Hello guys ,
I’m trying to implement a web application for object detection on images using TensorFlow.js. I’ve trained my model and loaded it using “tf.loadLayersModel()”. Then I made predictions using “model.predict()” function. The problem is that I don’t understand how to interpret “predict” which is model.predict() output.
The output from "console.log(predict); " is :
Array(3) [ {…}, {…}, {…} ]
​0: Object { kept: false, isDisposedInternal: false, dtype: “float32”, … }
​1: Object { kept: false, isDisposedInternal: false, dtype: “float32”, … }
​2: Object { kept: false, isDisposedInternal: false, dtype: “float32”, … }
​length: 3​
The output from “console.log(predict[0].dataSync())” is :
Float32Array(18) [ -0.933699369430542, 2.0597338676452637, -8.093562126159668, -1.653637170791626, 29.91468048095703, -2.5104284286499023, -1.6961907148361206, 5.431970596313477, -8.678093910217285, 1.1465117931365967, … ]
The output from “console.log(predict[1].dataSync())” is :
Float32Array(72) [ -3.040828227996826, 19.110309600830078, -0.057641081511974335, -1.872375249862671, -124.70093536376953, 2.4474217891693115, 11.702408790588379, -9.773043632507324, -3.7172935009002686, 5.327491283416748, … ]
The output from “console.log(predict[2].dataSync())” is :
Float32Array(288) [ -36.274513244628906, -19.568172454833984, 12.820204734802246, -21.152021408081055, -225.57720947265625, 1.2267011404037476, 6.923470497131348, 26.43770408630371, 2.0712578296661377, -11.071444511413574, … ]
The aim is to get boxes location.
Thanks !