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deeplearn.js playground 1509994912630
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| <h1 align=center>SqueezeNet Cat Demo</h1> | |
| <script src='https://unpkg.com/deeplearn-squeezenet'></script> | |
| <img id='cat' src='https://storage.googleapis.com/learnjs-data/images/cat.jpeg' width=227 height=227 crossorigin onClick="{ | |
| document.getElementById('myDivOut').innerHTML = '' // clear the div | |
| }"><br><br> | |
| <input id="myFile01" type=text size=100 value='https://storage.googleapis.com/learnjs-data/images/cat.jpeg' onChange="{ | |
| document.getElementById('cat').src = this.value | |
| document.getElementById('myDivOut').innerHTML = '' // clear the div | |
| }"><br><br> | |
| <div id="myDivOut">...</div> | |
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| const catImage = document.getElementById('cat'); | |
| const math = new dl.NDArrayMathGPU(); | |
| const squeezeNet = new squeezenet.SqueezeNet(math); | |
| await squeezeNet.load(); | |
| const image = dl.Array3D.fromPixels(catImage); | |
| const inferenceResult = await squeezeNet.predict(image); | |
| const topClassesToProbs = await squeezeNet.getTopKClasses(inferenceResult.logits, 10); | |
| document.getElementById('myDivOut').innerHTML = '' // clear the div | |
| for (const className in topClassesToProbs) { | |
| document.getElementById('myDivOut').innerHTML += topClassesToProbs[className].toFixed(5) + ' : '+ className + '<br>' | |
| } |
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