As requested by our users, the following are the list of endpoints that is provided by PixLab for all your face detection, recognition, generation & landmarks extraction tasks. These includes:

• /facedetect: State-of-the-art face detection.
• /facelandmarks: Used for extracting facial features such as the eyes, bone, mouth coordinates and thus to Mimic the famous Snapchat filters.
• /facecompare which is used for face to face comparison. In other words, it is used for recognition.
• /facelookup: find a person’s face in a set or group of people.

Here is two working Python code to illustrate this:

1.Detect all human faces present in a given image or video frame via facedetect and extract each one of them via crop:

import requests
import json
     
    # Target image: Feel free to change to whatever image holding as many human faces you want
    img = 'http://cf.broadsheet.ie/wp-content/uploads/2015/03/jeremy-clarkson_3090507b.jpg'
     
    req = requests.get('https://api.pixlab.io/facedetect',params={
        'img': img,
        'key':'My_Pix_Key',
    })
    reply = req.json()
    if reply['status'] != 200:
        print (reply['error'])
        exit();
     
    total = len(reply['faces']) # Total detected faces
    print(str(total)+" faces were detected")
     
    # Extract each face via crop now 
    for face in reply['faces']:
        req = requests.get('https://api.pixlab.io/crop',params={
            'img':img,
            'key':'My_Pix_Key',
            'width': face['width'],
            'height': face['height'],
            'x': face['left'],
            'y': face['top']
        })
        reply = req.json()
        if reply['status'] != 200:
            print (reply['error'])
        else:
            print ("Face #"+str(face['face_id'])+" location: "+ reply['link'])

2. Detect all human faces in a given image via facedetect and apply a blur filter to each one of them via mogrify:

import requests
import json

img = 'http://anewscafe.com/wp-content/uploads/2012/05/Brave-Faces-Group-shot.jpg' 

# Detect all human faces in a given image via facedetect and blur all of them via mogrify.
req = requests.get('https://api.pixlab.io/facedetect',params={
    'img': img,
    'key':'Pix_Key',
})
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
    exit();

total = len(reply['faces']) # Total detected faces
print(str(total)+" faces were detected")
if total < 1:
    # No faces were detected, exit immediately
    exit()
# Pass the detected faces coordinates untouched to mogrify 
coordinates = reply['faces']
# Call mogrify & blur the faces
req = requests.post('https://api.pixlab.io/mogrify',headers={'Content-Type':'application/json'},data=json.dumps({
    'img': img,
    'key':'PIXLAB_API_KEY',
    'cord': coordinates #The field of interest
}))
reply = req.json()
if reply['status'] != 200:
    print (reply['error'])
else:
    print ("Blurred faces URL: "+ reply['link'])

Further code samples are available on the PixLab Github repository or refer to the PixLab Endpoints list for the official documentation.