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(Node.js) Amazon Rekognition - Detect Text in an Image
Detects text in the input image and converts it into machine-readable text. This example passes theimage as base64-encoded image bytes.For more information, see https://docs.aws.amazon.com/rekognition/latest/dg/API_DetectText.html
var os = require('os');
if (os.platform() == 'win32') {
var chilkat = require('@chilkat/ck-node23-win64');
} else if (os.platform() == 'linux') {
if (os.arch() == 'arm') {
var chilkat = require('@chilkat/ck-node23-linux-arm');
} else if (os.arch() == 'arm64') {
var chilkat = require('@chilkat/ck-node23-linux-arm64');
} else {
var chilkat = require('@chilkat/ck-node23-linux-x64');
}
} else if (os.platform() == 'darwin') {
var chilkat = require('@chilkat/ck-node23-mac-universal');
}
function chilkatExample() {
var rest = new chilkat.Rest();
var success;
var authAws = new chilkat.AuthAws();
authAws.AccessKey = "AWS_ACCESS_KEY";
authAws.SecretKey = "AWS_SECRET_KEY";
// Don't forget to change the region to your particular region. (Also make the same change in the call to Connect below.)
authAws.Region = "us-west-2";
authAws.ServiceName = "rekognition";
// SetAuthAws causes Chilkat to automatically add the following headers: Authorization, X-Amz-Date
rest.SetAuthAws(authAws);
// URL: https://rekognition.us-west-2.amazonaws.com/
var bTls = true;
var port = 443;
var bAutoReconnect = true;
// Don't forget to change the region domain (us-west-2.amazonaws.com) to your particular region.
success = rest.Connect("rekognition.us-west-2.amazonaws.com",port,bTls,bAutoReconnect);
if (success !== true) {
console.log("ConnectFailReason: " + rest.ConnectFailReason);
console.log(rest.LastErrorText);
return;
}
// Note: The above code does not need to be repeatedly called for each REST request.
// The rest object can be setup once, and then many requests can be sent. Chilkat will automatically
// reconnect within a FullRequest* method as needed. It is only the very first connection that is explicitly
// made via the Connect method.
// Load the JPG to be passed as base64 in the JSON.
var bdJpg = new chilkat.BinData();
success = bdJpg.LoadFile("qa_data/jpg/monday_keep_smiling.jpg");
if (success !== true) {
console.log("Failed to load the input JPG file.");
return;
}
// We wish to send the following JSON in the body of our HTTP request:
// {
// "Image": {
// "Bytes": "base64_image_bytes"
// }
// }
// Here is the image we used for testing:
// Convert binary image bytes to base64.
// Note: We are explicitly keeping the data inside Chilkat to avoid having to pass large strings
// as arguments to function calls. This is important for some programming languages.
var sbJpg = new chilkat.StringBuilder();
bdJpg.GetEncodedSb("base64",sbJpg);
var json = new chilkat.JsonObject();
json.UpdateSb("Image.Bytes",sbJpg);
rest.AddHeader("Content-Type","application/x-amz-json-1.1");
rest.AddHeader("X-Amz-Target","RekognitionService.DetectText");
var sbRequestBody = new chilkat.StringBuilder();
json.EmitSb(sbRequestBody);
var sbResponseBody = new chilkat.StringBuilder();
success = rest.FullRequestSb("POST","/",sbRequestBody,sbResponseBody);
if (success !== true) {
console.log(rest.LastErrorText);
return;
}
var respStatusCode = rest.ResponseStatusCode;
console.log("response status code = " + respStatusCode);
if (respStatusCode >= 400) {
console.log("Response Status Code = " + respStatusCode);
console.log("Response Header:");
console.log(rest.ResponseHeader);
