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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_find_similar_faces_async.py
DESCRIPTION:
This sample demonstrates how to find similar faces from a specified list of face ids or a largeFaceList.
USAGE:
python sample_find_similar_faces_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 FindSimilarFaces:
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_findsimilar_faces_async")
async def find_similar_from_face_ids(self):
from azure.core.credentials import AzureKeyCredential
from azure.ai.vision.face.aio import FaceClient
from azure.ai.vision.face.models import FaceDetectionModel, FaceRecognitionModel
async with FaceClient(endpoint=self.endpoint, credential=AzureKeyCredential(self.key)) as face_client:
# Detect faces from 'IMAGE_NINE_FACES'
nine_faces_file_path = helpers.get_image_path(TestImages.IMAGE_NINE_FACES)
detect_result1 = await face_client.detect(
helpers.read_file_content(nine_faces_file_path),
detection_model=FaceDetectionModel.DETECTION03,
recognition_model=FaceRecognitionModel.RECOGNITION04,
return_face_id=True,
)
face_ids = [str(face.face_id) for face in detect_result1]
self.logger.info(f"Detect {len(face_ids)} faces from the file '{nine_faces_file_path}': {face_ids}")
# Detect face from 'IMAGE_FINDSIMILAR'
find_similar_file_path = helpers.get_image_path(TestImages.IMAGE_FINDSIMILAR)
detect_result2 = await face_client.detect(
helpers.read_file_content(find_similar_file_path),
detection_model=FaceDetectionModel.DETECTION03,
recognition_model=FaceRecognitionModel.RECOGNITION04,
return_face_id=True,
)
assert len(detect_result2) == 1
face_id = str(detect_result2[0].face_id)
self.logger.info(f"Detect 1 face from the file '{find_similar_file_path}': {face_id}")
# Call Find Similar
# The default find similar mode is MATCH_PERSON
find_similar_result1 = await face_client.find_similar(face_id=face_id, face_ids=face_ids)
self.logger.info("Find Similar with matchPerson mode:")
for r in find_similar_result1:
self.logger.info(f"{beautify_json(r.as_dict())}")
async def find_similar_from_large_face_list(self):
from azure.core.credentials import AzureKeyCredential
from azure.ai.vision.face.aio import FaceAdministrationClient, FaceClient
from azure.ai.vision.face.models import (
FaceDetectionModel,
FaceRecognitionModel,
FindSimilarMatchMode,
)
async with FaceAdministrationClient(
endpoint=self.endpoint, credential=AzureKeyCredential(self.key)
) as face_admin_client, FaceClient(
endpoint=self.endpoint, credential=AzureKeyCredential(self.key)
) as face_client:
large_face_list_id = "lfl01"
# Prepare a LargeFaceList which contains several faces.
self.logger.info(f"Create a LargeFaceList, id = {large_face_list_id}")
await face_admin_client.large_face_list.create(
large_face_list_id,
name="List of Face",
user_data="Large Face List for Test",
recognition_model=FaceRecognitionModel.RECOGNITION04,
)
# Add faces into the largeFaceList
self.logger.info(f"Add faces into the LargeFaceList {large_face_list_id}")
await face_admin_client.large_face_list.add_face(
large_face_list_id,
helpers.read_file_content(helpers.get_image_path(TestImages.IMAGE_FAMILY_1_MOM_1)),
detection_model=FaceDetectionModel.DETECTION02,
user_data="Lady1-1",
)
await face_admin_client.large_face_list.add_face(
large_face_list_id,
helpers.read_file_content(helpers.get_image_path(TestImages.IMAGE_FAMILY_1_MOM_2)),
detection_model=FaceDetectionModel.DETECTION02,
user_data="Lady1-2",
)
await face_admin_client.large_face_list.add_face(
large_face_list_id,
helpers.read_file_content(helpers.get_image_path(TestImages.IMAGE_FAMILY_2_LADY_1)),
detection_model=FaceDetectionModel.DETECTION02,
user_data="Lady2-1",
)
await face_admin_client.large_face_list.add_face(
large_face_list_id,
helpers.read_file_content(helpers.get_image_path(TestImages.IMAGE_FAMILY_2_LADY_2)),
detection_model=FaceDetectionModel.DETECTION02,
user_data="Lady2-2",
)
await face_admin_client.large_face_list.add_face(
large_face_list_id,
helpers.read_file_content(helpers.get_image_path(TestImages.IMAGE_FAMILY_3_LADY_1)),
detection_model=FaceDetectionModel.DETECTION02,
user_data="Lady3-1",
)
# The LargeFaceList should be trained to make it ready for find similar operation.
self.logger.info(f"Train the LargeFaceList {large_face_list_id}, and wait until the operation completes.")
poller = await face_admin_client.large_face_list.begin_train(large_face_list_id, polling_interval=30)
await poller.wait() # Keep polling until the "Train" operation completes.
# Detect face from 'IMAGE_FINDSIMILAR'
find_similar_file_path = helpers.get_image_path(TestImages.IMAGE_FINDSIMILAR)
detect_result = await face_client.detect(
helpers.read_file_content(find_similar_file_path),
detection_model=FaceDetectionModel.DETECTION03,
recognition_model=FaceRecognitionModel.RECOGNITION04,
return_face_id=True,
)
assert len(detect_result) == 1
face_id = str(detect_result[0].face_id)
self.logger.info(f"Detect 1 face from the file '{find_similar_file_path}': {face_id}")
# Call Find Similar
find_similar_result = await face_client.find_similar_from_large_face_list(
face_id=face_id,
large_face_list_id=large_face_list_id,
max_num_of_candidates_returned=3,
mode=FindSimilarMatchMode.MATCH_FACE,
)
self.logger.info("Find Similar with matchFace mode:")
for r in find_similar_result:
self.logger.info(f"{beautify_json(r.as_dict())}")
# Clean up: Remove the LargeFaceList
self.logger.info(f"Remove the LargeFaceList {large_face_list_id}")
await face_admin_client.large_face_list.delete(large_face_list_id)
async def main():
sample = FindSimilarFaces()
await sample.find_similar_from_face_ids()
await sample.find_similar_from_large_face_list()
if __name__ == "__main__":
asyncio.run(main())
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