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Update index.js
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index.js
CHANGED
@@ -167,10 +167,16 @@ app.post('/api/nsfw-check', async (req, res) => {
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responseType: "arraybuffer"
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})
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const response = await check_nsfw(data_img.data)
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res.json(
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} else if (images && typeof images == 'string' && isBase64(images)) {
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const response = await check_nsfw(Buffer.from(images, "base64"))
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res.json(
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} else {
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res.json({
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success: false, message: 'No url or base64 detected!!'
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@@ -336,9 +342,12 @@ async function check_nsfw(buffer) {
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const image = await tfjs.node.decodeImage(buffer,3)
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const predictions = await model.classify(image)
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image.dispose() // Tensor memory must be managed explicitly (it is not sufficient to let a tf.Tensor go out of scope for its memory to be released).
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})
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}
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responseType: "arraybuffer"
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})
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const response = await check_nsfw(data_img.data)
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res.json({
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status: "ok",
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result: response
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})
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} else if (images && typeof images == 'string' && isBase64(images)) {
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const response = await check_nsfw(Buffer.from(images, "base64"))
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res.json({
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status: "ok",
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result: response
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})
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} else {
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res.json({
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success: false, message: 'No url or base64 detected!!'
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const image = await tfjs.node.decodeImage(buffer,3)
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const predictions = await model.classify(image)
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image.dispose() // Tensor memory must be managed explicitly (it is not sufficient to let a tf.Tensor go out of scope for its memory to be released).
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cosnt results = prediction.map(v => {
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return {
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class_name: v.className,
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probability: v.probability,
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probability_percent: (v.probability * 100).toFixed(2)
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}
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})
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return results
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}
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