|Introduction | Supported_Platforms | Installation_Steps | Plugin_Usage | Working_Examples | More_about_us!|
|:---:|:------:|:---:|:---:|:---:|:---:|

> BREAKING CHANGES introduced in plugin version 2.0.0 and 3.0.0. Older version will run as expected!
> In 2.x.x returnType input was removed!
> In 3.x.x if no text was found in the image, the success callback will be called instead of the error callback along with a new key foundText with boolean value. Please see example objects at the very end for more explanation.

> DOCUMENTATION here applies only to plugin ver 3.x.x! The respective documentation of each of the versions is available with the npm release

cordova-plugin-mobile-ocr 

> This plugin was made possible because of google mobile vision text recognition API. The supported languages are listed in the link. This plugin is absolutely free and will work offline once install is complete. All required files required for Text Recognition are downloaded during install if necessary space is available.

This plugin defines a global textocr object, which provides an method that accepts image uri or base64 inputs. If some text was detected in the image, this text will be returned as a string. The imageuri or base64 can be send to the plugin using any another plugin like cordova-plugin-camera or cordova-plugin-document-scanner. Although the object is attached to the global scoped window, it is not available until after the deviceready event.

``
document.addEventListener("deviceready", onDeviceReady, false);
function onDeviceReady() {
console.log(textocr);
}
`

Supported Platforms

- Android
- iOS

Installation Steps

This requires cordova 7.1.0+ , cordova android 6.4.0+ and cordova ios 4.3.0+

npm link :- https://www.npmjs.com/package/cordova-plugin-mobile-ocr

cordova plugin add cordova-plugin-mobile-ocr

For Android that is all.

For iOS please also follow the steps below :-
- Once the iOS platform is added in command line, change directory to where podfile is found. Example location :- (myapp/platforms/ios).
- Make sure you have cocoapods installed then in command line do pod update.
- Now open myapp.xcworkspace which is usually found in the same directory as the podfile, then build and run.

Note :- if you use myapp.xcodeproj to build and run, it will not work and it will show a linker error.

Note :- if you manually create the podfile, please refer to issue #2

Plugin Usage

textocr.recText(sourceType, /returnType,/ uriOrBase, successCallback, errorCallback) //returnType no longer accepted from plugin version 2.x.x
- textocr.recText
The textocr.recText function accepts image data as uri or base64 and uses google mobile vision to recognize text and return the recognized text as string on its successcallback.

- sourceType
The sourceType parameter can take values 0,1,2,3 or 4 each of which are explained in detail in the table below. sourceType is an Int within the native code.

| sourceType | uriOrBase | Accuracy | Recommendation | Notes |
| :-------------: |:-------------:|:-------------:|:-------------: |:-------------: |
| 0 | NORMFILEURI | Very High | Recommended | On android this is same as NORMNATIVEURI |
| 1 | NORMNATIVEURI | Very High | Not Recommended (See note below) | On android this is same as NORMFILEURI |
| 2 | FASTFILEURI | Very Low | Not Recommended | On android this is same as FASTNATIVEURI. Compression allows for faster processing but sacrifices a lot of accuracy. Best used if ocr images will always be extremely large with large text in them. |
| 3 | FASTNATIVEURI | Very Low | Not Recommended | On android this is same as FASTFILEURI. Compression allows for faster processing but sacrifices a lot of accuracy. Best used if ocr images will always be extremely large with large text in them. |
| 4 | BASE64 | Very High | Not Recommended | Extremely memory intensive and thus not recommended

>Note :- NORMNATIVEURI & FASTNATIVEURI for iOS uses deprecated methods to access images. This is to support the camera plugin which still uses the deprecated methods to return native image URI's using ALAssetsLibrary. This plugin uses non deprecated PHAsset library whose deprecated method fetchAssets(withALAssetURLs:options:) is used to retrieve the image data.

- returnType
> Note :- This input is no longer accepted from plugin version 2.0.0 and above.


