Image Processing ​
The following API endpoints perform analysis on an image input.
Image Prediction ​
Analyse an image and make a prediction about the primary subject depicted.
Parameters
endpoint : https://api.weburban.com/image/to-predicttop : (int) the number of top predictions returned
Example of how this would be implemented in shown below.
js
curl --location 'https://api.weburban.com/image/to-predict' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"url" : "https://www.your-website.com/image.jpg",
"top" : 3
}'curl --location 'https://api.weburban.com/image/to-predict' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"url" : "https://www.your-website.com/image.jpg",
"top" : 3
}'js
var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"imageUrl": "https://www.your-website.com/image.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/to-predict", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"imageUrl": "https://www.your-website.com/image.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/to-predict", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
Example input for this image on Wikipedia would be:
json
{
"Version": "1.0",
"Output": {
"predictions": [
{
"label": "koala",
"score": 0.996078431372549
},
{
"label": "indri",
"score": 0.00392156862745098
},
{
"label": "toilet tissue",
"score": 0.0
}
]
}
}{
"Version": "1.0",
"Output": {
"predictions": [
{
"label": "koala",
"score": 0.996078431372549
},
{
"label": "indri",
"score": 0.00392156862745098
},
{
"label": "toilet tissue",
"score": 0.0
}
]
}
}Text Recognition ​
Analyse and extract the text shown in an image. Text is extracted from an image with a response as simple as a list of text or as complex as text and positional data.
Parameters
endpoint : https://api.weburban.com/image/to-textresponse : either simple or compleximageUrl : the url of the image to be analysed
Example of how this would be implemented in shown below.
js
curl --location 'https://api.weburban.com/image/to-text' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"imageUrl" : "https://www.your-website.com/image.jpg"
}'curl --location 'https://api.weburban.com/image/to-text' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"imageUrl" : "https://www.your-website.com/image.jpg"
}'js
var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"imageUrl": "https://weburban-uploads-raw.s3.ap-southeast-2.amazonaws.com/poster.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/to-text", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"imageUrl": "https://weburban-uploads-raw.s3.ap-southeast-2.amazonaws.com/poster.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/to-text", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));Image Colour Analysis ​
Colours are extracted using k-means analysis and output as RGB values, with their frequency. This analysis will provide a summary of k colours in an image.
Parameters
endpoint : https://api.weburban.com/image/to-textk : the final number of extracted coloursimageUrl : the url of the image to be analysed
Example of how this would be implemented in shown below.
js
curl --location 'https://api.weburban.com/image/kmeans-palette' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"k" : 16,
"imageUrl" : "https://www.your-website.com/image.jpg"
}'curl --location 'https://api.weburban.com/image/kmeans-palette' \
--header 'Accept: application/json' \
--header 'x-api-key: <API Key>' \
--header 'Content-Type: application/json' \
--data '{
"k" : 16,
"imageUrl" : "https://www.your-website.com/image.jpg"
}'js
var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"k": 16,
"imageUrl": "https://www.your-website.com/image.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/kmeans-palette", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));var myHeaders = new Headers();
myHeaders.append("Accept", "application/json");
myHeaders.append("x-api-key", "<API Key>");
myHeaders.append("Content-Type", "application/json");
var raw = JSON.stringify({
"k": 16,
"imageUrl": "https://www.your-website.com/image.jpg"
});
var requestOptions = {
method: 'POST',
headers: myHeaders,
body: raw,
redirect: 'follow'
};
fetch("https://api.weburban.com/image/kmeans-palette", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));