Introduction
GETTING STARTED?
Check out our quickstart guide.NOT A DEVELOPER?
Sign in to your RAPYD.AI dashboard to get started with apps.Base URL:
https://api.rapyd.ai
RAPYD.AI is an API for AI services. Some people call it AI-as-a-Service. Some call it AI platform. We don't mind how you call it, but here's what RAPYD.AI does in plain English:
Let's break this statement down:
A simple API interface The RAPYD.AI API is organized around REST. Our API accepts form-encoded request bodies, returns JSON-encoded responses, and uses standard HTTP response codes, authentication, and verbs. You can send texts, images, videos or audio files as inputs. You can even use our API to train and deploy custom models (Pro Plan).
State-of-the-art AI services We ensure that the AI services that we provide belong the best of their class. You should focus on your use-case and your AI application and not whether another AI service might do a better job. It might be that another AI achieves better results, especially in very specific or niche settings. But generally speaking, the AI services that we provide here will give you a good baseline to start with.
Leading providers All AI services on RAPYD.AI are production ready. We don't want you to build your prototype using some AI service that does not scale. When you decide to go into production, you can rely that the service provider in the backend can handle your AI production workloads.
Authentication
The RAPYD.AI API uses a combination of your unique, permanent account ID and a temporary access token to authenticate requests.
You will get an Account ID when you sign up here. We will find your Account-ID in your welcome e-mail as well as in your RAPYD.AI Dashboard.
You can generate a token as often as you like either through your RAPYD.AI Dashboard or programmatically using the following API end point:
POST /v1/user/token
A token is valid for 60 minutes.
To get a token, use this code:
curl --location --request POST 'https://api.rapyd.ai/v1/user/token' \
--header 'Content-Type: application/json' \
--header 'Content-Type: text/plain' \
--data-raw '{
"email":"your-email",
"password":"your-password"
}
'
var myHeaders = new Headers();
myHeaders.append("Content-Type", "application/json");
myHeaders.append("Content-Type", "text/plain");
var raw = "{\n \"email\":\"your-email\",\n \"password\":\"your-password\"\n}\n";
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/user/token", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/user/token')
.headers({
'Content-Type': 'application/json'
})
.send(JSON.stringify({"email":"your-email","password":"your-password"}))
.end(function (res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
url = "https://api.rapyd.ai/v1/user/token"
payload = "{\n\t\"email\":\"your-email\",\n\t\"password\":\"your-password\"\n}\n"
headers = {
'Content-Type': 'application/json',
'Content-Type': 'text/plain'
}
response = requests.request("POST", url, headers=headers, data = payload)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/user/token"
payload <- list(email = "your-email",
password = "your-password")
# Get results
response <- POST(url, body = payload, encode = "json")
result <- content(response, "parsed")
Make sure to replace
your-emailandyour-passwordwith your password.Never store your password inside your code! If you are not sure how to manage your passwords safely, use our dashboard to generate a token.
Authentication to the API is performed via Bearer Token Usage.
RAPYD.AI expects the Account ID and the Token to be included in all API requests to the server in a header that looks like the following:
'ACCOUNT-ID: your-accountid'
'Authorization: Bearer your-token'
Never provide your RAPYD.AI login password via the API except for the endpoint /v1/user/token .
All API requests must be made over HTTPS. Calls made over plain HTTP will fail. API requests without authentication will also fail.
Credits
Every successful API request will deduct 1 credit from your RAPYD.AI credit balance.
A successful API request is defined as every request that yields a successful result object.
Errors, rejects or timeouts will not affect your credits balance.
Natural Language
Natural Language Processing (NLP) services helps you to process, analyze and get insights from text data.
Sentiment Analysis
Sentiment analysis is used to classify the polarity of a given text to find out whether the expressed opinion in this text is positive, negative, or neutral.
HTTP Request
POST /v1/nlp/sentiment
curl --location --request POST 'https://api.rapyd.ai/v1/nlp/sentiment' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer your-token' \
--data-raw '{
"text": "I don'\''t like old cabin cruisers.",
"provider":"aws",
"language": "auto"
}'
var myHeaders = new Headers();
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Content-Type", "application/json");
myHeaders.append("Authorization", "Bearer your-token");
var raw = JSON.stringify({
"text": "I don't like old cabin cruisers.",
"provider": "aws",
"language": "auto"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/nlp/sentiment", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/nlp/sentiment')
.headers({
'ACCOUNT-ID': 'your-accountid',
'Content-Type': 'application/json',
'Authorization': 'Bearer your-token'
})
.send(JSON.stringify({
"text": "I don't like old cabin cruisers.",
"provider": "aws",
"language": "auto"
}))
.end(function(res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
headers = {
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token',
'Content-Type': 'application/json'
}
payload = {
"text": "I don't like old cabin cruisers.",
"provider": "aws",
"language": "auto"
}
url = "https://api.rapyd.ai/v1/nlp/sentiment"
response = requests.request("POST", url, headers=headers, json = payload)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/nlp/sentiment"
payload <- list("text" = "I don't like old cabin cruisers.",
"provider" = "aws",
"language" = "auto")
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"Content-Type" = "application/json")
response <- POST(url, add_headers(headers), body = payload, encode = "json")
result <- content(response, "parsed")
result
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation. The content depends on the chosen provider.
Example response when provider is
aws:
{
"meta": {
"provider": "AWS",
"language": "en"
},
"result": {
"sentiment": "NEGATIVE",
"sentimentScore": {
"positive": 0.035679124,
"negative": 0.6906262,
"neutral": 0.27357435,
"mixed": 1.2039347E-4
}
}
}
Example response when provider is
gcp:
{
"meta": {
"provider": "GCP",
"language": "en"
},
"result": {
"score": -0.8
}
}
Example response when provider is
azure:
{
"meta": {
"provider": "AZURE",
"language": "English"
},
"result": {
"sentiment": "neutral",
"confidenceScores": {
"neutral": 0.52,
"positive": 0.03,
"negative": 0.45
},
"sentences": [
{
"text": "I don't like old cabin cruisers.",
"confidenceScores": {
"neutral": 0.52,
"positive": 0.03,
"negative": 0.45
},
"sentiment": "neutral"
}
],
"warnings": []
}
}
Request Parameters
The request body contains data in JSON representation:
| Parameter | Default | Description |
|---|---|---|
| Text | None | The text which you want to analyse. Maximum is 4.000 characters. |
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
| Language | auto |
The language of the text in the request body. Can be any of the following:
|
Detect Entities
Detects entities in a given text. An entity is a reference to a real-world object such as people, places, commercial items, and to measures such as dates and quantities.
