facial-recognition VS The-Machine

Compare facial-recognition vs The-Machine and see what are their differences.

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facial-recognition The-Machine
1 2
37 89
- -
0.0 2.3
over 1 year ago about 1 year ago
Python Python
MIT License -
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.

facial-recognition

Posts with mentions or reviews of facial-recognition. We have used some of these posts to build our list of alternatives and similar projects.

The-Machine

Posts with mentions or reviews of The-Machine. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-22.

What are some alternatives?

When comparing facial-recognition and The-Machine you can also consider the following projects:

DeepStack - The World's Leading Cross Platform AI Engine for Edge Devices

EyeDraw - Small computer vision software that allows you to draw with your own eyes

deepface - A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

stitching - A Python package for fast and robust Image Stitching

retinaface - RetinaFace: Deep Face Detection Library for Python

stitching - A Python package for fast and robust Image Stitching [Moved to: https://github.com/OpenStitching/stitching]

blurfaces - blurs faces in video

The_Machine_Rebooted

facenet-pytorch - Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models

apex-analysis-tool

Face Recognition - The world's simplest facial recognition api for Python and the command line

Ai_Demos_RPi - Example code for using different Raspberry Pi boards with various electronic and mechanical components.