Image File Compression before upload - javascript

The method below is being used as a parameter for another variable. But the problem here is that it is not returning the file back after it is being compressed.
async CompressImage(imageFile: File): Promise<File> {
return new Promise<File>((resolve, reject) => {
const cReader = new FileReader();
const image = new Image();
cReader.onload = () => {
image.src = cReader.result.toString();
image.onload = () => {
const canvas = document.createElement("canvas");
const context = canvas.getContext("2d");
context.drawImage(image, 0, 0);
//width & height initialization
canvas.width = width;
canvas.height = height;
var ctx = canvas.getContext("2d");
ctx.drawImage(image, 0, 0, width, height);
const convertedFile = canvas.toBlob((blob) => {
const scaledDown = new File([blob], imageFile.name);
});
resolve(convertedFile);
}
};
cReader.readAsDataURL(mediaFile);
});
}

Related

Uncaught (in promise) Error: Failed to compile fragment shader Error in Tensorflow.js project

I'm using face-api.js Javascript API to develop a web app that user uploads her/his picture and we want to detect faces in the picture.
On the other hand I used VGGface 16 model json formatted to predict that user uploaded image is similar to which celebrity.
following are my javascript codes:
const MODEL_URL = '../faceapi_models'
Promise.all([
faceapi.nets.ssdMobilenetv1.loadFromUri(MODEL_URL),
faceapi.nets.faceRecognitionNet.loadFromUri(MODEL_URL),
// faceapi.nets.faceLandmark68Net.loadFromUri(MODEL_URL),
])
.then((val) => {
console.log('val')
})
.catch((err) => {
console.log(err)
})
let model
async function loadModel() {
model = await tf.loadLayersModel('../web_model/vgg_model.json');
}
loadModel()
.then((val) => {
console.log('Model is Loaded');
})
.catch((err) => {
console.log('Model Not Load : ' + err)
})
let croppedImage = null;
const user_pic = document.getElementById('user_pic')
const preview = document.getElementById('preview')
const canvas = document.getElementById('canvas');
const ctx = canvas.getContext('2d');
window.onload = function() {
canvas.width = preview.width;
canvas.height = preview.height;
ctx.drawImage(preview, 0, 0);
};
preview.onclick = () => user_pic.click()
user_pic.addEventListener('change', () => {
const reader = new FileReader()
reader.onload = (e) => {
const img = new Image();
img.onload = function() {
canvas.width = img.width;
canvas.height = img.height;
ctx.drawImage(img, 0, 0);
};
img.src = e.target.result;
}
reader.readAsDataURL(user_pic.files[0]);
detectFaces(user_pic.files[0])
})
async function detectFaces(input) {
let imgURL = URL.createObjectURL(input)
const imgElement = new Image()
imgElement.src = imgURL
const results = await faceapi.detectAllFaces(imgElement)
.then(results => {
if (Array.isArray(results) && results.forEach) {
results.forEach(result => {
const { x, y, width, height } = result.box;
const crop = ctx.getImageData(x, y, width, height);
croppedImage = new ImageData(crop.data, width, height);
const input = tf.browser.fromPixels(croppedImage);
const resizedImage = tf.image.resizeBilinear(input, [224, 224]);
const inputTensor = resizedImage.expandDims(0);
const predictions = model.predict(inputTensor).data();
const celebrityIndex = predictions.indexOf(Math.max(...predictions));
console.log(celebrityIndex)
// const celebrityName = celebrityLabels[celebrityIndex];
// Display the results
// const resultDisplay = document.getElementById('result');
// resultDisplay.innerHTML = `Most similar celebrity: ${celebrityName}`;
});
} else {
console.error('Results is not an array or does not have a forEach function.');
}
});
}
I have solve many problem that I have yet but I do not know how to handle this problem and Why did this problem arise?
This is complete erorr :
I found that problem is with x, y, width, height constants that had float values. a simple way is converting those to Int like this :
const {x, y, width, height} = result.box;
const xInt = Math.floor(x);
const yInt = Math.floor(y);
const widthInt = Math.floor(width);
const heightInt = Math.floor(height);

How to turn this promise based function into rxjs function?

I have this promise based function and im trying to update it to have the same functionality but use RXJS, im a bit new to rxjs and having a lot of trouble.. any help would be really appreciated
public getBase64ImageFromURL(url: string): Promise<any> {
return new Promise((resolve, reject) => {
const img = new Image();
img.setAttribute('crossOrigin', 'anonymous');
img.onload = () => {
const canvas = document.createElement('canvas');
canvas.width = img.width;
canvas.height = img.height;
const ctx = canvas.getContext('2d');
ctx.drawImage(img, 0, 0);
const dataURL = canvas.toDataURL('image/png');
resolve(dataURL);
};
img.onerror = error => {
reject(error);
};
img.src = url;
});
}
It's pretty straight forward : create a new Observable and next the same value as the resolve !
public getBase64ImageFromURL(url: string): Observable<string> {
return new Observable<string>((subscriber) => {
const img = new Image();
img.setAttribute('crossOrigin', 'anonymous');
img.onload = () => {
const canvas = document.createElement('canvas');
canvas.width = img.width;
canvas.height = img.height;
const ctx = canvas.getContext('2d');
ctx.drawImage(img, 0, 0);
const dataURL = canvas.toDataURL('image/png');
subscriber.next(dataURL);
};
img.onerror = (error) => {
subscriber.error(error);
};
img.src = url;
});
}

