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Deploying computer vision model as api using aws lambda and api gateway
- 1. 1 | 5 0 Deploying Computer Vision Model as an API using AWS Lambda & API Gateway
- 2. 2 | 5 0 Topic Deploying Computer Vision Model as an API using AWS Lambda & API Gateway 2 | 5 0 Speaker SHIRISH GUPTA HEAD – DATA SCIENCE & PARTNERSHIPS AT LOAN2GROW
- 3. 3 | 5 0 “Awesome. You have created a great machine learning algorithm. Am impressed by the accuracy and love the technique. How can we implement it in our system?” Is this something you have heard multiple times during a client or business meeting but never been able to truthfully answer it? Worry not, this is probably faced by 90% (to be conservative) of fellow data scientists. And AWS has many solutions for it. One of them being — “AWS lambda function integrated with Amazon API gateway”
- 4. 4 | 5 04 | 5 0 • What are AWS Lambda & Amazon API ? • Overview of our approach • Hands-On Training • Login to AWS Lambda • Understand & create a lambda_function • Download & define layers(aka dependencies) • Configure Amazon API gateway • Deploy the API and test it using Postman or Curl Agenda for Today
- 5. 5 | 5 0 AWS Lambda AWS Lambda is an event-driven, serverless computing platform provided by Amazon as a part of Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. The concept of serverless computing refers to the idea that you don’t need to maintain your own servers to run these functions. Which means you can just upload your codes (Python, Node.js, Go, .NET, Java, Ruby) and Lambda will manage other things like runtime, scaling, load balancing, etc. Amazon API Amazon API Gateway is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale. APIs act as the front door for applications to access data, business logic, or functionality from your backend services. Using API Gateway, we can create RESTful APIs and WebSocket APIs that enable real- time two-way communication applications. API Gateway supports containerized and serverless workloads, as well as web applications.
- 6. 6 | 5 0 Overview of our approa • Write a simple OCR code using OpenCV + Tesseract algorithm in Python language • Configure the algorithm in AWS Lambda • Deploy it as an API on Amazon API gateway 6 | 5 0 OCR or Optical character recognition or optical character reader is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo or from subtitle text superimposed on an image.
- 7. 7 | 5 0 OCR or Optical Character RecognitionThe electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo or from subtitle text superimposed on an image.
- 8. 8 | 5 0 Important Notes • The workshop will require you to upload few python libraries as zip files. You can download them from the following link • https://implayers.s3.amazonaws.com/Pillow.zip • https://implayers.s3.amazonaws.com/tesseract- layer.zip • https://implayers.s3.amazonaws.com/pytesseract%3D %3D0.3.3.zip • Python codes & sample photos to test https://drive.google.com/drive/folders/1jVXiI1QzOwaqW ggY-kDGE4WTtsd2mbX5?usp=sharing • Please refer to the following blog for other queries https://towardsdatascience.com/aws-lambda-amazon- api-gateway-not-as-daunting-as-they-sound-part-1- d77b92f53626 Pre-requisites • Python development experience • Basics on Computer Vision and OCR • Activated AWS account (You might need to enter your credit card details to activate the account. Don’t worry you won’t be charged for the same)
- 9. 9 | 5 0 Let’s jump into the workshop
- 10. 1 0 | 5 0 Lambda_Function The code (here: python) that runs on AWS Lambda is uploaded as a Lambda function • Event represents the event or trigger that caused the invocation of the lambda. It’s like the input to the function. eg: Lambda function can be triggered by an upload to S3 or by passing some input/data via API Gateway. • Context Provides information about the invocation, and execution environment of your lambda. Can be used to check the memory allocation or to retrieve the number of milliseconds left before the execution times out. It’s like extra or meta info provided by AWS to understand function’s runtime. Layers • Although we have created the lambda function, it won’t execute or run right away. The reason is that we haven’t downloaded or installed the necessary libraries(dependencies) required for the code to run. • Like in a normal environment, we need to pip or conda install the libraries, we will need to do the same thing for AWS lambda. We do that by adding layers to our AWS lambda • A ZIP archive that contains libraries, a custom runtime, or other dependencies. With layers, you can use libraries in your function without needing to include them in your deployment package
- 11. 1 1 | 5 0 Curl Command curl -X POST --data-binary @bookpage.jpg https://kglyy5173l.execute-api.us-east- 1.amazonaws.com/Testing
- 12. 1 2 | 5 0 [email protected] https://www.facebook.com/shirish .gupta.180/ https://www.linkedin.com/in/shirish -gupta-ba003742/
- 13. 1 3 | 5 0 Thank you
- 14. 1 4 | 5 0 Questions