Deploying a classification model on AWS Lambda with Docker and FastAPI

Create and deploy a model to classify selfies and IDs photos on AWS Lambda with Tensorflow, FastAPI and Docker. The entire explation of the projects can be found at my blog post.

To run the api:

import uvicorn

if __name__ == "__main__":
    uvicorn.run("doc_classifier.main:app", host="0.0.0.0", port=8000, reload=True)

To test it with Python:

import base64
import json
import requests

encoded_string = base64.b64encode(open("experiments/test_doc_2.jpg", "rb").read())
encoded_string_utf = encoded_string.decode("utf-8")

print(
     requests.post(
         "http://localhost:8000/classifier",
         json={"input_photo": encoded_string_utf, "leadId": "f8cad38c-c4f3-4f50-ab23-5262033bfef1"},
     ).text
 )```