The returnType parameter can take values 0,1,2 or 3 each of which are explained in detail in the table below. If a wrong value is passed into this parameter it will default to 3 or ALL. See the image below the table to get a better understanding of BLOCKS, LINES and WORDS. Each of these (BLOCKS, LINES or WORDS) will contain the entire recognized text but they can be used for better formatting and thus are separated. ALL will contain all blocks first, followed by a new line character \n, followed by all lines, followed by another new line character \n, followed by all words. So using ALL will return duplicates. returnType is an Int within the native code.

| returnType | returnConst | Notes |
| :-------------:|:-------------:|:-----------:|
| 0 | BLOCKS | Detected blocks of text seperated by two new line \n characters.|
| 1 | LINES | Detected lines of text seperated by one new line \n character. |
| 2 | WORDS | Detected words in the text seperated by , and . A comma followed by a space. |
| 3 | ALL | ALL will contain all blocks first, followed by a new line character \n, followed by all lines, followed by another new line character \n, followed by all words. So using ALL will return duplicates. |

!N|Solid

- uriOrBase
The plugin accepts image uri or base64 data in uriOrBase which is obtained from another plugin like cordova-plugin-document-scanner or cordova-plugin-camera. This uriOrBase is then used by the plugin and via google mobile vision, it detects the text on the image. The data required for OCR is initially downloaded when the app is first installed.

> Example uriOrBase for NORMFILEURI or FASTFILEURI as obtained from camera plugin or scanner plugin :- file:///var/mobile/Containers/Data/Application/FF505EA5-F16E-4CBA-8F8B-76A219EDA407/tmp/cdv_photo_001.jpg

> Example uriOrBase for NORMNATIVEURI or FASTNATIVEURI as obtained from camera plugin. scanner plugin doesn't return this :- assets-library://asset/asset.JPG?id=EFBA7BCD-3031-4646-9874-49368849749A&ext=JPG

- successCallback
The return value is sent to the successCallback callback function, in string format if no errors occured.

- errorCallback
The errorCallback function returns Scan Failed: Found no text to scan if no text was detected on the image. It also return other messages based on the error conditions.

>Note :- After install the OCR App using this plugin does not need an internet connection for Optical Character Recognition since all the required data is downloaded locally on install.

You can do whatever you want with the string obtained from this plugin, for example:
- Render the image in an

tag.
-

nothing yet. wait

in html
- var element = document.getElementById('pp');
element.innerHTML=recognizedText; in js

> Note :- This plugin doesn't handle permissions as it only requires the URIs or Base64 data of images and thus expects the other plugins that provide it the URI or Base64 data to handle permissions.

Working Examples

Please use cordova plugin add cordova-plugin-camera or cordova plugin add cordova-plugin-document-scanner before using the following examples.

>Note :- The cordova-plugin-mobile-ocr plugin will not automatically download either of these plugins as dependencies (This is because this plugin can be used as standalone plugin which can accept URIs or Base64 data through any method or plugin).

Using cordova-plugin-camera
`js
navigator.camera.getPicture(onSuccess, onFail, { quality: 100, correctOrientation: true });

function onSuccess(imageData) {
textocr.recText(0, /3,/ imageData, onSuccess, onFail); // removed returnType (here 3) from version 2.0.0
// for sourceType Use 0,1,2,3 or 4
// for returnType Use 0,1,2 or 3 // 3 returns duplicates[see table]
function onSuccess(recognizedText) {
//var element = document.getElementById('pp');
//element.innerHTML=recognizedText;
//Use above two lines to show recognizedText in html
console.log(recognizedText);
alert(recognizedText);
}
function onFail(message) {
alert('Failed because: ' + message);
}
}
function onFail(message) {
alert('Failed because: ' + message);
}

`

Using cordova-plugin-document-scanner
>Note :- base64 and NATIVEURIs won't work with cordova-plugin-document-scanner plugin
`js

scan.scanDoc(successCallback, errorCallback, {sourceType : 1, fileName : "myfilename", quality : 1.0, returnBase64 : false});

function successCallback(imageURI) {
textocr.recText(0, /3,/ imageURI, onSuccess, onFail); // removed returnType (here 3) from version 2.0.0
// for sourceType Use 0,2 // 1,3,4 won't work
// for returnType Use 0,1,2 or 3 // 3 returns duplicates[see table]
function onSuccess(recognizedText) {
//var element = document.getElementById('pp');
//element.innerHTML=recognizedText;
//Use above two lines to show recognizedText in html
console.log(recognizedText);
alert(recognizedText);
}
function onFail(message) {
alert('Failed because: ' + message);
}
}
function errorCallback(message) {
alert('Failed because: ' + message);
}
`

More about us

Find out more or contact us directly here :- http://www.neutrinos.co/

Facebook :- https://www.facebook.com/Neutrinos.co/

LinkedIn :- https://www.linkedin.com/company/25057297/

Twitter :- https://twitter.com/Neutrinosco

Instagram :- https://www.instagram.com/neutrinos.co/


Example Objects

> For the cordova plugin 2.x.x the success callback will return this object

The five properties text, languages, confidence, points and frame are obtained as arrays and are associated with each other using the index of the array.

