Object Detection using Azure Cognitive Service for Computer Vision
Object detection is a form of machine learning based computer vision in which a model is trained to recognize individual types of objects in an image, and to identify their location in the image.
An object detection model returns the following information:
- The class of each object identified in the image.
- The probability score of the object classification (which you can interpret as the confidence of the predicted class being correct).
- The coordinates of a bounding box for each object.
Object Detection belongs to advanced computer vision and can be performed in the following ways:
- Azure Cognitive Services for Vision
- Build own advanced computer vision models.
In this project we will be utilising Azure Computer Vision
service to process images for object-detection.
- Python 3.X version:
- Microsoft Azure Account
- Editor of choice:
- Jupyter Notebook comes packaged with Conda distribution
- Google Colab
-
Sign-in to your Microsoft Azure account.
-
Create a Resource Group (in a region closest to your location) to logically contain your Azure Resources.
-
Create a Computer Vision service inside the resource group created above.
-
Copy the
Keys
andEndpoint
from theComputer Vision
resource and substitute them forsubscription_key
andendpoint
respectively. This will be used to authenticate the computer-vision-client to the computer vision resource. -
Run the provided notebook for performing object-detection.