Each entity comes with a score that indicates the level of confidence for the detected entity type.
HTTP Request
POST /v1/nlp/entities
curl --location --request POST 'https://api.rapyd.ai/v1/nlp/entities' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer your-token' \
--data-raw '{
"text": "Next summer I want to visit Barcelona and Lion.",
"provider":"aws",
"language": "auto"
}'
var myHeaders = new Headers();
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Content-Type", "application/json");
myHeaders.append("Authorization", "Bearer your-token");
var raw = JSON.stringify({
"text": "Next summer I want to visit Barcelona and Lion.",
"provider": "aws",
"language": "auto"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/nlp/entities", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/nlp/entities')
.headers({
'ACCOUNT-ID': 'your-accountid',
'Content-Type': 'application/json',
'Authorization': 'Bearer your-token'
})
.send(JSON.stringify({
"text": "Next summer I want to visit Barcelona and Lion.",
"provider": "aws",
"language": "auto"
}))
.end(function(res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
headers = {
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token',
'Content-Type': 'application/json'
}
payload = {
"text": "Next summer I want to visit Barcelona and Lion.",
"provider": "aws",
"language": "auto"
}
url = "https://api.rapyd.ai/v1/nlp/entities"
response = requests.request("POST", url, headers=headers, json = payload)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/nlp/entities"
payload <- list("text" = "Next summer I want to visit Barcelona and Lion.",
"provider" = "aws",
"language" = "auto")
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"Content-Type" = "application/json")
response <- POST(url, add_headers(headers), body = payload, encode = "json")
result <- content(response, "parsed")
result
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation. The content depends on the chosen provider.
Example response when provider is
aws:
{
"meta": {
"provider": "aws",
"language": "en"
},
"result": {
"entities": [
{
"score": 0.9543518,
"type": "DATE",
"text": "Next summer",
"beginOffset": 0,
"endOffset": 11
},
{
"score": 0.99991035,
"type": "LOCATION",
"text": "Barcelona",
"beginOffset": 28,
"endOffset": 37
},
{
"score": 0.99886346,
"type": "LOCATION",
"text": "Lion",
"beginOffset": 42,
"endOffset": 46
}
]
}
}
Example response when provider is
gcp:
{
"meta": {
"provider": "GCP",
"language": "en"
},
"result": [
{
"name": "Barcelona",
"salience": 0.6229014992713928,
"type": "LOCATION"
},
{
"name": "Lion",
"salience": 0.3770985007286072,
"type": "ORGANIZATION"
}
]
}
Example response when provider is
azure:
{
"meta": {
"provider": "AZURE",
"language": "English"
},
"result": [
{
"text": "Next summer",
"category": "DateTime",
"subcategory": "DateRange",
"confidenceScore": 0.8
},
{
"text": "Barcelona",
"category": "Location",
"subcategory": "GPE",
"confidenceScore": 0.41
},
{
"text": "Lion",
"category": "Location",
"subcategory": "GPE",
"confidenceScore": 0.36
}
]
}
Request Parameters
The request body contains data in JSON representation.
| Parameter | Default | Description |
|---|---|---|
| Text | None | The text which you want to analyse. Maximum is 4.000 characters. |
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
| Language | auto |
The language of the text in the request body. Can be any of the following:
|
Detect Key Phrases
Detects the key noun phrases used in text.
Each key phrase comes with a score that indicates the level of confidence for the detected noun phrase.
HTTP Request
POST /v1/nlp/keyphrase
curl --location --request POST 'https://api.rapyd.ai/v1/nlp/keyphrase' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer your-token' \
--data-raw '{
"text": "Seems it never rains in Southern California.",
"provider":"aws",
"language": "auto"
}'
var myHeaders = new Headers();
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Content-Type", "application/json");
myHeaders.append("Authorization", "Bearer your-token");
var raw = JSON.stringify({
"text": "Seems it never rains in Southern California.",
"provider": "aws",
"language": "auto"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/nlp/keyphrase", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/nlp/keyphrase')
.headers({
'ACCOUNT-ID': 'your-accountid',
'Content-Type': 'application/json',
'Authorization': 'Bearer your-token'
})
.send(JSON.stringify({
"text": "Seems it never rains in Southern California.",
"provider": "aws",
"language": "auto"
}))
.end(function(res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
headers = {
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token',
'Content-Type': 'application/json'
}
payload = {
"text": "Seems it never rains in Southern California.",
"provider": "aws",
"language": "auto"
}
url = "https://api.rapyd.ai/v1/nlp/keyphrase"
response = requests.request("POST", url, headers=headers, json = payload)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/nlp/keyphrase"
payload <- list("text" = "Seems it never rains in Southern California.",
"provider" = "aws",
"language" = "auto")
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"Content-Type" = "application/json")
response <- POST(url, add_headers(headers), body = payload, encode = "json")
result <- content(response, "parsed")
result
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation. The content depends on the chosen provider.
Example response when provider is
aws:
{
"meta": {
"provider": "aws",
"language": "en"
},
"result": {
"keyPhrases": [
{
"score": 0.9999997,
"text": "Southern California",
"beginOffset": 24,
"endOffset": 43
}
]
}
}
Example response when provider is
azure:
{
"meta": {
"provider": "azure",
"language": "English"
},
"result": [
"Southern California"
]
}
Request Parameters
The request body contains data in JSON representation.
| Parameter | Default | Description |
|---|---|---|
| Text | None | The text which you want to analyse. Maximum is 4.000 characters. |
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
| Language | auto |
The language of the text in the request body. Can be any of the following:
|
Computer Vision
Computer Vision enables machines to "see" images and recognize objects, entities and texts or extract meta information from a given image.