>For example :-
The text linetext[0] contains the languages linelanguages[0] and have a confidence of lineconfidence[0] with linepoints[0] and lineframe [0].

>Refer the examples to see how the points and frame are returned. Points hold four (x,y) point values that can be used to draw a box around each text. The Frame holds the origin x,y value, the height and the width of the rectangle that can be drawn around the text. The x,y value returned from the Frame property usually correspond to x1 and y4 of the Points property. The Points and Frame values can be used to obtain the placement of the text on the image

The basic structure of the object is as follows :-

> foundText was added in plugin version 3.0.0 and above. In earlier plugin versions if image did not contain text the error callback was called. From 3.0.0 onwards all success callbacks will contain the foundText key with a boolean value. Letting the user know if a text was present in the image. if foundText is false, text was not found and hence the blocks, lines, words keys won't be returned

- foundText - boolean value that is true if image contains text else false
- blocks
- blocktext - Array that contains each text block
- blocklanguages - Array of languages (Currently returns unusable values)
- blockconfidence - Array of confidence values (Currently return nil for on-Device text recognition)
- blockpoints - Array of objects of four points each that represent a block drawn around the text
- x1 - Key (Example to get x1 of the first text block :- recognizedText.blocks.blockpoints[0].x1)
- y1 - Key
- x2 - Key
- y2 - Key
- x3 - Key
- y3 - Key
- x4 - Key
- y4 - Key
- blockframe - Array of objects that contain origin point and size of the rectangle that holds text
- x - Key (Example to get x from blockframe of the first text block :- recognizedText.blocks.blockframe[0].x)
- y - Key
- height - Key
- width - Key
- lines
- linetext - Array that contains each text block
- linelanguages - Array of languages (Currently returns unusable values)
- lineconfidence - Array of confidence values (Currently return nil for on-Device text recognition)
- linepoints - Array of objects of four points each that represent a block drawn around the text
- x1 - Key
- y1 - Key
- x2 - Key
- y2 - Key
- x3 - Key
- y3 - Key
- x4 - Key
- y4 - Key
- lineframe - Array of objects that contain origin point and size of the rectangle that holds text
- x - Key
- y - Key
- height - Key
- width - Key
- words
- wordtext - Array that contains each text block
- wordlanguages - Array of languages (Currently returns unusable values)
- wordconfidence - Array of confidence values (Currently return nil for on-Device text recognition)
- wordpoints - Array of objects of four points each that represent a block drawn around the text
- x1 - Key
- y1 - Key
- x2 - Key
- y2 - Key
- x3 - Key
- y3 - Key
- x4 - Key
- y4 - Key
- wordframe - Array of objects that contain origin point and size of the rectangle that holds text
- x - Key
- y - Key
- height - Key
- width - Key


