Face-Recognition_Flutter VS OPUS-MT-train

Compare Face-Recognition_Flutter vs OPUS-MT-train and see what are their differences.

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Face-Recognition_Flutter OPUS-MT-train
2 1
61 302
- 5.3%
0.0 1.7
over 3 years ago about 2 months ago
Makefile Makefile
Apache License 2.0 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.
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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.

Face-Recognition_Flutter

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

OPUS-MT-train

Posts with mentions or reviews of OPUS-MT-train. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-21.
  • Amazon releases 51-language dataset for language understanding
    2 projects | news.ycombinator.com | 21 Apr 2022
    https://translatelocally.com/ is a nice gui around marian/bergamot. So far not very many bundled pairs, though I would guess any of the models from https://github.com/Helsinki-NLP/Opus-MT-train/tree/master/mo... and https://github.com/Helsinki-NLP/Tatoeba-Challenge/blob/maste... should be usable.

    There is also Apertium, a rule-based system which is very good for some closely-related pairs that have had a lot of work put into them (especially translation between Romance languages, e.g. Spanish→Catalan, and Norwegian Bokmål→Nynorsk), and the only OK translator for some lesser-resourced languages (e.g. Northern Saami→Norwegian Bokmål), but very underdeveloped for anything to/from English (it feels a bit pointless writing rules for English where there is so much available data; RBMT shines where there's not enough available data, ie. most of the languages of the world)

What are some alternatives?

When comparing Face-Recognition_Flutter and OPUS-MT-train you can also consider the following projects:

awesome-flutter - An awesome list that curates the best Flutter libraries, tools, tutorials, articles and more.

Opus-MT - Open neural machine translation models and web services

Google-MLKit-Android-Apps - All Android Applications using Google MLKit [Java & Kotlin]

NLP-progress - Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

firekart - An Ecommerce application built in Flutter using Nodejs and MySQl.

Tatoeba-Challenge

flutter_programs - Experiments with Mobile

tensor2tensor - Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

tailor_made - ✄ Managing a Fashion designer's daily routine.

klpt - The Kurdish Language Processing Toolkit

Random-Face-Generator - A Cross-Platform(Web, Android, iOS, Linux and Macos) app to Generate Faces of People (These people don't actually exist) made using Flutter.

deep-learning-drizzle - Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!