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Supports the web, NodeJS, React, and others.
Available on npm or via cdn
## Quickstart
> **Developers Note**: you can now use the [jscanify debugging tool](https://colonelparrot.github.io/jscanify/tester.html) to observe the result (highlighting, extraction) on test images.
### Import
npm:
```js
$ npm i jscanify
import jscanify from 'jscanify'
```
cdn:
```html
```
> **Note**: jscanify on NodeJS is slightly different. See [wiki: use on NodeJS](https://github.com/ColonelParrot/jscanify/wiki#use-on-nodejs).
### Highlight Paper in Image
```html
```
```js
const scanner = new jscanify();
image.onload = function () {
const highlightedCanvas = scanner.highlightPaper(image);
document.body.appendChild(highlightedCanvas);
};
```
### Extract Paper
```js
const scanner = new jscanify();
const paperWidth = 500;
const paperHeight = 1000;
image.onload = function () {
const resultCanvas = scanner.extractPaper(image, paperWidth, paperHeight);
document.body.appendChild(resultCanvas);
};
```
### Highlighting Paper in User Camera
The following code continuously reads from the user's camera and highlights the paper:
```html
```
```js
const scanner = new jscanify();
const canvasCtx = canvas.getContext("2d");
const resultCtx = result.getContext("2d");
navigator.mediaDevices.getUserMedia({ video: true }).then((stream) => {
video.srcObject = stream;
video.onloadedmetadata = () => {
video.play();
setInterval(() => {
canvasCtx.drawImage(video, 0, 0);
const resultCanvas = scanner.highlightPaper(canvas);
resultCtx.drawImage(resultCanvas, 0, 0);
}, 10);
};
});
```
To export the paper to a PDF, see [here](https://stackoverflow.com/questions/23681325/convert-canvas-to-pdf)
### Notes
- for optimal paper detection, the paper should be placed on a flat surface with a solid background color
- we recommend wrapping your code using `jscanify` in a window `load` event listener to ensure OpenCV is loaded