Face Detection
Face detection identifies faces on images and analyses various characteristics such as the face expression or facial features like eyes, nose or mouth positions.
Each face detection carries a confidence score for recognizing the face itself as well as the features of the face.
HTTP Request
POST /v1/vision/face
curl --location --request POST 'https://api.rapyd.ai/v1/vision/face' \
--header 'PROVIDER: gcp' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Authorization: Bearer your-token' \
--form 'file=face_demo.png'
var myHeaders = new Headers();
myHeaders.append("PROVIDER", "gcp");
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Authorization", "Bearer your-token");
var formdata = new FormData();
formdata.append("file", fileInput.files[0], "face_demo.png");
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: formdata,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/vision/face", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/vision/face')
.headers({
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
})
.attach('file', 'face_demo.png')
.end(function (res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
url = "https://api.rapyd.ai/v1/vision/face"
payload = {}
files = [('file', open('face_demo.png', 'rb'))]
headers = {
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
}
response = requests.request(
"POST", url, headers=headers, data=payload, files=files)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/vision/face"
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"PROVIDER" = "gcp")
payload <- list(file = upload_file("face_demo.png"))
response <- POST(url, add_headers(headers), body = payload)
result <- content(response, "parsed")
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation.
Example response when provider is
gcp:
{
"meta": {
"provider": "GCP",
"language": ""
},
"result": [
{
"rollAngle": -0.4798591,
"panAngle": 0.12718968,
"tiltAngle": -1.2569677,
"detectionConfidence": 0.94939417,
"landmarkingConfidence": 0.80378807,
"joyRating": 1.0,
"sorrowRating": 0.2,
"angerRating": 0.2,
"surpriseRating": 0.2,
"underExposedRating": 0.2,
"blurredRating": 0.2,
"headwearRating": 0.2,
"joy": "VERY_LIKELY",
"sorrow": "VERY_UNLIKELY",
"anger": "VERY_UNLIKELY",
"surprise": "VERY_UNLIKELY",
"underExposed": "VERY_UNLIKELY",
"blurred": "VERY_UNLIKELY",
"headwear": "VERY_UNLIKELY",
"boundingPoly": [
{
"x": 549,
"y": 26
},
{
"x": 1164,
"y": 26
},
{
"x": 1164,
"y": 740
},
{
"x": 549,
"y": 740
}
],
"fdBoundingPoly": [
{
"x": 587,
"y": 153
},
{
"x": 1124,
"y": 153
},
{
"x": 1124,
"y": 686
},
{
"x": 587,
"y": 686
}
],
"landmarks": [
{
"type": "LEFT_EYE",
"x": 768.32544,
"y": 373.06293,
"z": 0.0013751984
},
{
"type": "RIGHT_EYE",
"x": 951.94446,
"y": 369.37823,
"z": 0.4714136
},
{
"type": "LEFT_OF_LEFT_EYEBROW",
"x": 701.52814,
"y": 339.7583,
"z": 14.543475
},
{
"type": "RIGHT_OF_LEFT_EYEBROW",
"x": 814.4408,
"y": 331.55685,
"z": -34.32722
},
{
"type": "LEFT_OF_RIGHT_EYEBROW",
"x": 903.94037,
"y": 327.39395,
"z": -33.947388
},
{
"type": "RIGHT_OF_RIGHT_EYEBROW",
"x": 1017.8008,
"y": 336.4593,
"z": 15.296562
},
{
"type": "MIDPOINT_BETWEEN_EYES",
"x": 859.9506,
"y": 364.55762,
"z": -36.450184
},
{
"type": "NOSE_TIP",
"x": 856.7595,
"y": 477.4241,
"z": -88.43703
},
{
"type": "UPPER_LIP",
"x": 858.8607,
"y": 536.78925,
"z": -47.308403
},
{
"type": "LOWER_LIP",
"x": 860.94543,
"y": 612.84033,
"z": -34.59475
},
{
"type": "MOUTH_LEFT",
"x": 763.8856,
"y": 559.6046,
"z": 2.3785026
},
{
"type": "MOUTH_RIGHT",
"x": 955.97986,
"y": 554.21515,
"z": 3.0310767
},
{
"type": "MOUTH_CENTER",
"x": 862.51575,
"y": 575.4721,
"z": -34.262444
},
{
"type": "NOSE_BOTTOM_RIGHT",
"x": 920.23486,
"y": 484.30716,
"z": -22.016401
},
{
"type": "NOSE_BOTTOM_LEFT",
"x": 797.2778,
"y": 486.82227,
"z": -22.553627
},
{
"type": "NOSE_BOTTOM_CENTER",
"x": 858.078,
"y": 504.10403,
"z": -48.339252
},
{
"type": "LEFT_EYE_TOP_BOUNDARY",
"x": 766.4023,
"y": 358.04807,
"z": -10.352289
},
{
"type": "LEFT_EYE_RIGHT_CORNER",
"x": 803.16595,
"y": 374.9589,
"z": -0.06131935
},
{
"type": "LEFT_EYE_BOTTOM_BOUNDARY",
"x": 766.3668,
"y": 387.02142,
"z": -1.8237071
},
{
"type": "LEFT_EYE_LEFT_CORNER",
"x": 728.4919,
"y": 377.98483,
"z": 15.790957
},
{
"type": "RIGHT_EYE_TOP_BOUNDARY",
"x": 953.81085,
"y": 352.64587,
"z": -9.6653805
},
{
"type": "RIGHT_EYE_RIGHT_CORNER",
"x": 991.34924,
"y": 374.1126,
"z": 16.405922
},
{
"type": "RIGHT_EYE_BOTTOM_BOUNDARY",
"x": 953.1808,
"y": 383.13376,
"z": -1.3505049
},
{
"type": "RIGHT_EYE_LEFT_CORNER",
"x": 913.28955,
"y": 371.66306,
"z": 0.2713766
},
{
"type": "LEFT_EYEBROW_UPPER_MIDPOINT",
"x": 759.5528,
"y": 317.5705,
"z": -20.760433
},
{
"type": "RIGHT_EYEBROW_UPPER_MIDPOINT",
"x": 961.46344,
"y": 313.44608,
"z": -19.984333
},
{
"type": "LEFT_EAR_TRAGION",
"x": 643.31226,
"y": 435.80838,
"z": 221.14575
},
{
"type": "RIGHT_EAR_TRAGION",
"x": 1066.6526,
"y": 425.88293,
"z": 223.30026
},
{
"type": "FOREHEAD_GLABELLA",
"x": 860.34784,
"y": 325.64413,
"z": -40.136284
},
{
"type": "CHIN_GNATHION",
"x": 861.9055,
"y": 709.1296,
"z": -9.581303
},
{
"type": "CHIN_LEFT_GONION",
"x": 688.78577,
"y": 595.2242,
"z": 148.22136
},
{
"type": "CHIN_RIGHT_GONION",
"x": 1029.5104,
