In my first blog, ‘Bird Recognition App using Microsoft Custom Vision AI and Power BI’, we looked at the intriguing behaviors and attributes of birds using Power BI. This inspired me to create an ‘AI for birds’ web app’ using Azure Custom Vision along with a phone app using Power Apps and an iPhone / Android platform that could identify a bird in real-time. I created this app to raise awareness of the heart-breaking reality which most birds face around the world.

In this blog, let’s go behind the scenes and take a look at the journey of how this was created.

What is Azure Custom Vision?

_Azure Custom Vision is an image recognition AI service part of _Azure Cognitive Services that enables you to build, deploy, and improve your own image identifiers. An image identifier applies labels (which represent classes or objects) to images, according to their visual characteristics. It allows you to specify the labels and train custom models to detect them.

What does Azure Custom Vision do?

The Custom Vision service uses a Machine Learning algorithm to analyze images. You can submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time of the submission. Then, the algorithm trains to this data and calculates its accuracy by testing itself on those same images.

Once the algorithm is trained, you can run a test, retrain, and eventually use it in your image recognition app to classify new images. You can also export the model itself for offline use.

How does it work?

1. Upload images - Bring your own labelled images or use Custom Vision to quickly add tags to any unlabelled images.

2. Train the model - Use your labelled images to teach Custom Vision the concepts you care about.

3. Evaluate the result - Use simple REST API calls to quickly tag images with your new custom computer vision model.

The Custom Vision Service uses machine learning to classify the images you upload. The only thing that is required to do is specify the correct tag for each image. You can also tag thousands of images at a time. The AI algorithm is very powerful and once the model is trained, you can use the same model to classify new images according to the needs of the app.

#artificial intelligence #azure machine learning #classification