mirror of
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123 lines
3.8 KiB
Markdown
123 lines
3.8 KiB
Markdown
<p align="center">
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<img src="docs/images/logo-github.png" height="150">
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</p>
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<p align="center">
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<a href="https://www.jsdelivr.com/package/gh/ColonelParrot/jscanify"><img src="https://data.jsdelivr.com/v1/package/gh/ColonelParrot/jscanify/badge"></a>
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<a href="https://cdnjs.com/libraries/jscanify"><img src="https://img.shields.io/cdnjs/v/jscanify"></a>
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<a href="https://npmjs.com/package/jscanify"><img src="https://badgen.net/npm/dw/jscanify"></a>
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<br />
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<a href="https://github.com/puffinsoft/jscanify/blob/master/LICENSE"><img src="https://img.shields.io/github/license/puffinsoft/jscanify.svg"></a>
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<a href="https://npmjs.com/package/jscanify"><img src="https://badgen.net/npm/v/jscanify"></a>
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</p>
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<p align="center">
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<a href="https://nodei.co/npm/jscanify/"><img src="https://nodei.co/npm/jscanify.png"></a>
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</p>
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<p align="center">
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Powered with <a href="https://docs.opencv.org/3.4/d5/d10/tutorial_js_root.html">opencv.js</a><br/>
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Supports the web, NodeJS, <a href="https://github.com/ColonelParrot/react-scanify-demo">React</a>, and others.
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<br/>
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Available on <a href="https://www.npmjs.com/package/jscanify">npm</a> or via <a href="https://www.jsdelivr.com/package/gh/ColonelParrot/jscanify">cdn</a><br/>
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</p>
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**Features**:
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- paper detection & highlighting
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- paper scanning with distortion correction
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<br/>
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- 🆕 glare suppression
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- 🆕 multi-colored paper support
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<hr />
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<img src="docs/images/github-explanation-long.png" />
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<hr/>
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## Quickstart
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> **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.
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### Import
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npm:
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```js
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$ npm i jscanify
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import jscanify from 'jscanify'
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```
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cdn:
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```html
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<script src="https://docs.opencv.org/4.7.0/opencv.js" async></script>
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<!-- warning: loading OpenCV can take some time. Load asynchronously -->
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<script src="https://cdn.jsdelivr.net/gh/ColonelParrot/jscanify@master/src/jscanify.min.js"></script>
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```
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> **Note**: jscanify on NodeJS is slightly different. See [wiki: use on NodeJS](https://github.com/ColonelParrot/jscanify/wiki#use-on-nodejs).
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### Highlight Paper in Image
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```html
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<img src="/path/to/your/image.png" id="image" />
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```
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```js
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const scanner = new jscanify();
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image.onload = function () {
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const highlightedCanvas = scanner.highlightPaper(image);
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document.body.appendChild(highlightedCanvas);
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};
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```
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### Extract Paper
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```js
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const scanner = new jscanify();
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const paperWidth = 500;
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const paperHeight = 1000;
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image.onload = function () {
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const resultCanvas = scanner.extractPaper(image, paperWidth, paperHeight);
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document.body.appendChild(resultCanvas);
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};
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```
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### Highlighting Paper in User Camera
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The following code continuously reads from the user's camera and highlights the paper:
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```html
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<video id="video"></video> <canvas id="canvas"></canvas>
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<!-- original video -->
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<canvas id="result"></canvas>
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<!-- highlighted video -->
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```
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```js
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const scanner = new jscanify();
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const canvasCtx = canvas.getContext("2d");
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const resultCtx = result.getContext("2d");
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navigator.mediaDevices.getUserMedia({ video: true }).then((stream) => {
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video.srcObject = stream;
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video.onloadedmetadata = () => {
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video.play();
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setInterval(() => {
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canvasCtx.drawImage(video, 0, 0);
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const resultCanvas = scanner.highlightPaper(canvas);
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resultCtx.drawImage(resultCanvas, 0, 0);
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}, 10);
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};
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});
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```
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To export the paper to a PDF, see [here](https://stackoverflow.com/questions/23681325/convert-canvas-to-pdf)
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### Notes
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- for optimal paper detection, the paper should be placed on a flat surface with a solid background color
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- we recommend wrapping your code using `jscanify` in a window `load` event listener to ensure OpenCV is loaded
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