"y": 582.9388,
"z": 149.34828
},
{
"type": "UNKNOWN_LANDMARK",
"x": 726.73364,
"y": 497.08798,
"z": 17.647654
},
{
"type": "UNKNOWN_LANDMARK",
"x": 994.6479,
"y": 492.37317,
"z": 18.335396
}
]
}
]
}
Example response when provider is
aws
{
"meta":{
"language":"",
"provider":"aws"
},
"result":{
"faceDetails":[
{
"ageRange":"None",
"beard":"None",
"boundingBox":{
"height":0.26589525,
"left":0.37521443,
"top":0.06623106,
"width":0.2295874
},
"confidence":99.99913,
"emotions":"None",
"eyeglasses":"None",
"eyesOpen":"None",
"gender":"None",
"landmarks":[
{
"type":"eyeLeft",
"x":0.44272083,
"y":0.17161196
},
{
"type":"eyeRight",
"x":0.5494187,
"y":0.17190441
},
{
"type":"mouthLeft",
"x":0.4502387,
"y":0.2601221
},
{
"type":"mouthRight",
"x":0.5393077,
"y":0.26036945
},
{
"type":"nose",
"x":0.49708697,
"y":0.2186894
}
],
"mouthOpen":"None",
"mustache":"None",
"pose":{
"pitch":3.009071,
"roll":-0.5177236,
"yaw":1.9940312
},
"quality":{
"brightness":90.198135,
"sharpness":95.51619
},
"smile":"None",
"sunglasses":"None"
}
],
"orientationCorrection":"None"
}
}
Example response when provider is
azure
{
"meta":{
"language":"",
"provider":"azure"
},
"result":{
"faces":[
{
"age":57,
"faceRectangle":{
"height":252,
"left":382,
"top":146,
"width":252
},
"gender":"Male"
}
]
}
}
Request Parameters
| Parameter | Default | Description |
|---|---|---|
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
File Properties
The request sends a file over HTTPS.
| File Properties | Description |
|---|---|
| Image File Size | Maximum file size is 2 MB |
| File Format | The following image types are supported:
|
| Image Dimensions | The recommended image size is 1600 x 1200 pixels (ca. 1.9M pixels). The larger the faces on the image the better. The distance between eyes is most important. |
The response object contains many information. Please see the following links for more details:
Face detection results from GCP
Landmark Detection
Landmark detection detects public places, tourist attractions or well-known landmarks in an image. It provides the label, the geo-coordinates, the position, and the confidence score of the detected landmark.
Object information is returned in English only.
HTTP Request
POST /v1/vision/landmark
curl --location --request POST 'https://api.rapyd.ai/v1/vision/landmark' \
--header 'PROVIDER: gcp' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Authorization: Bearer your-token' \
--form 'file=landmark_demo.png'
var myHeaders = new Headers();
myHeaders.append("PROVIDER", "gcp");
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Authorization", "Bearer your-token");
var formdata = new FormData();
formdata.append("file", fileInput.files[0], "landmark_demo.png");
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: formdata,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/vision/landmark", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/vision/landmark')
.headers({
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
})
.attach('file', 'landmark_demo.png')
.end(function (res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
url = "https://api.rapyd.ai/v1/vision/landmark"
payload = {}
files = [
('file', open('landmark_demo.png','rb'))
]
headers = {
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
}
response = requests.request("POST", url, headers=headers, data = payload, files = files)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/vision/landmark"
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"PROVIDER" = "gcp")
payload <- list(file = upload_file("landmark_demo.png"))
response <- POST(url, add_headers(headers), body = payload)
result <- content(response, "parsed")
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation.
Example response when provider is
gcp:
{
"meta": {
"provider": "GCP",
"language": ""
},
"result": [
{
"description": "Palace of Fine Arts",
"score": 0.68384635,
"boundingPoly": [
{
"x": 108,
"y": 102
},
{
"x": 256,
"y": 102
},
{
"x": 256,
"y": 398
},
{
"x": 108,
"y": 398
}
],
"locations": [
{
"lng": -122.447777,
"lat": 37.80290085993192
}
]
}
]
}
Example response when provider is
azure:
{
"meta":{
"language":"",
"provider":"azure"
},
"result":{
"categories":[
{
"detail":{
"landmarks":[
{
"confidence":0.9999419450759888,
"name":"Eiffel Tower"
}
]
},
"name":"building_",
"score":0.3671875
},
{
"detail":{
"landmarks":[
{
"confidence":0.9999419450759888,
"name":"Eiffel Tower"
}
]
},
"name":"building_church",
"score":0.609375
}
]
}
}
Request Parameters
| Parameter | Default | Description |
|---|---|---|
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
File Properties
The request sends a file over HTTPS.
| File Properties | Description |
|---|---|
| Image File Size | Maximum file size is 2 MB |
| File Format | The following image types are supported:
|
| Image Dimensions | The recommended image size is 640 x 480 pixels (ca. 300k pixels). Larger image sizes may not gain much in accuracy, while greatly increasing bandwidth usage and processing time. |
Object Localization
Object localization detects multiple objects in an image and provides the label, the position, and the confidence score of the detected object.
Object information is returned in English only.
