In this article, we will explore Microsoft Azure’s Computer Vision API and Custom Vision API, two robust tools for image analysis and processing.
What is Computer Vision API?
The Computer Vision API is a pre-trained, readily deployable solution that provides a variety of sophisticated image processing capabilities without requiring additional setup. The system offers features such as image detection, object spotting, text retrieval, and facial identification.
The Computer Vision API allows customers to easily include advanced image analysis capabilities into their applications, even without substantial expertise in machine learning or computer vision methods. This software is specifically intended to effectively process a diverse range of image formats and situations, making it suited for a wide range of applications, including automated content moderation and intelligent image tagging.
Features of Computer Vision API
- Computer Vision API is a predefined model that is ready to use and it does not require the expertise or knowledge to start working with.
- Computer Vision API has well-developed APIs with proper documentation and examples for integrating into your use cases.
- Computer Vision API requires less time as it does not require dataset preparation, model training, evaluation, testing, or deployment.
When we should use Computer Vision API and why?
- Rapid Prototyping and Proof of Concept: The Computer Vision API allows for quick integration of robust image processing capabilities, using pre-trained models. This eliminates the need to design custom models, enabling focus on core application features without the complexities of model training and optimization.
- Scalability and Cost-Effectiveness: The API offers scalability and cost-efficiency, automatically adjusting to varying workloads without additional setup. With cloud infrastructure hosting the API, you only pay for the services you use, eliminating the expenses of maintaining your own infrastructure for image analysis tasks.
- Seamless Integration: Integrating image analysis capabilities into existing systems, workflows, or applications is seamless with the Computer Vision API. It provides RESTful endpoints and SDKs for multiple programming languages, enabling easy integration into your preferred development environment. This minimizes development time and effort, allowing for quick upgrades and improved user experiences.
What is Custom Vision API?
The Custom Vision API is designed for situations where customers require training custom machine learning models that are specifically suited for their individual picture classification or object identification needs.
The platform offers an intuitive interface for generating, instructing, and implementing personalized models for picture classification and object identification. Users have the ability to submit their own photos that have been labeled, utilize advanced machine learning techniques to train a model, and seamlessly incorporate the trained model into their apps utilizing REST APIs.
The Custom Vision API enables users to develop precise models tailored to their individual needs, making it well-suited for applications that require specialized picture recognition, such as product identification or quality control in manufacturing.
Features of Custom Vision API
- Customization: Enables users to train custom models using their own image datasets.
- Fine-tuning: Allows fine-tuning of models to improve accuracy and performance.
- Integration: Offers SDKs and APIs for seamless integration into various applications and platforms.
When we should use Custom vision API and why ?
- Unique Issue: You encounter a highly particular quandary in image analysis that is not resolved by generic pre-made solutions.
- Precision Requirements: Your application necessitates a high level of accuracy that may not be fulfilled by pre-existing APIs.
- Specialized Domain: You are working in a field that has very unique and easily recognizable visual features, such as medical imaging or manufacturing error identification.
Key Differences between Custom Vision API vs Computer vision API
Computer Vision API is suitable for general-purpose image analysis tasks, whereas Custom Vision API is ideal for specialized and industry-specific applications that require customized image classification or object detection. Let’s explore more differences between Computer Vision API and Custom Vision API.
|
Feature |
Custom Vision API |
Computer Vision API |
|---|---|---|
|
Customization |
Allows training custom image classification models |
Pre-trained models for common image analysis tasks |
|
Ease of Use |
User-friendly interface for training custom models |
Straightforward integration with pre-trained models |
|
Integration |
Integrates with Azure services and other platforms |
Seamless integration with Azure services and others |
|
Scalability |
Scales according to the demands of your application |
Scalable to handle large-scale image analysis tasks |
|
Cross-Platform Support |
Supports various platforms including mobile and web |
Versatile for integration into different applications |
|
Pre-Trained Models |
No pre-trained models, focuses on custom models |
Offers pre-trained models for common tasks |
|
OCR Functionality |
Limited OCR capabilities |
Robust OCR capabilities for extracting text from images |
|
Cost-Effectiveness |
Pay-as-you-go pricing model for usage |
Pay-as-you-go pricing model for services used |
Thus, we can decide according to our requirement which to use when.