How to extract the detected faces from face-api.js

I am using a Javascript library called face-api.js.
I need to extract the face from the video frame when face-api detects a face. Could anyone help me to do that part?
const video = document.getElementById('video');
Promise.all([
faceapi.nets.tinyFaceDetector.loadFromUri('/models')
]).then(startVideo)
function startVideo() {
navigator.getUserMedia(
{video: {}},
stream => video.srcObject = stream,
err => console.error(err)
)
}
video.addEventListener('play', () => {
const canvas = faceapi.createCanvasFromMedia(video);
document.body.append(canvas);
const displaySize = {width: video.width, height: video.height};
faceapi.matchDimensions(canvas, displaySize);
setInterval(async () => {
const detections = await faceapi.detectAllFaces(video, new faceapi.TinyFaceDetectorOptions())
console.log('Box: ', detections[0].detection._box);
const resizedDetections = faceapi.resizeResults(detections, displaySize)
canvas.getContext('2d').clearRect(0, 0, canvas.width, canvas.height)
faceapi.draw.drawDetections(canvas, resizedDetections)
}, 5000)
})
Add extractFaceFromBox function to your code, it can extract a face from video frames with giving bounding box and display result into outputimage.
Try this code and enjoy
// This is your code
video.addEventListener('play', () => {
const canvas = faceapi.createCanvasFromMedia(video);
document.body.append(canvas);
const displaySize = {width: video.width, height: video.height};
faceapi.matchDimensions(canvas, displaySize);
setInterval(async () => {
const detections = await faceapi.detectAllFaces(video, new faceapi.TinyFaceDetectorOptions())
//Call this function to extract and display face
extractFaceFromBox(video, detections[0].detection.box)
const resizedDetections = faceapi.resizeResults(detections, displaySize)
canvas.getContext('2d').clearRect(0, 0, canvas.width, canvas.height)
faceapi.draw.drawDetections(canvas, resizedDetections)
}, 5000)
})
let outputImage = document.getElementById('outputImage')
// This function extract a face from video frame with giving bounding box and display result into outputimage
async function extractFaceFromBox(inputImage, box){
const regionsToExtract = [
new faceapi.Rect( box.x, box.y , box.width , box.height)
]
let faceImages = await faceapi.extractFaces(inputImage, regionsToExtract)
if(faceImages.length == 0){
console.log('Face not found')
}
else
{
faceImages.forEach(cnv =>{
outputImage.src = cnv.toDataURL();
})
}
}
This is not specific to face-api.js but you can use canvas to extract an image from a video. Here is a little function I wrote in my case.
const extractFace = async (video,x,y,width, height) => {
const canvas = document.createElement("canvas");
canvas.width = video.videoWidth;
canvas.height = video.videoHeight;
const context = canvas.getContext("2d");
// Get a screenshot from the video
context?.drawImage(video, 0, 0, canvas.width, canvas.height);
const dataUrl = canvas.toDataURL("image/jpeg");
const image = new Image();
image.src = dataUrl;
const canvasImg = document.createElement("canvas");
canvasImg.width = width;
canvasImg.height = height;
const ctx = canvasImg.getContext("2d");
image.onload = () => {
// Crop the image
ctx?.drawImage(image, x, y, width, height, 0, 0, width, height);
canvasImg.toBlob((blob) => {
// Do something with the blob. Alternatively, you can convert it to a DataUrl like the video screenshot
// I was using react so I just called my handler
handSavePhoto(blob);
}, "image/jpeg");
};
};
You don't have to take the screenshot first, you can just go ahead and crop it but I found out after testing that cropping from an image gives consistent results. Here is how you will achieve it in that case.
const extractFace = async (video, x, y, width, height) => {
const canvas = document.createElement("canvas");
canvas.width = width;
canvas.height = height;
const context = canvas.getContext("2d");
// Get a screenshot from the video
context?.drawImage(image, x, y, width, height, 0, 0, width, height);
canvas.toBlob((blob) => {
handSavePhoto(blob);
}, "image/jpeg");
};
With that out of the way, you can now use face-api data to get the face you want.
// assuming your video element is store in video variable
const detections = await faceapi.detectAllFaces(video, new faceapi.TinyFaceDetectorOptions());
const {x, y, width, height} = detections[0].detection.box;
extractFace(video, x, y, width, height);
You can read more about drawImage from here.
Check if detection.length is bigger than 0. It means that it detects something in front of it.

