Software Alternatives & Reviews

Amazon Rekognition VS Machine Box

Compare Amazon Rekognition VS Machine Box and see what are their differences

Amazon Rekognition logo Amazon Rekognition

Add Amazon's advanced image analysis to your applications.

Machine Box logo Machine Box

Run, deploy & scale state of the art machine learning tech
  • Amazon Rekognition Landing page
    Landing page //
    2023-04-18
  • Machine Box Landing page
    Landing page //
    2019-12-21

Amazon Rekognition videos

AWS Rekognition Tutorial | Image Recognition using AWS | Amazon Rekognition | AWS Training | Edureka

More videos:

  • Review - Extract Data from Images and Videos with Amazon Rekognition (Level 300)
  • Demo - Can Amazon's Facial Recognition identify my 15 years younger picture? | Amazon Rekognition Demo

Machine Box videos

No Machine Box videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Amazon Rekognition and Machine Box)
Image Analysis
100 100%
0% 0
AI
68 68%
32% 32
Machine Learning
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon Rekognition and Machine Box

Amazon Rekognition Reviews

2019 Examples to Compare OCR Services: Amazon Textract/Rekognition vs Google Vision vs Microsoft Cognitive Services
Pricing: Amazon Rekognition, Amazon Textract, Google, Microsoft. We don't really care which one you use, but Microsoft did best by our sample data. Textract was a very close second if you only need its headline feature: extracting text from digital documents. If someone wants to email bill -at- amplenote.com with comparable data for other images/services, I can try to...

Machine Box Reviews

We have no reviews of Machine Box yet.
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Social recommendations and mentions

Based on our record, Amazon Rekognition should be more popular than Machine Box. It has been mentiond 33 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Rekognition mentions (33)

  • Afraid of outgrowing AWS Rekognition? Try YOLO in Lambda.
    AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 1 month ago
  • Amazon Rekognition Custom Labels for Bears
    I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 9 months ago
  • “During a gold rush, sell shovels.” What are the shovels in the AI rush?
    For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago
  • Serverless Facial Recognition Voting Application Using AWS Services
    Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / 12 months ago
  • Amazon Prime Video playback features
    Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
View more

Machine Box mentions (5)

  • [P] 🗣️ Speechbox - A new library to *unnormalize* your speech.
    Reminds me of Machine Box (http://machinebox.io). Source: over 1 year ago
  • Wrapper for Dog CEO API
    Thank you :) I did that to teach dog’s breed to an AI. If you don’t know machine box yet : Https://machinebox.io It seems really cool and easy to use. Source: almost 2 years ago
  • Time to build my Lab
    I think you should go 5 Pi X 5 Jetson Nano’s I haven’t seen many people offloading the Nano’s GPU functionality for ML similar to this Serverless style of product. https://machinebox.io/. Source: over 2 years ago
  • [P] Facial Recognition with AWS Rekognition or Azure Vision
    For face recognition - CompreFace. Disclaimer - I created it, as an alternative you can use MachineBox, but it's not open source and has limits. Also, I think, you will use some software to control the system, e.g. Frigate or Home Assistant, I think this repository can be useful for you. Source: over 2 years ago
  • Database for Face Recognition
    If you have a really simple application, you can just save the encodings into the files. If not - it's better to use a database. SQL is ok. But for the best results, I would suggest using milvus.io, as it was created for saving vectors and finding the distances (I haven't tried it, though). If your final goal is not to learn face recognition basics, you can just use free ready to use solutions like CompreFace... Source: over 2 years ago

What are some alternatives?

When comparing Amazon Rekognition and Machine Box, you can also consider the following products

Clarifai - The World's AI

Amazon Machine Learning - Machine learning made easy for developers of any skill level

Google Vision AI - Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.

Model Zoo - Deploy your machine learning model in a single line of code.

OpenCV - OpenCV is the world's biggest computer vision library

MorphL - Applied AI/ML for eCommerce