Step 1. Install and run CompreFace using our Getting Started guide
Step 2. You need to sign up for the system and login into the account you’ve just created or use the one you already have. After that, the system redirects you to the main page.
Step 3. Create an application (left section) using the “Create” link at the bottom of the page. An application is where you can create and manage your Face Collections.
Step 4. Enter your application by clicking on its name. Here, you have two options: adding new users and managing their access roles or creating new Face Services.
Step 5. To recognize subjects among the known subjects, you need to create a Face Recognition Service. After creating a new Face Service, you can see it in the Services List with an appropriate name and API key. After this step, you can look at our demos.
Step 6. To add known subjects to your Face Collection of Face Recognition Service, you can use REST API. Once you’ve uploaded all known faces, you can test the collection using REST API or the TEST page. We recommend using an image size no higher than 5MB, as it could slow down the request process. The supported image formats include JPEG/PNG/JPG/ICO/BMP/GIF/TIF/TIFF.
Step 7. Upload your photo and let our open-source face recognition system match the image against the Face Collection. Using a UI for face recognition, you can see the original picture with marks near every face. Using REST API, you receive a response in JSON format.
JSON contains an array of objects that represent each recognized face. Each object has the following fields:
subject - person identifiersimilarity - gives a confidence that this is the found subjectprobability - gives the confidence that this is a facex_min, x_max, y_min, y_max are coordinates of the face in
the image
{
"result": [
{
"box": {
"probability": 0.99583,
"x_max": 551,
"y_max": 364,
"x_min": 319,
"y_min": 55
},
"subjects": [
{
"similarity": 0.99593,
"subject": "lisan"
}
]
},
{
}
]
}
This demo shows the most simple example of Face recognition service usage. To run a demo, open an HTML file in a browser. API key for this demo was created on step 5 of How to Use CompreFace
This demo shows the most simple webcam demo for Face recognition service. To run a demo, open an HTML file in a browser. API key for this demo was created on step 5 of How to Use CompreFace
Here is a JavaScript code snippet that loads a new image to your Face Collection:
function saveNewImageToFaceCollection(elem) {
let subject = encodeURIComponent(document.getElementById("subject").value);
let apiKey = document.getElementById("apiKey").value;
let formData = new FormData();
let photo = elem.files[0];
formData.append("file", photo);
fetch('http://localhost:8000/api/v1/recognition/faces/?subject=' + subject,
{
method: "POST",
headers: {
"x-api-key": apiKey
},
body: formData
}
).then(r => r.json()).then(
function (data) {
console.log('New example was saved', data);
})
.catch(function (error) {
alert('Request failed: ' + JSON.stringify(error));
});
}
This function sends the image to our server and shows results in a text area:
function recognizeFace(elem) {
let apiKey = document.getElementById("apiKey").value;
let formData = new FormData();
let photo = elem.files[0];
formData.append("file", photo);
fetch('http://localhost:8000/api/v1/recognition/recognize',
{
method: "POST",
headers: {
"x-api-key": apiKey
},
body: formData
}
).then(r => r.json()).then(
function (data) {
document.getElementById("result").innerHTML = JSON.stringify(data);
})
.catch(function (error) {
alert('Request failed: ' + JSON.stringify(error));
});
}