HTTP Request
POST /v1/vision/localize
curl --location --request POST 'https://api.rapyd.ai/v1/vision/localize' \
--header 'PROVIDER: gcp' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Authorization: Bearer your-token' \
--form 'file=localize_demo.png'
var myHeaders = new Headers();
myHeaders.append("PROVIDER", "gcp");
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Authorization", "Bearer your-token");
var formdata = new FormData();
formdata.append("file", fileInput.files[0], "localize_demo.png");
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: formdata,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/vision/localize", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/vision/localize')
.headers({
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
})
.attach('file', 'localize_demo.png')
.end(function (res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
url = "https://api.rapyd.ai/v1/vision/localize"
payload = {}
files = [
('file', open('localize_demo.png','rb'))
]
headers = {
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
}
response = requests.request("POST", url, headers=headers, data = payload, files = files)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/vision/localize"
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"PROVIDER" = "gcp")
payload <- list(file = upload_file("localize_demo.png"))
response <- POST(url, add_headers(headers), body = payload)
result <- content(response, "parsed")
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation.
Example response when provider is
gcp:
{
"meta": {
"provider": "gcp",
"language": ""
},
"result": [
{
"description": "Wheel",
"score": 0.9287957,
"boundingPoly": [
{
"x": 0.21665983,
"y": 0.8182854
},
{
"x": 0.3499323,
"y": 0.8182854
},
{
"x": 0.3499323,
"y": 0.99085253
},
{
"x": 0.21665983,
"y": 0.99085253
}
]
},
{
"description": "Pants",
"score": 0.9245052,
"boundingPoly": [
{
"x": 0.61920214,
"y": 0.7110153
},
{
"x": 0.7021143,
"y": 0.7110153
},
{
"x": 0.7021143,
"y": 0.9056063
},
{
"x": 0.61920214,
"y": 0.9056063
}
]
},
{
"description": "Person",
"score": 0.8962906,
"boundingPoly": [
{
"x": 0.072677895,
"y": 0.4074293
},
{
"x": 0.2129082,
"y": 0.4074293
},
{
"x": 0.2129082,
"y": 0.9247987
},
{
"x": 0.072677895,
"y": 0.9247987
}
]
},
{
"description": "Person",
"score": 0.84560376,
"boundingPoly": [
{
"x": 0.6047527,
"y": 0.501253
},
{
"x": 0.7425805,
"y": 0.501253
},
{
"x": 0.7425805,
"y": 0.9682343
},
{
"x": 0.6047527,
"y": 0.9682343
}
]
},
{
"description": "Person",
"score": 0.8412963,
"boundingPoly": [
{
"x": 0.20903979,
"y": 0.44468263
},
{
"x": 0.32457075,
"y": 0.44468263
},
{
"x": 0.32457075,
"y": 0.64302355
},
{
"x": 0.20903979,
"y": 0.64302355
}
]
},
{
"description": "Top",
"score": 0.8289973,
"boundingPoly": [
{
"x": 0.60539424,
"y": 0.5631088
},
{
"x": 0.72236294,
"y": 0.5631088
},
{
"x": 0.72236294,
"y": 0.73758584
},
{
"x": 0.60539424,
"y": 0.73758584
}
]
},
{
"description": "Motorcycle",
"score": 0.824747,
"boundingPoly": [
{
"x": 0.031174297,
"y": 0.577174
},
{
"x": 0.3698026,
"y": 0.577174
},
{
"x": 0.3698026,
"y": 0.992837
},
{
"x": 0.031174297,
"y": 0.992837
}
]
},
{
"description": "Person",
"score": 0.7636599,
"boundingPoly": [
{
"x": 0.2532207,
"y": 0.60297704
},
{
"x": 0.35460314,
"y": 0.60297704
},
{
"x": 0.35460314,
"y": 0.7952354
},
{
"x": 0.2532207,
"y": 0.7952354
}
]
},
{
"description": "Pants",
"score": 0.7326683,
"boundingPoly": [
{
"x": 0.07288302,
"y": 0.67554694
},
{
"x": 0.15689848,
"y": 0.67554694
},
{
"x": 0.15689848,
"y": 0.8859668
},
{
"x": 0.07288302,
"y": 0.8859668
}
]
},
{
"description": "Wheel",
"score": 0.65781885,
"boundingPoly": [
{
"x": 0.0026128727,
"y": 0.83867663
},
{
"x": 0.10945473,
"y": 0.83867663
},
{
"x": 0.10945473,
"y": 0.9945914
},
{
"x": 0.0026128727,
"y": 0.9945914
}
]
}
]
}
Example response when provider is
aws:
{
"meta":{
"language":"",
"provider":"aws"
},
"result":{
"labels":[
{
"confidence":99.93255,
"instances":[
],
"name":"Transportation",
"parents":[
]
},
{
"confidence":99.93255,
"instances":[
{
"boundingBox":{
"height":0.26746246,
"left":0.2435077,
"top":0.7304542,
"width":0.43250093
},
"confidence":99.93255
},
{
"boundingBox":{
"height":0.20392673,
"left":0.64362967,
"top":0.69532245,
"width":0.23975754
},
"confidence":99.69274
},
{
"boundingBox":{
"height":0.11905708,
"left":0.91752166,
"top":0.60079324,
"width":0.08082161
},
"confidence":99.64808
}
],
"name":"Car",
"parents":[
{
"name":"Vehicle"
},
{
"name":"Transportation"
}
]
},
{
"confidence":99.93255,
"instances":[
],
"name":"Automobile",
"parents":[
{
"name":"Vehicle"
},
{
"name":"Transportation"
}
]
},
{
"confidence":99.93255,
"instances":[
],
"name":"Vehicle",
"parents":[
{
"name":"Transportation"
}
]
},
{
"confidence":99.66535,
"instances":[
],
"name":"Human",
"parents":[
]
},
{
"confidence":99.66535,
"instances":[
{
"boundingBox":{
"height":0.25602785,
"left":0.19563706,
"top":0.71866006,
"width":0.074756525
},
"confidence":99.66535
},
{
"boundingBox":{
"height":0.2606125,
"left":0.16511679,
"top":0.70453167,
"width":0.057169415
},
"confidence":98.798164
},
{
"boundingBox":{
"height":0.08052279,