Angular 4: TypeError: this.function is not a function

I run out of ideas.. I saw this question got asked many times here and here and many more, but I could not find a way to solve my issue. So as I understood, the problem is this it does not refer to the correct context. How do I use an arrow function to capture this from the declaration site?
drawImageProp(ctx, img, x, y, w, h, offsetX, offsetY) {
// more code than displayed here
ctx.drawImage(img, cx, cy, cw, ch, x, y, w, h);
}
onFileSelected(event) {
for (const file of event.target.files) {
if (file) {
const reader = new FileReader();
reader.onload = function(e: FileReaderEvent) {
const canvas = <HTMLCanvasElement>document.getElementById('canvas');
const ctx = canvas.getContext('2d');
const img = new Image;
img.onload = draw;
function draw() {
this.drawImageProp(ctx, this, 0, 0, canvas.width, canvas.height, 0.5, 0.5);
}
img.src = e.target.result;
};
reader.readAsDataURL(file);
}
}
}
Use a closure:
onFileSelected(event) {
const self = this;
for (const file of event.target.files) {
if (file) {
const reader = new FileReader();
reader.onload = function(e: FileReaderEvent) {
const canvas = <HTMLCanvasElement>document.getElementById('canvas');
const ctx = canvas.getContext('2d');
const img = new Image;
img.onload = draw;
function draw() {
self.drawImageProp(ctx, img, 0, 0, canvas.width, canvas.height, 0.5, 0.5);
}
img.src = e.target.result;
};
reader.readAsDataURL(file);
}
}
}

Javascript - Wait for array to finish populating

I am trying to get the value of some array elements. It works for the elements [0], [1], [2], [3], but not [4].
function getBase64() {
const urls = ['https://i.imgur.com/egNg7JU.jpg',
'https://i.imgur.com/RLZ7WH1.jpg', 'https://i.imgur.com/qfabBbA.jpg',
'https://i.imgur.com/Zuh1KaX.jpg', 'https://i.imgur.com/yD7X6Q1.jpg'
];
let base64urls = [];
const start = async () => {
await asyncForEach(urls, async (num) => {
await waitFor(50)
toDataURL(num, function(dataURL) {
base64urls.push(dataURL);
});
})
console.log(base64urls);
console.log(base64urls[4]);
}
start()
}
async function asyncForEach(array, callback) {
for (let index = 0; index < array.length; index++) {
await callback(array[index], index, array)
}
}
const waitFor = (ms) => new Promise(r => setTimeout(r, ms))
toDataURL simply returns the base64 value of an image. Whenever I try console.log(base64urls[4]), it returns 'undefined'. I do get the correct value for the previous elements. Is there some way to restructure this, or perhaps use a different method of waiting for the array to completely populate before checking for the values of its elements?
EDIT
Here is my toDataURL
function toDataURL(src, callback) {
const image = new Image();
image.crossOrigin = 'Anonymous';
image.onload = function () {
const canvas = document.createElement('canvas');
const context = canvas.getContext('2d');
canvas.height = this.naturalHeight;
canvas.width = this.naturalWidth;
context.drawImage(this, 0, 0);
const dataURL = canvas.toDataURL('image/jpeg');
callback(dataURL);
};
image.src = src;
}
It looks like toDataURL is asynchronous and callback-based - either change it so that it returns a Promise and await that Promise, or pass a Promise's resolve into the callback:
async function getBase64() {
const urls = ['https://i.imgur.com/egNg7JU.jpg',
'https://i.imgur.com/RLZ7WH1.jpg', 'https://i.imgur.com/qfabBbA.jpg',
'https://i.imgur.com/Zuh1KaX.jpg', 'https://i.imgur.com/yD7X6Q1.jpg'];
const base64urls = [];
for (const url of urls) {
const dataURL = await new Promise(resolve => toDataURL(url, resolve));
base64urls.push(dataURL);
}
console.log(base64urls);
console.log(base64urls[4]);
}
If you want to change your toDataURL function to return a Promise so you don't have to treat it like a callback:
function toDataURL(src) {
return new Promise(resolve => {
const image = new Image();
image.crossOrigin = 'Anonymous';
image.onload = function () {
const canvas = document.createElement('canvas');
const context = canvas.getContext('2d');
canvas.height = this.naturalHeight;
canvas.width = this.naturalWidth;
context.drawImage(this, 0, 0);
const dataURL = canvas.toDataURL('image/jpeg');
resolve(dataURL);
};
image.src = src;
});
}
and then const dataURL = await toDataURL(url)
You can use promise.all for this kind of situation to wait for the results of your queries
const urls = ['https://i.imgur.com/egNg7JU.jpg',
'https://i.imgur.com/RLZ7WH1.jpg', 'https://i.imgur.com/qfabBbA.jpg',
'https://i.imgur.com/Zuh1KaX.jpg', 'https://i.imgur.com/yD7X6Q1.jpg'];
let base64urls = [];
Promise.all(urls.map(url => fetch(url))).then(res => toBase64DataURL(res)).then(result => {base64urls.push(result.toDataURL());
console.log(base64urls);});
function toBase64DataURL(src) {
return new Promise(resolve => {
const image = new Image();
image.crossOrigin = 'Anonymous';
image.onload = _=> {
const canvas = document.createElement('canvas');
const context = canvas.getContext('2d');
canvas.height = this.naturalHeight;
canvas.width = this.naturalWidth;
context.drawImage(this, 0, 0);
const dataURL = canvas.toDataURL('image/jpeg');
resolve(dataURL);
};
image.src = src;
});
}

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