Example Object when no text in image


`json
{
"foundText" : false
}
`

iOS Example Object

`json
{
"foundText" : true,
"blocks": {
"blocklanguages": [
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]"
],
"blockpoints": [
{
"x3": "2338.143066",
"y1": "52.000000",
"x1": "2073.000000",
"y4": "656.654541",
"x4": "1972.193848",
"y2": "113.009895",
"x2": "2438.949219",
"y3": "717.664429"
},
{
"x3": "1204.772949",
"y1": "255.000000",
"x1": "942.000000",
"y4": "537.928284",
"x4": "865.838440",
"y2": "346.237946",
"x2": "1280.934570",
"y3": "629.166199"
},
{
"x3": "628.515869",
"y1": "1192.000000",
"x1": "398.000000",
"y4": "1452.757080",
"x4": "386.741180",
"y2": "1202.439209",
"x2": "639.774719",
"y3": "1463.196289"
},
{
"x3": "1787.353516",
"y1": "1257.000000",
"x1": "1495.000000",
"y4": "1482.905884",
"x4": "1488.478027",
"y2": "1265.628662",
"x2": "1793.875488",
"y3": "1491.534546"
},
{
"x3": "2804.546387",
"y1": "1267.000000",
"x1": "2495.000000",
"y4": "1547.713013",
"x4": "2468.088867",
"y2": "1299.255127",
"x2": "2831.457520",
"y3": "1579.968140"
},
{
"x3": "939.620850",
"y1": "2279.000000",
"x1": "587.000000",
"y4": "2548.592773",
"x4": "572.175903",
"y2": "2299.204590",
"x2": "954.444946",
"y3": "2568.797363"
},
{
"x3": "1968.580078",
"y1": "2307.000000",
"x1": "1776.000000",
"y4": "2534.936768",
"x4": "1770.634888",
"y2": "2311.659180",
"x2": "1973.945190",
"y3": "2539.595947"
},
{
"x3": "2982.085693",
"y1": "2334.000000",
"x1": "2793.000000",
"y4": "2544.980225",
"x4": "2790.103760",
"y2": "2336.635254",
"x2": "2984.981934",
"y3": "2547.615479"
},
{
"x3": "1426.792480",
"y1": "3287.000000",
"x1": "1072.000000",
"y4": "3611.215088",
"x4": "1037.933228",
"y2": "3327.859375",
"x2": "1460.859253",
"y3": "3652.074463"
},
{
"x3": "2455.617920",
"y1": "3346.000000",
"x1": "2255.000000",
"y4": "3559.973633",
"x4": "2251.643066",
"y2": "3349.199951",
"x2": "2458.974854",
"y3": "3563.173584"
}
],
"blocktext": [
"# 3",
"2",
"Q",
"W",
"E",
"A",
"S",
"D",
"Z",
"X"
],
"blockconfidence": [
null,
null,
null,
null,
null,
null,
null,
null,
null,
null
],
"blockframe": [
{
"y": "52.000000",
"x": "1972.000000",
"height": "666.000000",
"width": "467.000000"
},
{
"y": "255.000000",
"x": "865.000000",
"height": "375.000000",
"width": "416.000000"
},
{
"y": "1192.000000",
"x": "386.000000",
"height": "272.000000",
"width": "254.000000"
},
{
"y": "1257.000000",
"x": "1488.000000",
"height": "235.000000",
"width": "306.000000"
},
{
"y": "1267.000000",
"x": "2468.000000",
"height": "313.000000",
"width": "364.000000"
},
{
"y": "2279.000000",
"x": "572.000000",
"height": "290.000000",
"width": "383.000000"
},
{
"y": "2307.000000",
"x": "1770.000000",
"height": "233.000000",
"width": "204.000000"
},
{
"y": "2334.000000",
"x": "2790.000000",
"height": "214.000000",
"width": "195.000000"
},
{
"y": "3287.000000",
"x": "1037.000000",
"height": "366.000000",
"width": "424.000000"
},
{
"y": "3346.000000",
"x": "2251.000000",
"height": "218.000000",
"width": "208.000000"
}
]
},
"lines": {
"lineframe": [
{
"y": "53.000000",
"x": "2048.000000",
"height": "231.000000",
"width": "264.000000"
},
{
"y": "342.000000",
"x": "1979.000000",
"height": "369.000000",
"width": "405.000000"
},
{
"y": "255.000000",
"x": "865.000000",
"height": "375.000000",
"width": "416.000000"
},
{
"y": "1192.000000",
"x": "386.000000",
"height": "272.000000",
"width": "254.000000"
},
{
"y": "1257.000000",
"x": "1488.000000",
"height": "235.000000",
"width": "306.000000"
},
{
"y": "1267.000000",
"x": "2468.000000",
"height": "313.000000",
"width": "364.000000"
},
{
"y": "2279.000000",
"x": "572.000000",
"height": "290.000000",
"width": "383.000000"
},
{
"y": "2307.000000",
"x": "1770.000000",
"height": "233.000000",
"width": "204.000000"
},
{