"left":0.9173708,
"top":0.5655817,
"width":0.022436142
},
"confidence":86.93286
},
{
"boundingBox":{
"height":0.09262364,
"left":0.44430676,
"top":0.66099834,
"width":0.033827115
},
"confidence":48.962578
}
],
"name":"Person",
"parents":[
]
},
{
"confidence":97.96712,
"instances":[
{
"boundingBox":{
"height":0.086164854,
"left":0.75191283,
"top":0.8163411,
"width":0.04245138
},
"confidence":97.96712
},
{
"boundingBox":{
"height":0.076943204,
"left":0.84725034,
"top":0.76657265,
"width":0.029026221
},
"confidence":62.06658
}
],
"name":"Wheel",
"parents":[
{
"name":"Machine"
}
]
},
{
"confidence":97.96712,
"instances":[
],
"name":"Machine",
"parents":[
]
},
{
"confidence":88.32316,
"instances":[
],
"name":"Urban",
"parents":[
]
},
{
"confidence":88.32316,
"instances":[
],
"name":"Building",
"parents":[
]
},
{
"confidence":88.32316,
"instances":[
],
"name":"Neighborhood",
"parents":[
{
"name":"Urban"
},
{
"name":"Building"
}
]
},
{
"confidence":80.73974,
"instances":[
],
"name":"Canopy",
"parents":[
]
},
{
"confidence":80.73974,
"instances":[
],
"name":"Awning",
"parents":[
{
"name":"Canopy"
}
]
},
{
"confidence":76.45942,
"instances":[
],
"name":"Road",
"parents":[
]
},
{
"confidence":60.37967,
"instances":[
],
"name":"Path",
"parents":[
]
},
{
"confidence":60.273117,
"instances":[
],
"name":"Town",
"parents":[
{
"name":"Urban"
},
{
"name":"Building"
}
]
},
{
"confidence":60.273117,
"instances":[
],
"name":"City",
"parents":[
{
"name":"Urban"
},
{
"name":"Building"
}
]
},
{
"confidence":57.69777,
"instances":[
],
"name":"Shop",
"parents":[
]
},
{
"confidence":56.987423,
"instances":[
],
"name":"Pedestrian",
"parents":[
{
"name":"Person"
}
]
}
]
}
}
Example response when provider is
azure:
{
"meta":{
"language":"",
"provider":"azure"
},
"result":{
"metadata":{
"format":"Png",
"height":480,
"width":640
},
"objects":[
{
"confidence":0.597,
"object":"car",
"parent":{
"confidence":0.618,
"object":"Land vehicle",
"parent":{
"confidence":0.618,
"object":"Vehicle"
}
},
"rectangle":{
"h":51,
"w":45,
"x":591,
"y":289
}
},
{
"confidence":0.824,
"object":"car",
"parent":{
"confidence":0.853,
"object":"Land vehicle",
"parent":{
"confidence":0.853,
"object":"Vehicle"
}
},
"rectangle":{
"h":96,
"w":162,
"x":411,
"y":337
}
},
{
"confidence":0.858,
"object":"car",
"parent":{
"confidence":0.884,
"object":"Land vehicle",
"parent":{
"confidence":0.884,
"object":"Vehicle"
}
},
"rectangle":{
"h":124,
"w":263,
"x":163,
"y":356
}
}
]
}
}
Request Parameters
| Parameter | Default | Description |
|---|---|---|
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
File Properties
The request sends a file over HTTPS.
| File Properties | Description |
|---|---|
| Image File Size | Maximum file size is 2 MB |
| File Format | The following image types are supported:
|
| Image Dimensions | The recommended image size is 640 x 480 pixels (ca. 300k pixels). Larger image sizes may not gain much in accuracy, while greatly increasing bandwidth usage and processing time. |
Text Detection
Text detection extracts text from an image using OCR (optical character recognition).
Extracted text structures follow a strict hierarchy as follows (bottom to top level): * Symbol -> Word -> Paragraph -> Block -> Page
Each of these components have their own properties such as position and confidence score.
HTTP Request
POST /v1/vision/text
curl --location --request POST 'https://api.rapyd.ai/v1/vision/text' \
--header 'PROVIDER: gcp' \
--header 'ACCOUNT-ID: your-accountid' \
--header 'Authorization: Bearer your-token' \
--form 'file=text_demo.png'
var myHeaders = new Headers();
myHeaders.append("PROVIDER", "gcp");
myHeaders.append("ACCOUNT-ID", "your-accountid");
myHeaders.append("Authorization", "Bearer your-token");
var formdata = new FormData();
formdata.append("file", fileInput.files[0], "text_demo.png");
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: formdata,
redirect: 'follow'
};
fetch("https://api.rapyd.ai/v1/vision/text", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
var unirest = require('unirest');
var req = unirest('POST', 'https://api.rapyd.ai/v1/vision/text')
.headers({
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
})
.attach('file', 'text_demo.png')
.end(function (res) {
if (res.error) throw new Error(res.error);
console.log(res.raw_body);
});
import requests
url = "https://api.rapyd.ai/v1/vision/text"
payload = {}
files = [
('file', open('text_demo.png','rb'))
]
headers = {
'PROVIDER': 'gcp',
'ACCOUNT-ID': 'your-accountid',
'Authorization': 'Bearer your-token'
}
response = requests.request("POST", url, headers=headers, data = payload, files = files)
print(response.text.encode('utf8'))
library(httr)
url <- "https://api.rapyd.ai/v1/vision/text"
headers <- c("ACCOUNT-ID" = "your-accountid",
"Authorization" = "Bearer your-token",
"PROVIDER" = "gcp")
payload <- list(file = upload_file("text_demo.png"))
response <- POST(url, add_headers(headers), body = payload)
result <- content(response, "parsed")
Make sure to replace
your-accountidandyour-tokenwith your personal credentials.The above command returns results in JSON representation.
