api-builder-plugin-rekognition
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Axway API Builder flow-node that implements AWS Rekognition for image Analysis : api-builder-plugin-rekognition.
Methods implemented:
Flow-nodes are used within Axway API Builder's flow editor that is a low-code / no-code solution to designing and developing services that integrate to many different connected components, such as databases and APIs.
After creating your API Builder Project, you can install this plugin using npm:
npm install api-builder-plugin-rekognition
Note that this command will install from npm. If you want to install locally, then provide the full path to the plugin folder
Before launching your API Builder app that uses this plugin, you must set the following two environment variables as per the AWS SDK for JavaScript online docs:
You should also add the following to the /conf/default.js file in order to overcome the 1MB default limit on POST data:
bodyParser: {
limit: '5mb'
},
Note that 5mb is just an example. You can set it to the value that meets your needs based on the image size
Find the plugin in the AI group in the Flow-Nodes panel. Drag onto the canvas and select the desired method and provide the input string (Image as a Base64 encoded string) and wire up to the rest of your flow as shown below:
Images (JPEG or PNG) need to be provided as Base64 encoded strings. You can find many Base64 encoders online such as this one.
The currently implemented methods are described below.
AWS docs are here
Provide the Image input as a Base64 encoded string and the output will be similar to below:
Image = Base64 encoded version of the following image:
{
"Labels": [
{
"Name": "Car",
"Confidence": 98.41893005371094,
"Instances": [
{
"BoundingBox": {
"Width": 0.9095886945724487,
"Height": 0.4260041415691376,
"Left": 0.044332683086395264,
"Top": 0.37117668986320496
},
"Confidence": 98.41893005371094
}
],
"Parents": [
{
"Name": "Vehicle"
},
{
"Name": "Transportation"
}
]
},
{
"Name": "Automobile",
"Confidence": 98.41893005371094,
"Instances": [],
"Parents": [
{
"Name": "Vehicle"
},
{
"Name": "Transportation"
}
]
},
.
.
.
{
"Name": "Jaguar Car",
"Confidence": 57.534969329833984,
"Instances": [],
"Parents": [
{
"Name": "Car"
},
{
"Name": "Vehicle"
},
{
"Name": "Transportation"
}
]
}
],
"LabelModelVersion": "2.0"
}
AWS docs are here
Provide the Image input as a Base64 encoded string and the output will be similar to below:
Image = Base64 encoded version of the following image:
{
"TextDetections": [
{
"DetectedText": "Platforms",
"Type": "LINE",
"Id": 0,
"Confidence": 80.76984405517578,
"Geometry": {
"BoundingBox": {
"Width": 0.322684109210968,
"Height": 0.21306292712688446,
"Left": 0.31165120005607605,
"Top": 0.20371627807617188
},
"Polygon": [
{
"X": 0.32710322737693787,
"Y": 0.20371627807617188
},
{
"X": 0.6343352794647217,
"Y": 0.33576905727386475
},
{
"X": 0.6188832521438599,
"Y": 0.41677922010421753
},
{
"X": 0.31165120005607605,
"Y": 0.28472644090652466
}
]
}
},
{
"DetectedText": "Tickets",
"Type": "LINE",
"Id": 1,
"Confidence": 100,
"Geometry": {
"BoundingBox": {
"Width": 0.26651281118392944,
"Height": 0.18099485337734222,
"Left": 0.28803831338882446,
"Top": 0.3775637149810791
},
"Polygon": [
{
"X": 0.30245441198349,
"Y": 0.3775637149810791
},
{
"X": 0.5545511245727539,
"Y": 0.4674002528190613
},
{
"X": 0.5401350259780884,
"Y": 0.5585585832595825
},
{
"X": 0.28803831338882446,
"Y": 0.46872198581695557
}
]
}
},
.
.
.
