Introduction

Azure Custom Vision is a cloud-based service provided by Microsoft Azure that enables you to build and deploy custom image recognition models. It allows you to train machine learning models to recognize specific objects or categories within images. In this guide, we will explore the key concepts of Azure Custom Vision, its benefits, and provide sample code to help you get started with image recognition.


Key Concepts

Before delving into Azure Custom Vision, it's important to understand some key concepts:

  • Custom Vision: Custom Vision is a platform for building and training custom machine learning models for image recognition.
  • Training Data: Training data is a set of labeled images used to teach the model to recognize specific objects or categories.
  • Predictions: Predictions are the model's output when presented with new, unlabeled images.
  • API: An API (Application Programming Interface) allows developers to integrate Custom Vision into their applications for image recognition.

Using Azure Custom Vision

To get started with Azure Custom Vision for image recognition, follow these steps:

  1. Set up an Azure account if you don't have one already.
  2. Create a Custom Vision resource in the Azure Portal.
  3. Collect and prepare training data with labeled images.
  4. Use the Custom Vision portal to train your model, evaluate its performance, and export it for use in your application.

Sample Code: Using the Custom Vision API

Here's an example of using Python to make predictions with an Azure Custom Vision model using the API:

import requests
import json
# Define your API endpoint and prediction key
endpoint = "Your-Endpoint-URL"
prediction_key = "Your-Prediction-Key"
# Specify the image URL for prediction
image_url = "https://example.com/your-image.jpg"
# Create the API request
headers = {
    "Prediction-Key": prediction_key,
    "Content-Type": "application/json"
}
data = {
    "url": image_url
}
response = requests.post(f"{endpoint}/predict", headers=headers, json=data)
results = response.json()
print(json.dumps(results, indent=4))

Benefits of Azure Custom Vision

Azure Custom Vision offers several benefits, including:

  • Customizable machine learning models for specific image recognition tasks.
  • Integration with applications for real-time image recognition.
  • Support for image classification, object detection, and more.
  • Scalability and reliability with Azure's cloud infrastructure.

Conclusion

Azure Custom Vision simplifies the process of building and deploying custom image recognition models. By understanding the key concepts and using sample code, you can leverage this service to build applications that can recognize and classify objects within images.