README
¶
infer-lambda-api
An example image recognition API using infer and AWS Lambda + API Gateway.
Overview
This project serves as an example for how to quickly deploy a Go Image Recognition API using Terraform and AWS. It uses infer, a Go package that provides abstractions for interacting with TensorFlow models.
Setup
Build
Lambda functions require a zipped application containing the executable and any supporting assets. A Dockerfile has been provided to make the build step easy.
$ make build
Once executed, a deployment.zip file will be included in the root of the project. The zip includes:
- Lambda Function as a Go binary
- TensorFlow bindings
- Model file
- Labels file
Deploy
Once the application has been built, it's ready to be deployed. The application is deployed as a Lambda function and uses API Gateway to provide HTTP access. Terraform config has been included to make setup easy.
For an in-depth tutorial for using Terraform and Lambda/API Gateway, see here.
First, make sure you have a valid AWS account and have installed Terraform.
From there, initialize the Terraform build and apply. Note: This will incur fees.
$ cd terraform
$ terraform init
$ terraform apply
This creates the following
- S3 Bucket and Object containing deployment zip
- Lambda Function
- IAM Role
- API Gateway Rest API
- API Gateway Methods + Integrations into Lambda
Together, this results in a Lambda function that is accessible via HTTP over API Gateway.
Teardown
$ terraform destroy
A version number will be required. Any semver value works.
Usage
Locate the API Gateway Endpoint.
$ cd terraform
$ terraform output endpoint
Execute a request, example using curl below.
$ curl --upload-file "/path/to/img.png" "ENDPOINT" -H "Content-Type: image/png"
[
{
"Class": "thing",
"Score": 0.875
},
...
]
Notes
- Lambda Function memory size set to 512mb. Any lower and the TF model could not execute.
- Startup time on first request can often be slow.
Directories