Example response when provider is
gcp:
{
"meta": {
"provider": "GCP",
"language": ""
},
"result": [
{
"description": "SCHOOL\nSPEED\nLIMIT\n25\nWHEN\nCHILDREN\nARE PRESENT\n",
"boundingPoly": [
{
"x": 596,
"y": 387
},
{
"x": 904,
"y": 387
},
{
"x": 904,
"y": 971
},
{
"x": 596,
"y": 971
}
]
},
{
"description": "SCHOOL",
"boundingPoly": [
{
"x": 596,
"y": 389
},
{
"x": 904,
"y": 387
},
{
"x": 904,
"y": 456
},
{
"x": 596,
"y": 458
}
]
},
{
"description": "SPEED",
"boundingPoly": [
{
"x": 612,
"y": 522
},
{
"x": 877,
"y": 520
},
{
"x": 877,
"y": 575
},
{
"x": 612,
"y": 577
}
]
},
{
"description": "LIMIT",
"boundingPoly": [
{
"x": 634,
"y": 604
},
{
"x": 849,
"y": 604
},
{
"x": 849,
"y": 659
},
{
"x": 634,
"y": 659
}
]
},
{
"description": "25",
"boundingPoly": [
{
"x": 608,
"y": 684
},
{
"x": 867,
"y": 684
},
{
"x": 867,
"y": 827
},
{
"x": 608,
"y": 827
}
]
},
{
"description": "WHEN",
"boundingPoly": [
{
"x": 685,
"y": 870
},
{
"x": 784,
"y": 870
},
{
"x": 784,
"y": 897
},
{
"x": 685,
"y": 897
}
]
},
{
"description": "CHILDREN",
"boundingPoly": [
{
"x": 642,
"y": 904
},
{
"x": 827,
"y": 902
},
{
"x": 827,
"y": 933
},
{
"x": 642,
"y": 935
}
]
},
{
"description": "ARE",
"boundingPoly": [
{
"x": 596,
"y": 940
},
{
"x": 670,
"y": 941
},
{
"x": 670,
"y": 970
},
{
"x": 596,
"y": 969
}
]
},
{
"description": "PRESENT",
"boundingPoly": [
{
"x": 699,
"y": 940
},
{
"x": 871,
"y": 941
},
{
"x": 871,
"y": 971
},
{
"x": 699,
"y": 970
}
]
}
]
}
Example response when provider is
aws
{
"meta":{
"language":"",
"provider":"aws"
},
"result":{
"textDetections":[
{
"confidence":99.96048,
"detectedText":"SCHOOL",
"geometry":{
"boundingBox":{
"height":0.059901997,
"left":0.41503906,
"top":0.3580729,
"width":0.20507498
},
"polygon":[
{
"x":0.41503906,
"y":0.3580729
},
{
"x":0.620114,
"y":0.35616863
},
{
"x":0.62042695,
"y":0.4160706
},
{
"x":0.41535196,
"y":0.41797492
}
]
},
"id":0,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.98234,
"detectedText":"SPEED",
"geometry":{
"boundingBox":{
"height":0.057378843,
"left":0.421665,
"top":0.47647533,
"width":0.1875003
},
"polygon":[
{
"x":0.421665,
"y":0.47647533
},
{
"x":0.6091653,
"y":0.47525543
},
{
"x":0.6093753,
"y":0.53263426
},
{
"x":0.421875,
"y":0.5338542
}
]
},
"id":1,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.986595,
"detectedText":"LIMIT",
"geometry":{
"boundingBox":{
"height":0.057398427,
"left":0.43525207,
"top":0.5533881,
"width":0.15459111
},
"polygon":[
{
"x":0.43525207,
"y":0.5533881
},
{
"x":0.5898432,
"y":0.5519739
},
{
"x":0.59013855,
"y":0.6093723
},
{
"x":0.43554744,
"y":0.61078656
}
]
},
"id":2,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.89751,
"detectedText":"25",
"geometry":{
"boundingBox":{
"height":0.13938081,
"left":0.41544846,
"top":0.6276083,
"width":0.18847631
},
"polygon":[
{
"x":0.41544846,
"y":0.6276083
},
{
"x":0.60392475,
"y":0.6262442
},
{
"x":0.6044922,
"y":0.765625
},
{
"x":0.41601586,
"y":0.7669891
}
]
},
"id":3,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.82379,
"detectedText":"WHEN",
"geometry":{
"boundingBox":{
"height":0.03125,
"left":0.47070312,
"top":0.79817706,
"width":0.076171875
},
"polygon":[
{
"x":0.47070312,
"y":0.79817706
},
{
"x":0.546875,
"y":0.79817706
},
{
"x":0.546875,
"y":0.82942706
},
{
"x":0.47070312,
"y":0.82942706
}
]
},
"id":4,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.91038,
"detectedText":"CHILDREN",
"geometry":{
"boundingBox":{
"height":0.031289447,
"left":0.44122976,
"top":0.8333351,
"width":0.13396531
},
"polygon":[
{
"x":0.44122976,
"y":0.8333351
},
{
"x":0.5751951,
"y":0.83199
},
{
"x":0.5753718,
"y":0.86327946
},
{
"x":0.4414065,
"y":0.86462456
}
]
},
"id":5,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.85474,
"detectedText":"ARE PRESENT",
"geometry":{
"boundingBox":{
"height":0.032753557,
"left":0.4082035,
"top":0.8643817,
"width":0.19635078
},
"polygon":[
{
"x":0.4082035,
"y":0.8643817
},
{
"x":0.6045543,
"y":0.8650575
},
{
"x":0.6044909,
"y":0.89781106
},
{
"x":0.4081401,
"y":0.8971352
}
]
},
"id":6,
"parentId":"None",
"type":"LINE"
},
{
"confidence":99.96048,
"detectedText":"SCHOOL",
"geometry":{
"boundingBox":{
"height":0.05859375,
"left":0.41503906,
"top":0.3580729,
"width":0.20508225
},
"polygon":[
{
"x":0.41503906,
"y":0.3580729
},
{
"x":0.6201172,
"y":0.35677084
},
{
"x":0.6201172,
"y":0.4153646
},
{
"x":0.41601562,
"y":0.41796875
}
]
},
"id":7,
"parentId":0,
"type":"WORD"
},
{
"confidence":99.98234,
"detectedText":"SPEED",
"geometry":{
"boundingBox":{
"height":0.05729999,
"left":0.421875,
