Plate Number Recognition with Amazon Rekognition
Read license plate number from existing video in S3
- Create an empty S3 bucket in same region of your Amazon Rekognition service, please note down your bucket name.
- Create the Amazon SNS topic, prepend the topic name with "AmazonRekognition" and note down your SNS ARN.
- Create the Amazon SQS queue, note down your SQS ARN.
- Allow SNS to send message to SQS, modify your SQS access policy:
{
"Statement": [{
"Effect":"Allow",
"Principal": {
"Service": "sns.amazonaws.com"
},
"Action":"sqs:SendMessage",
"Resource":"<YOUR-SQS-ARN>",
"Condition":{
"ArnEquals":{
"aws:SourceArn":"<YOUR-SNS-ARN>"
}
}
}]
}
- Give Amazon Rekognition Video permission to publish the completion status of a video analysis operation to the Amazon SNS topic.
- In IAM, create new policy:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"sns:Publish"
],
"Resource": "<YOUR-TOPIC-ARN>"
}
]
}
- Create new Service Role, Choose Rekognition as AWS Service. Please note service role ARN.
- Subscribe the Amazon SQS queue to the Amazon SNS topic.
- Create Cloud9 Environment with default configuration and install boto3
- Clone demo repository:
git clone https://github.com/divaga/plate-number-rekognition.git
- Go to plate-number-rekognition folder and copy sample video to your S3 bucket
aws s3 cp traffic.mp4 s3://<YOUR-S3-BUCKET-NAME>/traffic.mp4
- Open detect-text.py and change value for roleArn (from step no.4), bucket name (from step no.1) and video file name (from step no.8)
- execute detect-text.py
- For Lambda. use detect-text-lambda.py and set Lambda timeout properly.
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