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React component performing border detection, perspective correction and simple image filters over a provided image ๐Ÿ“ฒ ๐Ÿ“ธ

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react-perspective-cropper

React component performing border detection, perspective correction and simple image filters over a provided image ๐Ÿ“ฒ ๐Ÿ“ธ

NPM JavaScript Style Guide

Intro

react-perspective-cropper doesn't, yet, do live borders recognition like some famous mobile apps.
Though it exports a main <Cropper /> component which given an image it renders a cropper component with an already applied but editable crop area.
You must pass an img through the src prop otherwise the component won't be rendered. Using its ref you have:

  • a done async method that you can call and it will return the cropped and filtered image and you have the option to also show a preview of the edited image!
  • a backToCrop method to use only if you requested for a preview in the done.

If you have special needs, please open a issue and we'll discuss it there!

demo gif

Install

npm i react-perspective-cropper

or

yarn add react-perspective-cropper

Props

export interface CropperProps {
  image: string | File
  onDragStop: () => void
  onChange: () => void
  cropperRef: React.ElementRef
  pointSize: number
  lineWidth: number
  pointBgColor: string
  pointBorder: string // css border property value
  lineColor: string
  maxWidth: number
  maxHeight: number
  openCvPath: string
}

filterCvParams Property

The filterCvParams property allows you get bit more control over the cropping and filtering in react-perspective-cropper.

Usage

filterCvParams: {
    blur: false,                         // Applies a Gaussian blur to the image.
    th: true,                            // Applies adaptive thresholding to the image.
    thMode: cv.ADAPTIVE_THRESH_MEAN_C,   // Determines the method used for adaptive thresholding.
    thMeanCorrection: 15,                // Adjusts the mean for thresholding.
    thBlockSize: 25,                     // Determines the size of the block for adaptive thresholding.
    thMax: 255,                          // Sets the maximum value for thresholding.
    grayScale: true                      // Converts the image to grayscale.
}


// Configuration for image processing that can be passed to the function.
const filterParams = { preview: false, filterCvParams};

// Pass the filterParams configuration to the `cropperRef.current.done()` function.
const res = await cropperRef.current.done(filterParams);

Usage

import React from 'react'
import Cropper from 'react-perspective-cropper'

const App = () => {
  const [cropState, setCropState] = useState()
  const [img, setImg] = useState()
  const [inputKey, setInputKey] = useState(0)
  const cropperRef = useRef()

  const onDragStop = useCallback((s) => setCropState(s), [])
  const onChange = useCallback((s) => setCropState(s), [])

  const doSomething = async () => {
    console.log(cropState)
    try {
      const res = await cropperRef.current.done({ preview: true })
      console.log(res)
    } catch (e) {
      console.log('error', e)
    }
  }

  const onImgSelection = async (e) => {
    if (e.target.files && e.target.files.length > 0) {
      // it can also be a http or base64 string for example
      setImg(e.target.files[0])
    }
  }

  return (
    <Cropper
      ref={cropperRef}
      image={img}
      onChange={onChange}
      onDragStop={onDragStop}
    />
    <input
      type='file'
      key={inputKey}
      onChange={onImgSelection}
      accept='image/*'
    />
    <button onClick={doSomething}>Ho finito</button>
  )
}

OpenCV

This cropper uses OpenCV for border recognition, perspective transformation and b&w thresholding. In order to use it, I've created this other handy wrapper around it: opencv-react
If you're already using it or if you're importing OpenCV manually in a different way, this lib got you covered as long as you provide the OpenCV instance in window.cv and the component isn't rendered before OpenCV finished loading.
So, be careful.

OpenCV async loading

The openCV library is really big (approx. 1mb for the entire js file).
Now, opencv-react uses the document.createElement('script') browser function to inject this script and that's equal to writing <script src="..."></script> in your html page. The parsing of the js file from the browser is done synchronously and we don't want this since it'd block the js thread.
The solution, which is already implemented in the opencv-react lib, is to use the keyword async in front of the script tag. This won't block the thread but still you gotta decide when to load it.

Basically I can imagine many, if not all, of you will render this component under certain conditions; well you need to know that doing so you'll start fetching and asynchronously parsing the library only when you'll render this cropper component.
If you wanna start fetching the lib as soon as your app is opened, then you want to wrap your entire app with the opencv-react provider and then render the component whenever you want. The cropper will surely start faster, straight away.

OpenCV locally or from CDN

You might be asking yourself this question. Well, openCV or not, the answer doesn't differ based on the libs you need in your project.
Always fewer js devs import stuff from cdns nowadays (think about npm i). If you notice the example folder the lib is loaded locally.
But this lib doesn't decide this on your behalf. Do what you think is best :)

Nice to have

It would be nice to have a react-doc-scan component which uses a webcam featuring live borders recognition.

Inspiration and help

Huge thanks to ngx-document-scanner which served me quite some openCV and canvas code to use.

License

MIT ยฉ giacomocerquone

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React component performing border detection, perspective correction and simple image filters over a provided image ๐Ÿ“ฒ ๐Ÿ“ธ

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