console.log("Response Body:");
console.log(sbResponseBody.GetAsString());
return;
}
var jResp = new chilkat.JsonObject();
jResp.LoadSb(sbResponseBody);
jResp.EmitCompact = false;
console.log(jResp.Emit());
// Sample JSON response:
// (Sample code for parsing the JSON response is shown below)
// {
// "TextDetections": [
// {
// "Confidence": 95.99308776855469,
// "DetectedText": "( MONDAY IT'S",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.6399821043014526,
// "Left": 0.219133198261261,
// "Top": 0.08677978068590164,
// "Width": 0.7433173656463623
// },
// "Polygon": [
// {
// "X": 0.219133198261261,
// "Y": 0.3588336706161499
// },
// {
// "X": 0.8984103798866272,
// "Y": 0.08677978068590164
// },
// {
// "X": 0.9624505639076233,
// "Y": 0.4547080099582672
// },
// {
// "X": 0.2831733524799347,
// "Y": 0.7267619371414185
// }
// ]
// },
// "Id": 0,
// "Type": "LINE"
// },
// {
// "Confidence": 99.70352172851562,
// "DetectedText": "but keep",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.09703556448221207,
// "Left": 0.6335319876670837,
// "Top": 0.5153074264526367,
// "Width": 0.21070890128612518
// },
// "Polygon": [
// {
// "X": 0.6355597376823425,
// "Y": 0.5153074264526367
// },
// {
// "X": 0.8442409038543701,
// "Y": 0.5266726613044739
// },
// {
// "X": 0.8422132134437561,
// "Y": 0.6123430132865906
// },
// {
// "X": 0.6335319876670837,
// "Y": 0.6009777784347534
// }
// ]
// },
// "Id": 1,
// "Type": "LINE"
// },
// {
// "Confidence": 99.92333984375,
// "DetectedText": "Smiling",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.31578224897384644,
// "Left": 0.5070608258247375,
// "Top": 0.6086956262588501,
// "Width": 0.4795433282852173
// },
// "Polygon": [
// {
// "X": 0.5070608258247375,
// "Y": 0.6298336386680603
// },
// {
// "X": 0.9808917045593262,
// "Y": 0.6086956262588501
// },
// {
// "X": 0.9866041541099548,
// "Y": 0.9033399224281311
// },
// {
// "X": 0.5127732157707214,
// "Y": 0.9244779348373413
// }
// ]
// },
// "Id": 2,
// "Type": "LINE"
// },
// {
// "Confidence": 99.77294158935547,
// "DetectedText": "IT'S",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.09903381764888763,
// "Left": 0.668789803981781,
// "Top": 0.17874395847320557,
// "Width": 0.1449044644832611
// },
// "Polygon": [
// {
// "X": 0.668789803981781,
// "Y": 0.17874395847320557
// },
// {
// "X": 0.8136942386627197,
// "Y": 0.17874395847320557
// },
// {
// "X": 0.8136942386627197,
// "Y": 0.2777777910232544
// },
// {
// "X": 0.668789803981781,
// "Y": 0.2777777910232544
// }
// ]
// },
// "Id": 5,
// "ParentId": 0,
// "Type": "WORD"
// },
// {
// "Confidence": 98.44307708740234,
// "DetectedText": "MONDAY",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.11112251877784729,
// "Left": 0.5541401505470276,
// "Top": 0.3526569902896881,
// "Width": 0.39013487100601196
// },
// "Polygon": [
// {
// "X": 0.5541401505470276,
// "Y": 0.3526569902896881
// },
// {
// "X": 0.9442675113677979,
// "Y": 0.3502415418624878
// },
// {
// "X": 0.9458598494529724,
// "Y": 0.4613526463508606
// },
// {
// "X": 0.5541401505470276,
// "Y": 0.4637681245803833
// }
// ]
// },
// "Id": 4,
// "ParentId": 0,
// "Type": "WORD"
// },
// {
// "Confidence": 99.61898803710938,
// "DetectedText": "but",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.06521739065647125,
// "Left": 0.6353503465652466,
// "Top": 0.5241546034812927,
// "Width": 0.0843949019908905
// },
// "Polygon": [
// {
// "X": 0.6353503465652466,
// "Y": 0.5241546034812927
// },
// {
// "X": 0.7197452187538147,
