Azure Face Recognition

main.py

# azure-cognitiveservices-vision-face==0.6.0
# image==1.5.33

import os
import json
import requests

from azure.cognitiveservices.vision.face import FaceClient
from azure.cognitiveservices.vision.face.models import DetectedFace
from msrest.authentication import CognitiveServicesCredentials
from io import BytesIO
from PIL import Image, ImageDraw

KEY = os.environ["AZURE_FACE_REC_KEY"]
ENDPOINT = os.environ["AZURE_FACE_REC_ENDPOINT"]

face_client = FaceClient(ENDPOINT, CognitiveServicesCredentials(KEY))


def getRectangle(faceDictionary):
    rect = faceDictionary.face_rectangle
    left = rect.left
    top = rect.top
    bottom = left + rect.height
    right = top + rect.width
    return ((left, top), (bottom, right))


def info(detected_face: DetectedFace):
    return {
        "face_id": detected_face.face_id,
        "face_attributes": {
            "age": detected_face.face_attributes.age,
            "gender": detected_face.face_attributes.gender,
            "smile": detected_face.face_attributes.smile,
            "facial_hair": {
                "moustache": detected_face.face_attributes.facial_hair.moustache,
                "beard": detected_face.face_attributes.facial_hair.beard,
                "sideburns": detected_face.face_attributes.facial_hair.sideburns
            },
            "glasses": detected_face.face_attributes.glasses,
            "head_pose": {
                "roll": detected_face.face_attributes.head_pose.roll,
                "yaw": detected_face.face_attributes.head_pose.yaw,
                "pitch": detected_face.face_attributes.head_pose.pitch
            },
            "emotion": {
                "anger": detected_face.face_attributes.emotion.anger,
                "contempt": detected_face.face_attributes.emotion.contempt,
                "disgust": detected_face.face_attributes.emotion.disgust,
                "fear": detected_face.face_attributes.emotion.fear,
                "happiness": detected_face.face_attributes.emotion.happiness,
                "neutral": detected_face.face_attributes.emotion.neutral,
                "sadness": detected_face.face_attributes.emotion.sadness,
                "surprise": detected_face.face_attributes.emotion.surprise,
            },
            "hair": {
                "bald": detected_face.face_attributes.hair.bald,
                "invisible": detected_face.face_attributes.hair.invisible,
                "hair_color": [{
                    "color": c.color,
                    "confidence": c.confidence
                } for c in detected_face.face_attributes.hair.hair_color]
            },
            "makeup": {
                "eye_makeup": detected_face.face_attributes.makeup.eye_makeup,
                "lip_makeup": detected_face.face_attributes.makeup.lip_makeup
            },
            "occlusion": {
                "forehead_occluded": detected_face.face_attributes.occlusion.forehead_occluded,
                "eye_occluded": detected_face.face_attributes.occlusion.eye_occluded,
                "mouth_occluded": detected_face.face_attributes.occlusion.mouth_occluded
            },
            "accessories": [
                {"type": a.type, "confidence": a.confidence} for a in detected_face.face_attributes.accessories],
            "blur": {
                "blur_level": detected_face.face_attributes.blur.blur_level,
                "value": detected_face.face_attributes.blur.value
            },
            "exposure": {
                "exposure_level": detected_face.face_attributes.exposure.exposure_level,
                "value": detected_face.face_attributes.exposure.value,
            },
            "noise": {
                "noise_level": detected_face.face_attributes.noise.noise_level,
                "value": detected_face.face_attributes.noise.value,
            },
            "mask": detected_face.face_attributes.mask,
            "quality_for_recognition": detected_face.face_attributes.quality_for_recognition
        }
    }


def detect(image_url: str):
    detected_faces = face_client.face.detect_with_url(
        url=image_url,
        return_face_attributes=[
            "age",
            "gender",
            "headPose",
            "smile",
            "facialHair",
            "glasses",
            "emotion",
            "hair",
            "makeup",
            "occlusion",
            "accessories",
            "blur",
            "exposure",
            "noise"
        ])

    if detected_faces:
        print(json.dumps([info(face) for face in detected_faces], indent=4))
        response = requests.get(image_url)
        img = Image.open(BytesIO(response.content))

        draw = ImageDraw.Draw(img)
        for face in detected_faces:
            draw.rectangle(getRectangle(face), outline="red", width=3)

        img.show()


if __name__ == "__main__":
    detect("https://raw.githubusercontent.com/Microsoft/Cognitive-Face-Windows/master/Data/detection1.jpg")

    # image from https://www.nist.gov/news-events/news/2020/07/nist-launches-studies-masks-effect-face-recognition-software
    detect("https://www.nist.gov/sites/default/files/styles/960_x_960_limit/public/images/2020/07/27/DoubleRow.png?itok=5CfcABWm")

    # image from newscientist.com
    detect("https://images.newscientist.com/wp-content/uploads/2022/02/14174128/PRI_223554170.jpg?width=800")