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Last updated: 2024-11-19
Here are some of the key features of the Azure AI Vision service:
- Optical Character Recognition (OCR): The OCR service extracted text from images. It used deep-learning-based models and worked with text on various surfaces and backgrounds.
- Image Analysis: The Image Analysis service extracted many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions.
- Face: The Face service provided AI algorithms that detected, recognized, and analyzed human faces in images.
- Video Analysis: Video Analysis included video-related features like Spatial Analysis and Video Retrieval.
| Azure Computer Vision vs Azure Custom Vision | Azure Computer Vision | Azure Custom Vision |
|---|---|---|
| Azure Computer Vision and Azure Custom Vision are both services that deal with image analysis, but they serve different purposes and offer different levels of customization. In summary, while Azure Computer Vision provides a wide range of pre-trained models for various tasks, Azure Custom Vision offers more customization but requires your own data for training. |
Azure Computer Vision is a pre-trained model that provides several general services: - Image Classification: The API gives a number of tags that classify the image along with a confidence score. - Content Moderation: The API can determine if the image meets certain criteria like being adult or racy content. - OCR: The API can read text within the images, including handwritten text. - Facial Recognition: This API can recognize the faces of celebrities or other well-known people within images. - Landmark Recognition: This API can recognize landmarks within images. |
Azure Custom Vision is a service that allows you to build, deploy, and improve your own image classifiers. You can specify your own labels and train custom models to detect them. It primarily supports image classification and object detection. However, unlike Azure Computer Vision, you need to provide your own images for training. |
Note
Here are some use cases:
- Product Recommendations: Analyze user's shopping behavior and recommend similar products.
- Inventory Management: Identify products on the shelf and track inventory in real time.
- Medical Imaging: Assist radiologists by identifying patterns in X-rays, MRIs, CT scans, etc.
- Patient Monitoring: Monitor patient's health condition through visual data.
- Quality Control: Detect defects in products on the assembly line.
- Safety Compliance: Ensure workers are wearing appropriate safety gear.
- Crop Health Monitoring: Identify unhealthy plants or areas needing attention based on drone or satellite imagery.
- Yield Estimation: Estimate crop yield based on visual data of the field.
- Traffic Management: Analyze traffic patterns and optimize traffic signal timings.
- Vehicle Identification: Identify vehicle types, license plates, etc. for toll collection or security purposes.
- Virtual Learning: Enhance virtual learning experiences with visual aids.
- Accessibility: Help visually impaired students by describing visual content.