"y": "2334.000000",
"x": "2790.000000",
"height": "214.000000",
"width": "195.000000"
},
{
"y": "3287.000000",
"x": "1037.000000",
"height": "366.000000",
"width": "424.000000"
},
{
"y": "3346.000000",
"x": "2251.000000",
"height": "218.000000",
"width": "208.000000"
}
],
"linelanguages": [
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]",
"[ \"\"]"
],
"lineconfidence": [
null,
null,
null,
null,
null,
null,
null,
null,
null,
null,
null
],
"linetext": [
"#",
"3",
"2",
"Q",
"W",
"E",
"A",
"S",
"D",
"Z",
"X"
],
"linepoints": [
{
"x3": "2279.747070",
"y1": "53.000000",
"x1": "2081.000000",
"y4": "245.345245",
"x4": "2048.932861",
"y2": "91.480637",
"x2": "2311.814209",
"y3": "283.825897"
},
{
"x3": "2295.458252",
"y1": "342.000000",
"x1": "2067.000000",
"y4": "605.842957",
"x4": "1979.416382",
"y2": "446.911316",
"x2": "2383.041992",
"y3": "710.754272"
},
{
"x3": "1204.772949",
"y1": "255.000000",
"x1": "942.000000",
"y4": "537.928284",
"x4": "865.838440",
"y2": "346.237946",
"x2": "1280.934570",
"y3": "629.166199"
},
{
"x3": "628.515869",
"y1": "1192.000000",
"x1": "398.000000",
"y4": "1452.757080",
"x4": "386.741180",
"y2": "1202.439209",
"x2": "639.774719",
"y3": "1463.196289"
},
{
"x3": "1787.353516",
"y1": "1257.000000",
"x1": "1495.000000",
"y4": "1482.905884",
"x4": "1488.478027",
"y2": "1265.628662",
"x2": "1793.875488",
"y3": "1491.534546"
},
{
"x3": "2804.546387",
"y1": "1267.000000",
"x1": "2495.000000",
"y4": "1547.713013",
"x4": "2468.088867",
"y2": "1299.255127",
"x2": "2831.457520",
"y3": "1579.968140"
},
{
"x3": "939.620850",
"y1": "2279.000000",
"x1": "587.000000",
"y4": "2548.592773",
"x4": "572.175903",
"y2": "2299.204590",
"x2": "954.444946",
"y3": "2568.797363"
},
{
"x3": "1968.580078",
"y1": "2307.000000",
"x1": "1776.000000",
"y4": "2534.936768",
"x4": "1770.634888",
"y2": "2311.659180",
"x2": "1973.945190",
"y3": "2539.595947"
},
{
"x3": "2982.085693",
"y1": "2334.000000",
"x1": "2793.000000",
"y4": "2544.980225",
"x4": "2790.103760",
"y2": "2336.635254",
"x2": "2984.981934",
"y3": "2547.615479"
},
{
"x3": "1426.792480",
"y1": "3287.000000",
"x1": "1072.000000",
"y4": "3611.215088",
"x4": "1037.933228",
"y2": "3327.859375",
"x2": "1460.859253",
"y3": "3652.074463"
},
{
"x3": "2455.617920",
"y1": "3346.000000",
"x1": "2255.000000",
"y4": "3559.973633",
"x4": "2251.643066",
"y2": "3349.199951",
"x2": "2458.974854",
"y3": "3563.173584"
}
]
},
"words": {
"wordtext": [
"#",
"3",
"2",
"Q",
"W",
"E",
"A",
"S",
"D",
"Z",
"X"
],
"wordlanguages": [
"[]",
"[]",
"[]",
"[]",
"[]",
"[]",
"[]",
"[]",
"[]",
"[]",
"[]"
],
"wordpoints": [
{
"x3": "2279.747070",
"y1": "53.000000",
"x1": "2081.000000",
"y4": "245.345245",
"x4": "2048.932861",
"y2": "91.480637",
"x2": "2311.814209",
"y3": "283.825897"
},
{
"x3": "2295.458252",
"y1": "342.000000",
"x1": "2067.000000",
"y4": "605.842957",
"x4": "1979.416382",
"y2": "446.911316",
"x2": "2383.041992",
"y3": "710.754272"
},
{
"x3": "1204.772949",
"y1": "255.000000",
"x1": "942.000000",
"y4": "537.928284",
"x4": "865.838440",
"y2": "346.237946",
"x2": "1280.934570",
"y3": "629.166199"
},
{
"x3": "628.515869",
"y1": "1192.000000",
"x1": "398.000000",
"y4": "1452.757080",
"x4": "386.741180",
"y2": "1202.439209",
"x2": "639.774719",
"y3": "1463.196289"
},
{
"x3": "1787.353516",
"y1": "1257.000000",
"x1": "1495.000000",
"y4": "1482.905884",
"x4": "1488.478027",
"y2": "1265.628662",
"x2": "1793.875488",
"y3": "1491.534546"
},
{
"x3": "2804.546387",
"y1": "1267.000000",
"x1": "2495.000000",
"y4": "1547.713013",
"x4": "2468.088867",
"y2": "1299.255127",
"x2": "2831.457520",
"y3": "1579.968140"
},
{
"x3": "939.620850",
"y1": "2279.000000",
"x1": "587.000000",
"y4": "2548.592773",
"x4": "572.175903",
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``