AWS Rekognition — A simple classifier without having to build a lot of in-house or Cloud Environments — Sample Bird-Project
A few weeks ago, I set up a bird feeder and used it to capture bird images, the classifier itself was not that accurate but was doing a decent job, what I have realised is that not every time we end up with highly accurate on-board edge classification especially while learning how to implement them.
So after a few weeks, there were a lot of images some of them sure enough had birds while some of them were taken in Pitch Dark and am not even sure what made the classifier figure out a birdie in the snapshot from the camera.
Now for me in order to make an Image, I have to rely on a re-classifier doing the job for me, initially, I thought I will write a lambda-based classifier as a learning experiment, but then I thought it was a one-time process every 6 months or so, so I went ahead with a managed service option and in this case, its AWS Rekognition, which is quite amazing.
https://aws.amazon.com/rekognition/
Code Snippet used for Classification
import os
import concurrent.futures
import boto3
def detect_birds(image_path):
# Configure AWS credentials and region
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