Remove NSFWJS

structures/Tensorflow.js

@@ -1,5 +1,4 @@
 const tf = require('@tensorflow/tfjs-node');
-const nsfw = require('nsfwjs');
 const faceDetection = require('@tensorflow-models/face-detection');
 const faceModel = faceDetection.SupportedModels.MediaPipeFaceDetector;
 const path = require('path');
@@ -9,18 +8,11 @@ module.exports = class Tensorflow {
 	constructor(client) {
 		Object.defineProperty(this, 'client', { value: client });
 
-		this.nsfwjs = null;
 		this.faceDetector = null;
 		this.styleModel = null;
 		this.transformerModel = null;
 	}
 
-	async loadNSFWJS() {
-		const nsfwjs = await nsfw.load('MobileNetV2');
-		this.nsfwjs = nsfwjs;
-		return this.nsfwjs;
-	}
-
 	async loadFaceDetector() {
 		const faceDetector = await faceDetection.createDetector(faceModel, { runtime: 'tfjs', maxFaces: 10 });
 		this.faceDetector = faceDetector;
@@ -55,22 +47,6 @@ module.exports = class Tensorflow {
 		return faces;
 	}
 
-	async isImageNSFW(image, bool = true) {
-		const img = await tf.node.decodeImage(image, 3);
-		const predictions = await this.nsfwjs.classify(img);
-		img.dispose();
-		if (bool) {
-			const results = [];
-			results.push(predictions[0]);
-			for (const result of predictions) {
-				if (result.className === predictions[0].className) continue;
-				if (result.probability >= predictions[0].probability - 0.1) results.push(result);
-			}
-			return results.some(result => result.className !== 'Drawing' && result.className !== 'Neutral');
-		}
-		return predictions;
-	}
-
 	async stylizeImage(image, styleImg) {
 		const imageTensor = await tf.node.decodeImage(image, 3);
 		const [originalHeight, originalWidth] = imageTensor.shape.slice(0, 2);