// "Y": 0.5241546034812927
// },
// {
// "X": 0.7197452187538147,
// "Y": 0.5893719792366028
// },
// {
// "X": 0.6353503465652466,
// "Y": 0.5893719792366028
// }
// ]
// },
// "Id": 6,
// "ParentId": 1,
// "Type": "WORD"
// },
// {
// "Confidence": 99.78804779052734,
// "DetectedText": "keep",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.07971014827489853,
// "Left": 0.7308917045593262,
// "Top": 0.5265700221061707,
// "Width": 0.1114649698138237
// },
// "Polygon": [
// {
// "X": 0.7308917045593262,
// "Y": 0.5265700221061707
// },
// {
// "X": 0.8423566818237305,
// "Y": 0.5265700221061707
// },
// {
// "X": 0.8423566818237305,
// "Y": 0.6062802076339722
// },
// {
// "X": 0.7308917045593262,
// "Y": 0.6062802076339722
// }
// ]
// },
// "Id": 7,
// "ParentId": 1,
// "Type": "WORD"
// },
// {
// "Confidence": 89.76324462890625,
// "DetectedText": "(",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.16401274502277374,
// "Left": 0.27229300141334534,
// "Top": 0.6642512083053589,
// "Width": 0.2850286066532135
// },
// "Polygon": [
// {
// "X": 0.27229300141334534,
// "Y": 0.6642512083053589
// },
// {
// "X": 0.2707006335258484,
// "Y": 0.37922704219818115
// },
// {
// "X": 0.43471336364746094,
// "Y": 0.37922704219818115
// },
// {
// "X": 0.4363057315349579,
// "Y": 0.6642512083053589
// }
// ]
// },
// "Id": 3,
// "ParentId": 0,
// "Type": "WORD"
// },
// {
// "Confidence": 99.92333984375,
// "DetectedText": "Smiling",
// "Geometry": {
// "BoundingBox": {
// "Height": 0.294724702835083,
// "Left": 0.5079618096351624,
// "Top": 0.6304348111152649,
// "Width": 0.4734293222427368
// },
// "Polygon": [
// {
// "X": 0.5079618096351624,
// "Y": 0.6304348111152649
// },
// {
// "X": 0.9808917045593262,
// "Y": 0.6086956262588501
// },
// {
// "X": 0.9856687784194946,
// "Y": 0.9033816456794739
// },
// {
// "X": 0.512738823890686,
// "Y": 0.9227052927017212
// }
// ]
// },
// "Id": 8,
// "ParentId": 2,
// "Type": "WORD"
// }
// ],
// "TextModelVersion": "3.0"
// }
//
//
// Sample code for parsing the JSON response...
// Use the following online tool to generate parsing code from sample JSON:
// Generate Parsing Code from JSON
var Confidence;
var DetectedText;
var GeometryBoundingBoxHeight;
var GeometryBoundingBoxLeft;
var GeometryBoundingBoxTop;
var GeometryBoundingBoxWidth;
var Id;
var v_Type;
var ParentId;
var j;
var count_j;
var X;
var Y;
var TextModelVersion = jResp.StringOf("TextModelVersion");
var i = 0;
var count_i = jResp.SizeOfArray("TextDetections");
while (i < count_i) {
jResp.I = i;
Confidence = jResp.StringOf("TextDetections[i].Confidence");
DetectedText = jResp.StringOf("TextDetections[i].DetectedText");
GeometryBoundingBoxHeight = jResp.StringOf("TextDetections[i].Geometry.BoundingBox.Height");
GeometryBoundingBoxLeft = jResp.StringOf("TextDetections[i].Geometry.BoundingBox.Left");
GeometryBoundingBoxTop = jResp.StringOf("TextDetections[i].Geometry.BoundingBox.Top");
GeometryBoundingBoxWidth = jResp.StringOf("TextDetections[i].Geometry.BoundingBox.Width");
Id = jResp.IntOf("TextDetections[i].Id");
v_Type = jResp.StringOf("TextDetections[i].Type");
ParentId = jResp.IntOf("TextDetections[i].ParentId");
j = 0;
count_j = jResp.SizeOfArray("TextDetections[i].Geometry.Polygon");
while (j < count_j) {
jResp.J = j;
X = jResp.StringOf("TextDetections[i].Geometry.Polygon[j].X");
Y = jResp.StringOf("TextDetections[i].Geometry.Polygon[j].Y");
j = j+1;
}
i = i+1;
}
}
chilkatExample();
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