face-recognition-service | Face recognition online service , allow | Computer Vision library

by tabvn JavaScript Version: Current License: No License

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kandi X-RAY | face-recognition-service Summary

face-recognition-service is a JavaScript library typically used in Artificial Intelligence, Computer Vision, Tensorflow applications. face-recognition-service has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Face recognition online service, allow user training it.

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face-recognition-service has a low active ecosystem.

It has 55 star(s) with 43 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of face-recognition-service is current.

Quality

face-recognition-service has 0 bugs and 0 code smells.

Security

face-recognition-service has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

face-recognition-service code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

face-recognition-service does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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face-recognition-service releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

face-recognition-service saves you 126 person hours of effort in developing the same functionality from scratch.

It has 316 lines of code, 20 functions and 7 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

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face-recognition-service Key Features

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Community Discussions

Trending Discussions on face-recognition-service

AWS Rekognition Service: Improve facial recognition accuracy

QUESTION

AWS Rekognition Service: Improve facial recognition accuracy

Asked 2018-Jul-10 at 03:33

I'm finding the right way to use AWS Rekognition service.

My problem is How to verify a person image on multi collections, I'm reading Build Your Own Face Recognition Service Using Amazon Rekognition | AWS Machine Learning Blog from Amazon but cannot find the implementation document for it. My point is Face verification title.

Update 1:

My target is: Using AWS Rekognition to get person's info by their face.

My problem is: How to make AWS Rekognition improves its accuracy when recognizing a face.

What I tried:

Upload multi captured portraits of a person with same ExternalImageID but I'm not sure it works or not.
Finding a way to create Collection for each person, then upload person's portraits to their Collection but I don't how to search a face through multiple Collections.
I'm trying use S3 for storage people's images then using Lambda function to do something that I've not got yet.

Update 2:

What is your input material: Input materials are some people's portrait photo with ExternalImageID is their name (eg: my portrait photo will have ExternalImageID is "Long").
What are you trying to do: I'm trying to get ExternalImageID when I send a portrait photo of a registered person. (eg: with my other portrait photo, AWS has to response ExternalImageID is "Long").
Do you have it working, but it is not recognizing some people? Yes, it's work but sometimes it cannot recognize exactly people.
Please tell us your use-case / scenario and what you are trying to accomplish:
- Create an AWS Rekognition collection with sample name (eg facetest).
- Register some people with their name is ExternalImageID.
- Submit an image to AWS Rekognition API to get ExternalImageID - his name.

...

ANSWER

Answered 2018-Jul-10 at 03:33

Okay, so basically you have it working but it doesn't always recognise the person. I'll assume it does not even list the person in the response, even with a low percentage.

I would recommend adding multiple images of the same person to the Face Collection, specifying the same ExternalImageId for each image. (Use one Face Collection with all people in it, including multiple images of the same person.)

Please note that "If you provide the same image, specify the same collection, and use the same external ID in the IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata." However, adding different images with the same ExternalImageId should be fine.

Source https://stackoverflow.com/questions/51186135

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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