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go-nude — Go Library for Image Nudity Detection | Open Awesome

go-nude

go-nude

MITGo

A Go library for detecting nudity in images, ported from nude.js.

What is go-nude?

go-nude is a Go library that provides nudity detection capabilities for images. It helps developers implement content filtering and moderation features by identifying potentially inappropriate visual content using skin region identification in JPEG images.

Target Audience

Go developers building applications that require automated content moderation, such as social media platforms, image hosting services, or user-generated content systems.

Value Proposition

Developers choose go-nude for its minimalistic, single-purpose design with a straightforward API, and because it's a reliable Go port of the established nude.js algorithm, offering consistency with implementations in other languages like Ruby and Python.

Overview

Nudity detection with Go.

Use Cases

Best For

Implementing automated nudity detection in Go-based web applications
Adding content filtering to image upload systems to flag inappropriate content

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421 stars51 forks0 contributors

Building moderation tools for user-generated image galleries or forums

Creating safety features in chat applications that handle image sharing

Integrating basic visual content analysis into Go backend services

Porting existing nudity detection logic from JavaScript, Ruby, or Python to Go

Not Ideal For

Applications requiring high-precision nudity detection with low false positive rates, such as legal or medical imaging systems
Projects that need to process multiple image formats beyond JPEG, like PNG or WebP
Real-time content moderation systems where processing speed is critical and every millisecond counts
Teams seeking customizable detection thresholds or integration with modern machine learning pipelines

Pros & Cons

Pros

Straightforward API

Offers a simple `IsNude()` function that returns a boolean, making it easy to integrate without extensive configuration, as shown in the example code.

Cross-Language Portability

Based on the established nude.js algorithm, allowing developers familiar with Ruby or Python implementations to port logic seamlessly to Go.

Minimalistic Design

Follows a single-purpose approach with a clean interface, reducing complexity for basic nudity detection needs, aligning with its philosophy.

Built-in Error Handling

Returns errors for issues like invalid image paths or processing failures, aiding in robust application development, as mentioned in the key features.

Cons

JPEG-Only Support

Primarily handles JPEG images, as indicated in the key features, limiting its utility in environments with diverse image formats like PNG or GIF.

Outdated Algorithm

Relies on the nude.js algorithm, which may not match the accuracy of contemporary machine learning-based solutions, leading to potential inaccuracies in detection.

No Customization Options

Lacks parameters to adjust detection sensitivity or tailor the analysis, which could be necessary for specific moderation use cases beyond basic filtering.

Sparse Documentation

The README is minimal, offering few examples or details on performance benchmarks, making it challenging for thorough evaluation and adoption.

Frequently Asked Questions

Quick Stats

Stars421

Forks51

Contributors0

Open Issues0

Last commit2 years ago

CreatedSince 2014

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#image-analysis

#image-processing

#content-filtering

#computer-vision

#content-moderation