我创建了一个集合名称,现在我想将图像添加到集合中,这样我就可以像compare_faces一样运行它们。问题是,当我运行像detect_faces这样的函数时,我不知道如何保存到我创建的特定集合。 AWS文档未显示将CollectionId添加到任何这些函数的语法,以便将我检测到的面部保存到集合中,以便稍后将其用于比较目的。
答案 0 :(得分:1)
这是您将带有元数据的图像上传到s3的方式,每张图片应该只包含一个面,其中一个名称作为元数据提供
import boto3
s3 = boto3.resource('s3')
# Get list of objects for indexing
images=[('image01.jpeg','Albert Einstein'),
('image02.jpeg','Candy'),
('image03.jpeg','Armstrong'),
('image04.jpeg','Ram'),
('image05.jpeg','Peter'),
('image06.jpeg','Shashank')
]
# Iterate through list to upload objects to S3
for image in images:
file = open(image[0],'rb')
object = s3.Object('rekognition-pictures','index/'+ image[0])
ret = object.put(Body=file,
Metadata={'FullName':image[1]}
)
现在你必须使用lambda函数进行索引,它将完成你的工作并将面存储到你的rekognition集合中,并为dynamodb表中的每个面存储一个名称,这两个你可以在以后使用其他api&#时引用它们39;比较面孔
from __future__ import print_function
import boto3
from decimal import Decimal
import json
import urllib
print('Loading function')
dynamodb = boto3.client('dynamodb')
s3 = boto3.client('s3')
rekognition = boto3.client('rekognition')
# --------------- Helper Functions ------------------
def index_faces(bucket, key):
response = rekognition.index_faces(
Image={"S3Object":
{"Bucket": bucket,
"Name": key}},
CollectionId="family_collection")
return response
def update_index(tableName,faceId, fullName):
response = dynamodb.put_item(
TableName=tableName,
Item={
'RekognitionId': {'S': faceId},
'FullName': {'S': fullName}
}
)
# --------------- Main handler ------------------
def lambda_handler(event, context):
# Get the object from the event
bucket = event['Records'][0]['s3']['bucket']['name']
key = urllib.unquote_plus(
event['Records'][0]['s3']['object']['key'].encode('utf8'))
try:
# Calls Amazon Rekognition IndexFaces API to detect faces in S3 object
# to index faces into specified collection
response = index_faces(bucket, key)
# Commit faceId and full name object metadata to DynamoDB
if response['ResponseMetadata']['HTTPStatusCode'] == 200:
faceId = response['FaceRecords'][0]['Face']['FaceId']
ret = s3.head_object(Bucket=bucket,Key=key)
personFullName = ret['Metadata']['fullname']
update_index('family_collection',faceId,personFullName)
# Print response to console
print(response)
return response
except Exception as e:
print(e)
print("Error processing object {} from bucket {}. ".format(key, bucket))
raise e