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/ distr/ Shinobi/ plugins/ tensorflow/ - drwxr-xr-x |
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Select action/file-type: // // Shinobi - Tensorflow Plugin // Copyright (C) 2016-2025 Moe Alam, moeiscool // // # Donate // // If you like what I am doing here and want me to continue please consider donating :) // PayPal : paypal@m03.ca // // ============================================================== // IF THIS TEST FAILS REINSTALL THE FOLLOWING NPM MODULES // - tfjs-core@2.3.0 // - tfjs-converter@2.3.0 // version 2.3.0 is selected for this example. Make it point to the version of tfjs-node(-gpu) in use. // ============================================================== // Not working still? You may need to run following inside this folder. // npm rebuild @tensorflow/tfjs-node-gpu@1.7.3 build-addon-from-source --unsafe-perm // ============================================================== console.log('############################################') console.log('@tensorflow/tfjs-node(-gpu) module test for Object Detection') // Base Init >> var fs = require('fs'); const fetch = require('node-fetch'); // Base Init />> var tf const tfjsBuild = process.argv[2] try{ switch(tfjsBuild){ case'gpu': console.log('GPU Test for Tensorflow Module') tf = require('@tensorflow/tfjs-node-gpu') break; case'cpu': console.log('CPU Test for Tensorflow Module') tf = require('@tensorflow/tfjs-node') break; default: console.log('Nothing selected, using CPU Module for test.') console.log(`Hint : Run the script like one of the following to specify cpu or gpu.`) console.log(`node test.js cpu`) console.log(`node test.js gpu`) tf = require('@tensorflow/tfjs-node') break; } }catch(err){ console.log(`Selection Failed. Could not load desired module. ${tfjsBuild}`) console.log(err) } if(!tf){ try{ tf = require('@tensorflow/tfjs-node-gpu') }catch(err){ try{ tf = require('@tensorflow/tfjs-node') }catch(err){ return console.log('tfjs-node could not be loaded') } } } console.log('############################################') const cocossd = require('@tensorflow-models/coco-ssd'); // const mobilenet = require('@tensorflow-models/mobilenet'); async function loadCocoSsdModal() { const modal = await cocossd.load({ base: 'lite_mobilenet_v2', //lite_mobilenet_v2 modelUrl: null, }) return modal; } // async function loadMobileNetModal() { // const modal = await mobilenet.load({ // version: 1, // alpha: 0.25 | .50 | .75 | 1.0, // }) // return modal; // } function getTensor3dObject(numOfChannels,imageArray) { const tensor3d = tf.node.decodeJpeg( imageArray, numOfChannels ); return tensor3d; } // const mobileNetModel = this.loadMobileNetModal(); var loadCocoSsdModel = { detect: function(){ return {data:[]} } } async function init() { loadCocoSsdModel = await loadCocoSsdModal(); } init() const runDetection = async (inputImage,type) => { const startTime = new Date(); const tensor3D = getTensor3dObject(3,(inputImage)); let predictions = await loadCocoSsdModel.detect(tensor3D); tensor3D.dispose(); return { data: predictions, type: type, time: new Date() - startTime } } const testImageUrl = `https://cdn.shinobi.video/images/test/car.jpg` const testImageUrl2 = `https://cdn.shinobi.video/images/test/bear.jpg` const testImageUrl3 = `https://cdn.shinobi.video/images/test/people.jpg` const runTest = async (imageUrl) => { console.log(`Loading ${imageUrl}`) const response = await fetch(imageUrl); const frameBuffer = await response.buffer(); console.log(`Detecting upon ${imageUrl}`) const resp = await runDetection(frameBuffer) const results = resp.data console.log(resp) if(results[0]){ var mats = [] results.forEach(function(v){ console.log({ x: v.bbox[0], y: v.bbox[1], width: v.bbox[2], height: v.bbox[3], tag: v.class, confidence: v.score, }) }) }else{ console.log('No Matrices...') } console.log(`Done ${imageUrl}`) } const allTests = async () => { await runTest(testImageUrl) await runTest(testImageUrl2) await runTest(testImageUrl3) } allTests() |
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