在这里,我正在从网络摄像头捕获图像。但是我无法将图像传输到谷歌云视觉 api。我还想在通过 api 捕获图像和图像传输时进行文本检测。 有人可以帮忙解决这个问题吗? 这是网络摄像头代码
<script>
(function() {
var width = 320; // We will scale the photo width to this
var height = 0; // This will be computed based on the input stream
var streaming = false;
var video = null;
var canvas = null;
var photo = null;
var startbutton = null;
var data=null;
function startup() {
video = document.getElementById('video');
canvas = document.getElementById('canvas');
photo = document.getElementById('photo');
startbutton = document.getElementById('startbutton');
navigator.mediaDevices.getUserMedia({
video: true,
audio: false
})
.then(function(stream) {
video.srcObject = stream;
video.play();
})
.catch(function(err) {
console.log("An error occurred: " + err);
});
video.addEventListener('canplay', function(ev) {
if (!streaming) {
height = video.videoHeight / (video.videoWidth / width);
if (isNaN(height)) {
height = width / (4 / 3);
}
video.setAttribute('width', width);
video.setAttribute('height', height);
canvas.setAttribute('width', width);
canvas.setAttribute('height', height);
streaming = true;
}
}, false);
startbutton.addEventListener('click', function(ev) {
takepicture();
ev.preventDefault();
}, false);
clearphoto();
quickstart()
}
function clearphoto() {
var context = canvas.getContext('2d');
context.fillStyle = "#AAA";
context.fillRect(0, 0, canvas.width, canvas.height);
data = canvas.toDataURL('image/png');
photo.setAttribute('src', data);
}
function takepicture() {
var context = canvas.getContext('2d');
if (width && height) {
canvas.width = width;
canvas.height = height;
context.drawImage(video, 0, 0, width, height);
data = canvas.toDataURL('image/png');
photo.setAttribute('src', data);
} else {
clearphoto();
}
}
window.addEventListener('load', startup, false);
})();
</script>
我想在网络摄像头部分添加该代码。
// Imports the Google Cloud client library
async function quickstart() {
process.env.GOOGLE_APPLICATION_CREDENTIALS = "/home/manu/Cap/Real_Time/VisionAPI_DEMO/ServiceAccountToken.json"
const vision = require('@google-cloud/vision');
const client = new vision.ImageAnnotatorClient();
// Performs text detection on the local file
const [result] = await client.textDetection("image/test.jpg");
const detections = result.textAnnotations;
const [ text, ...others ] = detections
console.log(`Text: ${ text.description }`);
}
quickstart()