via Co-Modulated Generative Adversarial Networks