Our great sponsors
| tfgo | GoLearn | |
|---|---|---|
| 5 | 3 | |
| 2,300 | 9,030 | |
| - | - | |
| 0.0 | 0.0 | |
| 2 months ago | 7 months ago | |
| Go | Go | |
| 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.
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.
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.
tfgo
Posts with mentions or reviews of tfgo.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-01.
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Introducing GoFaceRec: A Go-based Face Recognition Tool Using Deep Learning
I'm excited to share a project I've been working on: [GoFaceRec](https://github.com/modanesh/GoFaceRec). This is a face recognition tool built in Go, leveraging the power of MTCNN for face detection and QMagFace for face recognition. The project was born out of a desire to bring the power of deep learning models to the Go community. After much effort, I concluded that the best approach was to convert models to TensorFlow and then work with tfgo, a Go binding to TensorFlow's C API. In GoFaceRec, the input image is first processed, and then its embeddings are compared against the ones already computed from our dataset. If the distance between embeddings falls below a specific threshold, then the face is considered as unknown. Otherwise, the proper label will be printed. The project is tested using Go 1.17 on Ubuntu 20.04. For gocv, the version of OpenCV installed is 4.7. And for tfgo, I installed [this version](https://github.com/galeone/tfgo) instead of the official one. You can install this package by running the following command in your project: > go get github.com/modanesh/[email protected] You can find more detailed instructions on how to use the tool in the [GitHub repository](https://github.com/modanesh/GoFaceRec). I welcome any feedback, suggestions, or contributions to the project. I'm looking forward to seeing how the community uses GoFaceRec and hope it can be a valuable tool for those working on face recognition tasks. Happy coding! 🚀
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Why can't Go be popular for machine learning?
Paolo Galeone has improved bindings (tfgo) that can be used for training and deployment.
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How to train a model for object detection in Golang?
https://github.com/galeone/tfgo here is a very good tutorial. I would suggest starting there.
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What libraries from other languages do you wish were ported over into go?
Tensorflow is actually written in C++, and the python package is just bindings to tensorflow. There are Tensorflow Go bindings: https://github.com/galeone/tfgo.
GoLearn
Posts with mentions or reviews of GoLearn.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-06.
What are some alternatives?
When comparing tfgo and GoLearn you can also consider the following projects:
Gorgonia - Gorgonia is a library that helps facilitate machine learning in Go.
sklearn - bits of sklearn ported to Go #golang
goml - On-line Machine Learning in Go (and so much more)
neural-go - A multilayer perceptron network implemented in Go, with training via backpropagation.
gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library
regommend - Recommendation engine for Go
go-fann - Go bindings for FANN, library for artificial neural networks
onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
randomforest - Random Forest implementation in golang
bayesian - Naive Bayesian Classification for Golang.
neat