{
"DetectedText": "K",
"Type": "WORD",
"Id": 9,
"ParentId": 4,
"Confidence": 66.06149291992188,
"Geometry": {
"BoundingBox": {
"Width": 0.05910034105181694,
"Height": 0.0735236182808876,
"Left": 0.7411853075027466,
"Top": 0.5968468189239502
},
"Polygon": [
{
"X": 0.7411853075027466,
"Y": 0.5968468189239502
},
{
"X": 0.7794448733329773,
"Y": 0.5518018007278442
},
{
"X": 0.8132032752037048,
"Y": 0.6171171069145203
},
{
"X": 0.7749437093734741,
"Y": 0.6610360145568848
}
]
}
}
],
"TextModelVersion": "3.0"
}
AWS docs are here
Provide the Image input as a Base64 encoded string and the output will be similar to below:
Image = Base64 encoded version of the following image:
{
"FaceDetails": [
{
"BoundingBox": {
"Width": 0.37403011322021484,
"Height": 0.3589228093624115,
"Left": 0.3247712552547455,
"Top": 0.07539718598127365
},
"AgeRange": {
"Low": 23,
"High": 35
},
"Smile": {
"Value": false,
"Confidence": 98.7928695678711
},
"Eyeglasses": {
"Value": true,
"Confidence": 99.85688018798828
},
.
.
.
"MouthOpen": {
"Value": false,
"Confidence": 95.0227279663086
},
"Emotions": [
{
"Type": "CALM",
"Confidence": 98.27169036865234
},
{
"Type": "CONFUSED",
"Confidence": 0.4600139260292053
},
.
.
.
{
"Type": "HAPPY",
"Confidence": 0.08039141446352005
}
],
"Landmarks": [
{
"Type": "eyeLeft",
"X": 0.4211536645889282,
"Y": 0.22201673686504364
},
{
"Type": "eyeRight",
"X": 0.5880940556526184,
"Y": 0.22860434651374817
},
.
.
.
{
"Type": "upperJawlineRight",
"X": 0.6837441325187683,
"Y": 0.2481657713651657
}
],
"Pose": {
"Roll": 2.1925508975982666,
"Yaw": 0.3401939868927002,
"Pitch": 11.061576843261719
},
"Quality": {
"Brightness": 77.83470916748047,
"Sharpness": 94.08262634277344
},
"Confidence": 99.99972534179688
}
]
}
AWS docs are here
Provide the Image input as a Base64 encoded string and the output will be similar to below:
Image = Base64 encoded version of the following image:
{
"ModerationLabels": [
{
"Confidence": 95.99689483642578,
"Name": "Alcoholic Beverages",
"ParentName": "Alcohol"
},
{
"Confidence": 95.99689483642578,
"Name": "Alcohol",
"ParentName": ""
}
],
"ModerationModelVersion": "4.0"
}
AWS docs are here
Provide the Image input as a Base64 encoded string and the output will be similar to below:
Image = Base64 encoded version of the following image:
{
"ProtectiveEquipmentModelVersion": "1.0",
"Persons": [
{
"BodyParts": [
{
"Name": "FACE",
"Confidence": 99.33659362792969,
"EquipmentDetections": [
{
"BoundingBox": {
"Width": 0.09513942152261734,
"Height": 0.10421869158744812,
"Left": 0.4654864966869354,
"Top": 0.32142555713653564
},
"Confidence": 99.97029876708984,
"Type": "FACE_COVER",
"CoversBodyPart": {
"Confidence": 89.59506225585938,
"Value": true
}
}
]
},
{
"Name": "LEFT_HAND",
"Confidence": 97.67623901367188,
"EquipmentDetections": []
},
{
"Name": "RIGHT_HAND",
"Confidence": 56.84904479980469,
"EquipmentDetections": [
{
"BoundingBox": {
"Width": 0.09019285440444946,
"Height": 0.10900517553091049,
"Left": 0.22584359347820282,
"Top": 0.4841454327106476
},
"Confidence": 65.1576919555664,
