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---
title: Object Detection Lambda
emoji: 🌖
colorFrom: purple
colorTo: green
sdk: gradio
sdk_version: 5.5.0
app_file: app.py
pinned: false
short_description: Object detection Lambda
---
# Object detection via AWS Lambda
<b>Aim: AI-driven object detection task</b>
- Front-end: user interface via Gradio library
- Back-end: use of AWS Lambda function to run deployed ML models
## Local development
### 1. Building the docker image
bash
> docker build -t object-detection-lambda .
### 2. Running the docker container locally
bash
> docker run --name object-detection-lambda-cont -p 8080:8080 object-detection-lambda
### 3. Execution via user interface
Use of Gradio library for web interface
<b>Note:</b> The environment variable ```AWS_API``` should point to the local container
> export AWS_API=http://localhost:8080
Command line for execution:
> python3 app.py
The Gradio web application should now be accessible at http://localhost:7860
### 4. Execution via command line:
Example of a prediction request
bash
> encoded_image=$(base64 -i ./tests/data/boats.jpg)
> curl -X POST "http://localhost:8080/2015-03-31/functions/function/invocations" \
> -H "Content-Type: application/json" \
> -d '{"body": "'"$encoded_image"'", "isBase64Encoded": true, "model":"yolos-small"}'
python
> python3 inference_api.py \
> --api http://localhost:8080/2015-03-31/functions/function/invocations \
> --file ./tests/data/boats.jpg \
> --model yolos-small
## Deployment to AWS
### Pushing the docker container to AWS ECR
Steps:
- Create new ECR Repository via aws console
Example: ```object-detection-lambda```
- Optional for aws cli configuration (to run above commands):
> aws configure
- Authenticate Docker client to the Amazon ECR registry
> aws ecr get-login-password --region <aws_region> | docker login --username AWS --password-stdin <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com
- Tag local docker image with the Amazon ECR registry and repository
> docker tag object-detection-lambda:latest <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/object-detection-lambda:latest
- Push docker image to ECR
> docker push <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/object-detection-lambda:latest
[Link to AWS Documention](https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-push-ecr-image.html)
### Creating and testing a Lambda function
<b>Steps</b>:
- Create function from container image
Example name: ```object-detection```
- Notes: the API endpoint will use the ```lambda_function.py``` file and ```lambda_hander``` function
- Test the lambda via the AWS console
Advanced notes:
- Steps to update the Lambda function with latest container via aws cli:
> aws lambda update-function-code --function-name object-detection --image-uri <aws_account_id>.dkr.ecr.<aws_region>.amazonaws.com/object-detection-lambda:latest
### Creating a REST API via API Gateway
<b>Steps</b>:
- Create a new ```Rest API``` (e.g. ```object-detection-api```)
- Add a new resource to the API (e.g. ```/detect```)
- Add a ```POST``` method to the resource
- Integrate the Lambda function to the API
- Notes: currently using proxy integration option unchecked
- Deploy API with a specific stage (e.g. ```dev``` stage)
Example AWS API Endpoint:
```https://<api_id>.execute-api.<aws_region>.amazonaws.com/dev/detect```
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