npm i nsfw-filter
import NSFWFilter from 'nsfw-filter';
const isSafe = await NSFWFilter.isSafe(image);
import { useState } from 'react';
import NSFWFilter from 'nsfw-filter';
function ImageUploader() {
const [imageUrl, setImageUrl] = useState('');
const handleImageUpload = async (event) => {
const file = event.target.files[0];
// Check to see if the image is appropriate
const isSafe = await NSFWFilter.isSafe(file);
if (!isSafe) return 'Image is not appropriate';
// Process the image if it is safe
if (file) {
const reader = new FileReader();
reader.onloadend = () => {
setImageUrl(reader.result);
};
reader.readAsDataURL(file);
}
};
return (
<div>
<input type="file" onChange={handleImageUpload} />
{imageUrl && <img src={imageUrl} alt="Uploaded" />}
</div>
);
}
export default ImageUploader;
nsfw-filter
is currently used in production to process hundreds of thousands of images for a popular image restoration service called restorePhotos. It helps prevent people from uploading inappropriate pictures. See how it's used here.
you can polyfill the core node modules used in nsfw-filter for browser compatibility such as
["path", "stream", "assert", "events", "zlib", "util", "buffer"]
more on this: https://vitejs.dev/guide/troubleshooting.html
install vite-plugin-node-polyfills
with npm: https://www.npmjs.com/package/vite-plugin-node-polyfills
in vite.config.js
import { defineConfig } from "vite";
import react from "@vitejs/plugin-react-swc";
import { nodePolyfills } from "vite-plugin-node-polyfills";
import path from "path";
export default defineConfig({
plugins: [
nodePolyfills({
// To add only specific polyfills, add them here. If no option is passed, adds all polyfills
include: ["path", "stream", "assert", "events", "zlib", "util", "buffer"],
}),
react(),
],
resolve: {
alias: {
"@": path.resolve(__dirname, "./src"),
"~": path.resolve(__dirname, "./"),
},
},
});
bonus: you can polyfill path to support path aliases for vite when you deploy your could on the cloud for example vercel.
so you can use @
import { cn } from "@/lib/utils"
disclaimer: using nsfw-filter on the browser will dramatically increase your bundle size.
This library uses both Tensorflow.js, an OSS library for machine learning models, and nsfwjs
to predict whether a given image is NSFW (Not Safe For Work).