问题
I am trying to run custom object detection tensorflow.js model in a browser. I could able to convert tensorflow model to tensorflow.js model (in google colab) using the following command:
!tensorflowjs_converter \
--input_format=tf_frozen_model \
--output_node_names='detection_boxes,detection_scores,detection_classes,num_detections' \
/content/frozen_inference_graph.pb \
/content/web_model
I am sharing the code snippet of inference.html
file:
<html>
<head>
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest"> </script>
<script src="webcam.js"></script>
</head>
<body>
<div>
<div>
<video autoplay playsinline muted id="wc" width="224" height="224"></video>
</div>
</div>
<button type="button" id="startPredicting" onclick="startPredicting()" >Start Predicting</button>
<button type="button" id="stopPredicting" onclick="stopPredicting()" >Stop Predicting</button>
<div id="prediction"></div>
</body>
<script src="index.js"></script>
</html>
The code snippet of index.js
file is as follow:
let model;
const webcam = new Webcam(document.getElementById('wc'));
let isPredicting = false;
async function init(){
try {
await webcam.setup();
model = await tf.loadGraphModel('http://127.0.0.1:8887/model/model.json');
} catch (err) {
console.log(err);
}
}
async function predict() {
const img = webcam.capture();
console.log("executing model");
const cat = document.getElementById('image');
output = await model.executeAsync(img);
output.forEach(t => t.print) // log out the data of all tensors
const data = []
for (let i = 0; i < output.length; i++){
data.push(output.dataSync())
}
console.log(data);
}
init()
function startPredicting(){
isPredicting = true;
predict();
}
function stopPredicting(){
isPredicting = false;
predict();
}
When I run above inference.html
file using web server, it returns the following output:
(4) [t, t, t, t]
0: t {kept: false, isDisposedInternal: false, shape: Array(3), dtype: "float32", size: 400, …}
1: t {kept: false, isDisposedInternal: false, shape: Array(2), dtype: "float32", size: 100, …}
2: t {kept: false, isDisposedInternal: false, shape: Array(2), dtype: "float32", size: 100, …}
3: t {kept: false, isDisposedInternal: false, shape: Array(1), dtype: "float32", size: 1, …}
length: 4
__proto__: Array(0)
The problem is output seems to be irrelevant or I can't understand it. Am I missing something? Please provide me your suggestions. I am sorry for the long post but I am beginner in tensorflow.js.
回答1:
output
is a tf.Tensor. When you called console.log(output)
, it tries to stringify the object and prints out its properties
.
The tensor also has the method, print
to log out its data.
To get the data out of the tensor as a javaScript array, method such as data
(respectively dataSync
) and dataArray
(respectively dataArraySync
) can be called to retrieve the data aynchronously (respectively synchronously). The data is retrieved as a typedArray
.
output = await model.executeAsync(img);
// output is an array of tf.tensor.
output.forEach(t => t.print()) // log out the data of all tensors
const data = []
for (let i = 0; i < output.length; i++)
data.push(output[i].dataSync()) // get the data
来源:https://stackoverflow.com/questions/59575812/how-to-interpret-the-output-of-object-detection-model-in-tensorflow-js