"top":0.4765625,
"width":0.18652798
},
"polygon":[
{
"x":0.421875,
"y":0.4765625
},
{
"x":0.60839844,
"y":0.4752604
},
{
"x":0.609375,
"y":0.53255206
},
{
"x":0.421875,
"y":0.5338542
}
]
},
"id":8,
"parentId":1,
"type":"WORD"
},
{
"confidence":99.986595,
"detectedText":"LIMIT",
"geometry":{
"boundingBox":{
"height":0.057291668,
"left":0.43554688,
"top":0.55338544,
"width":0.15430237
},
"polygon":[
{
"x":0.43554688,
"y":0.55338544
},
{
"x":0.58984375,
"y":0.5520833
},
{
"x":0.58984375,
"y":0.609375
},
{
"x":0.43554688,
"y":0.61067706
}
]
},
"id":9,
"parentId":2,
"type":"WORD"
},
{
"confidence":99.89751,
"detectedText":"25",
"geometry":{
"boundingBox":{
"height":0.13932633,
"left":0.41601562,
"top":0.6276042,
"width":0.18750452
},
"polygon":[
{
"x":0.41601562,
"y":0.6276042
},
{
"x":0.6035156,
"y":0.62630206
},
{
"x":0.6044922,
"y":0.765625
},
{
"x":0.41601562,
"y":0.76692706
}
]
},
"id":10,
"parentId":3,
"type":"WORD"
},
{
"confidence":99.82379,
"detectedText":"WHEN",
"geometry":{
"boundingBox":{
"height":0.03125,
"left":0.47070312,
"top":0.79817706,
"width":0.076171875
},
"polygon":[
{
"x":0.47070312,
"y":0.79817706
},
{
"x":0.546875,
"y":0.79817706
},
{
"x":0.546875,
"y":0.82942706
},
{
"x":0.47070312,
"y":0.82942706
}
]
},
"id":11,
"parentId":4,
"type":"WORD"
},
{
"confidence":99.91038,
"detectedText":"CHILDREN",
"geometry":{
"boundingBox":{
"height":0.03125,
"left":0.44140625,
"top":0.8333333,
"width":0.1337954
},
"polygon":[
{
"x":0.44140625,
"y":0.8333333
},
{
"x":0.5751953,
"y":0.83203125
},
{
"x":0.5751953,
"y":0.86328125
},
{
"x":0.44140625,
"y":0.8645833
}
]
},
"id":12,
"parentId":5,
"type":"WORD"
},
{
"confidence":99.773544,
"detectedText":"ARE",
"geometry":{
"boundingBox":{
"height":0.032552082,
"left":0.40820312,
"top":0.8645833,
"width":0.05859375
},
"polygon":[
{
"x":0.40820312,
"y":0.8645833
},
{
"x":0.46679688,
"y":0.8645833
},
{
"x":0.46679688,
"y":0.89713544
},
{
"x":0.40820312,
"y":0.89713544
}
]
},
"id":13,
"parentId":6,
"type":"WORD"
},
{
"confidence":99.93593,
"detectedText":"PRESENT",
"geometry":{
"boundingBox":{
"height":0.03125,
"left":0.48046875,
"top":0.86588544,
"width":0.12402344
},
"polygon":[
{
"x":0.48046875,
"y":0.86588544
},
{
"x":0.6044922,
"y":0.86588544
},
{
"x":0.6044922,
"y":0.89713544
},
{
"x":0.48046875,
"y":0.89713544
}
]
},
"id":14,
"parentId":6,
"type":"WORD"
}
]
}
}
Example response when provider is
azure
{
"meta":{
"language":"",
"provider":"azure"
},
"result":{
"language":"en",
"orientation":"Up",
"regions":[
{
"boundingBox":"423,276,212,415",
"lines":[
{
"boundingBox":"430,276,205,44",
"words":[
{
"boundingBox":"430,276,205,44",
"text":"SCHOOL"
}
]
},
{
"boundingBox":"436,370,189,40",
"words":[
{
"boundingBox":"436,370,189,40",
"text":"SPEED"
}
]
},
{
"boundingBox":"487,618,71,21",
"words":[
{
"boundingBox":"487,618,71,21",
"text":"WHEN"
}
]
},
{
"boundingBox":"457,643,131,22",
"words":[
{
"boundingBox":"457,643,131,22",
"text":"CHILDREN"
}
]
},
{
"boundingBox":"423,669,197,22",
"words":[
{
"boundingBox":"423,669,54,21",
"text":"ARE"
},
{
"boundingBox":"497,669,123,22",
"text":"PRESENT"
}
]
}
]
}
],
"textAngle":0.0
}
}
Request Parameters
| Parameter | Default | Description |
|---|---|---|
| Provider | auto |
The AI service provider you want to use. The AI Service provider can be any of the following:
|
File Properties
The request sends a file over HTTPS.
| File Properties | Description |
|---|---|
| Image File Size | Maximum file size is 2 MB |
| File Format | The following image types are supported:
|
| Image Dimensions | The recommended image size is 1024 x 768 pixels (ca. 786k pixels). The total image size must not exceed 75M pixels (length x width). |
Errors
The RAPYD.AI API uses the following error codes:
| Error Code | Meaning |
|---|---|
| 400 | Bad Request -- Your request is invalid. |
| 401 | Unauthorized -- Your API key is wrong. |
| 403 | Forbidden -- The item requested is hidden for administrators only. |
| 404 | Not Found -- The specified item could not be found. |
| 405 | Method Not Allowed -- You tried to access an item with an invalid method. |
| 406 | Not Acceptable -- You requested a format that isn't json. |
| 410 | Gone -- The endpoint requested has been removed from our servers. |
| 418 | I'm a teapot. |
| 429 | Too Many Requests -- You're requesting too many services! Slow down! |
| 500 | Internal Server Error -- We had a problem with our server. Try again later. |
| 503 | Service Unavailable -- We're temporarily offline for maintenance. Please try again later. |