.net 调用 nsfwjs 进行视频鉴别

npm install express --save
npm install multer --save
npm install jpeg-js --save
npm install @tensorflow/tfjs-node --save
npm install nsfwjs --save

const express = require(‘express‘)
const multer = require(‘multer‘)
const jpeg = require(‘jpeg-js‘)
const tf = require(‘@tensorflow/tfjs-node‘)
const nsfw = require(‘nsfwjs‘)
const app = express()
const upload = multer()
let _model
const convert = async (img) => {
// Decoded image in UInt8 Byte array
const image = await jpeg.decode(img, true)
const numChannels = 3
const numPixels = image.width * image.height
const values = new Int32Array(numPixels * numChannels)
for (let i = 0; i < numPixels; i++)
for (let c = 0; c < numChannels; ++c)
values[i * numChannels + c] = image.data[i * 4 + c]
return tf.tensor3d(values, [image.height, image.width, numChannels], ‘int32‘)
}
app.post(‘/nsfw‘, upload.single(‘image‘), async (req, res) => {
if (!req.file) res.status(400).send(‘Missing image multipart/form-data‘)
else {
const image = await convert(req.file.buffer)
const predictions = await _model.classify(image)
image.dispose()
res.json(predictions)
}
})
const load_model = async () => {
_model = await nsfw.load() //you can specify module here
}
// Keep the model in memory, make sure it‘s loaded only once
load_model().then(() => app.listen(8080))

node server.js

curl --request POST localhost:8080/nsfw --header ‘Content-Type: multipart/form-data‘ --data-binary ‘image=@myimg.jpg‘

curl -F "image=@myimg.jpg" "http://localhost:8080/nsfw"