"Type": "HAND_COVER",
"CoversBodyPart": {
"Confidence": 99.8289566040039,
"Value": true
}
}
]
},
{
"Name": "HEAD",
"Confidence": 99.99517822265625,
"EquipmentDetections": []
}
],
"BoundingBox": {
"Width": 0.4809523820877075,
"Height": 0.8015267252922058,
"Left": 0.2380952388048172,
"Top": 0.18320611119270325
},
"Confidence": 99.83000183105469,
"Id": 0
},
{
"BodyParts": [
{
"Name": "FACE",
"Confidence": 99.58224487304688,
"EquipmentDetections": [
{
"BoundingBox": {
"Width": 0.08927446603775024,
"Height": 0.10428228974342346,
"Left": 0.12037970125675201,
"Top": 0.33622512221336365
},
"Confidence": 99.7800521850586,
"Type": "FACE_COVER",
"CoversBodyPart": {
"Confidence": 99.94519805908203,
"Value": true
}
}
]
},
{
"Name": "LEFT_HAND",
"Confidence": 99.28810119628906,
"EquipmentDetections": []
},
{
"Name": "RIGHT_HAND",
"Confidence": 99.97966766357422,
"EquipmentDetections": []
},
{
"Name": "HEAD",
"Confidence": 99.98377227783203,
"EquipmentDetections": []
}
],
"BoundingBox": {
"Width": 0.420634925365448,
"Height": 0.7811704874038696,
"Left": 0.007936508394777775,
"Top": 0.20610687136650085
},
"Confidence": 99.92481231689453,
"Id": 1
},
{
"BodyParts": [
{
"Name": "FACE",
"Confidence": 99.1600112915039,
"EquipmentDetections": [
{
"BoundingBox": {
"Width": 0.09494524449110031,
"Height": 0.1097668930888176,
"Left": 0.7650715112686157,
"Top": 0.31457528471946716
},
"Confidence": 99.89432525634766,
"Type": "FACE_COVER",
"CoversBodyPart": {
"Confidence": 98.65139770507812,
"Value": true
}
}
]
},
{
"Name": "LEFT_HAND",
"Confidence": 99.19236755371094,
"EquipmentDetections": []
},
{
"Name": "RIGHT_HAND",
"Confidence": 99.6152114868164,
"EquipmentDetections": []
},
{
"Name": "HEAD",
"Confidence": 99.98148345947266,
"EquipmentDetections": []
}
],
"BoundingBox": {
"Width": 0.29523810744285583,
"Height": 0.7913485765457153,
"Left": 0.7047619223594666,
"Top": 0.18066157400608063
},
"Confidence": 99.99444580078125,
"Id": 2
},
{
"BodyParts": [
{
"Name": "FACE",
"Confidence": 63.59202194213867,
"EquipmentDetections": []
},
{
"Name": "HEAD",
"Confidence": 96.91404724121094,
"EquipmentDetections": [
{
"BoundingBox": {
"Width": 0.03824697062373161,
"Height": 0.041919633746147156,
"Left": 0.6655418276786804,
"Top": 0.40767616033554077
},
"Confidence": 60.57323455810547,
"Type": "HEAD_COVER",
"CoversBodyPart": {
"Confidence": 99.9076156616211,
"Value": true
}
}
]
}
],
"BoundingBox": {
"Width": 0.06825397163629532,
"Height": 0.5038167834281921,
"Left": 0.6555555462837219,
"Top": 0.40458014607429504
},
"Confidence": 98.65675354003906,
"Id": 3
}
],
"Summary": {
"PersonsWithRequiredEquipment": [],
"PersonsWithoutRequiredEquipment": [
0,
1,
2
],
"PersonsIndeterminate": [
3
]
}
}
FAQs
A plugin for Axway API Builder
The npm package api-builder-plugin-rekognition receives a total of 1 weekly downloads. As such, api-builder-plugin-rekognition popularity was classified as not popular.
We found that api-builder-plugin-rekognition demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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