# 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())