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Added basic OCR text extraction
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MShwed committed Sep 4, 2019
1 parent c6de3eb commit f1659af
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79 changes: 70 additions & 9 deletions package-lock.json

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1 change: 1 addition & 0 deletions package.json
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"sortablejs": "^1.9.0",
"split.js": "^1.5.11",
"ssdeep.js": "0.0.2",
"tesseract.js": "^2.0.0-alpha.15",
"ua-parser-js": "^0.7.20",
"utf8": "^3.0.0",
"vkbeautify": "^0.99.3",
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3 changes: 2 additions & 1 deletion src/core/config/Categories.json
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Expand Up @@ -403,7 +403,8 @@
"Hex Density chart",
"Scatter chart",
"Series chart",
"Heatmap chart"
"Heatmap chart",
"OCR"
]
},
{
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87 changes: 87 additions & 0 deletions src/core/operations/OCR.mjs
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/**
* @author mshwed [[email protected]]
* @copyright Crown Copyright 2019
* @license Apache-2.0
*/

import Operation from "../Operation.mjs";
import OperationError from "../errors/OperationError.mjs";
import { isImage } from "../lib/FileType.mjs";
import { isWorkerEnvironment } from "../Utils.mjs";

import jimp from "jimp";
import Tesseract from "tesseract.js";
const { TesseractWorker } = Tesseract;

/**
* OCR operation
*/
class OCR extends Operation {

/**
* OCR constructor
*/
constructor() {
super();

this.name = "OCR";
this.module = "Default";
this.description = "Optical character recognition or optical character reader (OCR) is the mechanical or electronic conversion of images of typed, handwritten or printed text into machine-encoded text.";
this.infoURL = "https://en.wikipedia.org/wiki/Optical_character_recognition";
this.inputType = "ArrayBuffer";
this.outputType = "string";
this.args = [
/* Example arguments. See the project wiki for full details.
{
name: "First arg",
type: "string",
value: "Don't Panic"
},
{
name: "Second arg",
type: "number",
value: 42
}
*/
];
}

/**
* @param {ArrayBuffer} input
* @param {Object[]} args
* @returns {Object}
*/
async run(input, args) {
if (!isImage(input)) {
throw new OperationError("Invalid File Type");
}

try {
if (isWorkerEnvironment())
self.sendStatusMessage("Performing OCR on image...");

let image;
try {
image = await jimp.read(input);
image = await image.getBase64Async(jimp.AUTO);
} catch (err) {
throw new OperationError(`Error loading image. (${err})`);
}

const worker = new TesseractWorker();

const result = await worker.recognize(image)
.progress(progress => {
if (isWorkerEnvironment()) self.sendStatusMessage(`${progress.status} - ${parseFloat(progress.progress).toFixed(2)}%`);
});

console.log(result);

return result.text;
} catch (err) {
throw new OperationError(`Error performing OCR on image. (${err})`);
}
}
}

export default OCR;

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