Custom Vision is the Azure Cognitive Service to use for training custom image classification & object detection models to identify products in fashion store images. Learn why Custom Vision is the right choice over Form Recognizer, Computer Vision & Face APIs.
Table of Contents
Question
You are building a service to process images from fashion stores and identify the products of competitors. The solution will use a custom model. Which Azure Cognitive Services service should you use?
A. Custom Vision.
B. Form Recognizer.
C. Computer Vision.
D. Face.
Answer
A. Custom Vision.
Explanation
Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own custom image classification and object detection models. You can train Custom Vision to recognize specific objects and concepts in images by uploading labeled training images and tagging the objects you want to detect.
This scenario requires identifying fashion products from competitors in store images. That necessitates training a model to recognize those specific products, which is exactly what Custom Vision enables. You could upload many example images of the competitor products and tag them to teach Custom Vision to detect those products in new images.
The other options are not suitable for this use case:
- (B) Form Recognizer – Used for extracting text, key/value pairs and tables from documents and images, not product detection.
- (C) Computer Vision – Provides pre-built general image analysis models (tags, objects, brands, etc.) but cannot be trained to identify your specific products of interest.
- (D) Face – Detects and analyzes human faces in images. Not applicable for fashion product recognition.
Therefore, Custom Vision is the clear choice for building a custom computer vision model to detect competitor products in fashion store imagery. Its ability to train custom image classifiers and object detectors to recognize specific concepts makes it uniquely suited for this scenario.
Custom Vision is the appropriate Azure Cognitive Service for building a solution that processes images and identifies specific products. It allows you to train a custom model on your own dataset, making it ideal for recognizing and classifying ashion products from competitors.
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