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# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_face_detection_async.py
DESCRIPTION:
This sample demonstrates how to detect faces and analyze faces from an image or binary data.
USAGE:
python sample_face_detection_async.py
Set the environment variables with your own values before running this sample:
1) AZURE_FACE_API_ENDPOINT - the endpoint to your Face resource.
2) AZURE_FACE_API_ACCOUNT_KEY - your Face API key.
"""
import asyncio
import os
from dotenv import find_dotenv, load_dotenv
from shared.constants import (
CONFIGURATION_NAME_FACE_API_ACCOUNT_KEY,
CONFIGURATION_NAME_FACE_API_ENDPOINT,
DEFAULT_FACE_API_ACCOUNT_KEY,
DEFAULT_FACE_API_ENDPOINT,
TestImages,
)
from shared import helpers
from shared.helpers import beautify_json, get_logger
class DetectFaces:
def __init__(self):
load_dotenv(find_dotenv())
self.endpoint = os.getenv(CONFIGURATION_NAME_FACE_API_ENDPOINT, DEFAULT_FACE_API_ENDPOINT)
self.key = os.getenv(CONFIGURATION_NAME_FACE_API_ACCOUNT_KEY, DEFAULT_FACE_API_ACCOUNT_KEY)
self.logger = get_logger("sample_face_detection_async")
async def detect(self):
from azure.core.credentials import AzureKeyCredential
from azure.ai.vision.face.aio import FaceClient
from azure.ai.vision.face.models import (
FaceDetectionModel,
FaceRecognitionModel,
FaceAttributeTypeDetection03,
FaceAttributeTypeRecognition04,
)
async with FaceClient(endpoint=self.endpoint, credential=AzureKeyCredential(self.key)) as face_client:
sample_file_path = helpers.get_image_path(TestImages.IMAGE_DETECTION_5)
result = await face_client.detect(
helpers.read_file_content(sample_file_path),
detection_model=FaceDetectionModel.DETECTION03,
recognition_model=FaceRecognitionModel.RECOGNITION04,
return_face_id=True,
return_face_attributes=[
FaceAttributeTypeDetection03.BLUR,
FaceAttributeTypeDetection03.HEAD_POSE,
FaceAttributeTypeDetection03.MASK,
FaceAttributeTypeRecognition04.QUALITY_FOR_RECOGNITION,
],
return_face_landmarks=True,
return_recognition_model=True,
face_id_time_to_live=120,
)
self.logger.info(f"Detect faces from the file: {sample_file_path}")
for idx, face in enumerate(result):
self.logger.info(f"----- Detection result: #{idx+1} -----")
self.logger.info(f"Face: {beautify_json(face.as_dict())}")
async def detect_from_url(self):
from azure.core.credentials import AzureKeyCredential
from azure.ai.vision.face.aio import FaceClient
from azure.ai.vision.face.models import (
FaceDetectionModel,
FaceRecognitionModel,
FaceAttributeTypeDetection01,
)
async with FaceClient(endpoint=self.endpoint, credential=AzureKeyCredential(self.key)) as face_client:
sample_url = TestImages.DEFAULT_IMAGE_URL
result = await face_client.detect_from_url(
url=sample_url,
detection_model=FaceDetectionModel.DETECTION01,
recognition_model=FaceRecognitionModel.RECOGNITION04,
return_face_id=False,
return_face_attributes=[
FaceAttributeTypeDetection01.ACCESSORIES,
FaceAttributeTypeDetection01.EXPOSURE,
FaceAttributeTypeDetection01.GLASSES,
FaceAttributeTypeDetection01.NOISE,
],
)
self.logger.info(f"Detect faces from the url: {sample_url}")
for idx, face in enumerate(result):
self.logger.info(f"----- Detection result: #{idx+1} -----")
self.logger.info(f"Face: {beautify_json(face.as_dict())}")
async def main():
sample = DetectFaces()
await sample.detect()
await sample.detect_from_url()
if __name__ == "__main__":
asyncio.run(main())
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