Computer vision
100 XP
Key points to understand about computer vision include:
- Computer vision is accomplished by using large numbers of images to train a model.
- Image classification is a form of computer vision in which a model is trained with images that are labeled with the main subject of the image (in other words, what it's an image of) so that it can analyze unlabeled images and predict the most appropriate label - identifying the subject of the image.
- Object detection is a form of computer vision in which the model is trained to identify the location of specific objects in an image.
- There are more advanced forms of computer vision - for example, semantic segmentation is an advanced form of object detection where, rather than indicate an object's location by drawing a box around it, the model can identify the individual pixels in the image that belong to a particular object.
- You can combine computer vision and language models to create a multi-modal model that combines computer vision and generative AI capabilities.
Computer vision scenarios
Common uses of computer vision include:
- Auto-captioning or tag-generation for photographs.
- Visual search.
- Monitoring stock levels or identifying items for checkout in retail scenarios.
- Security video monitoring.
- Authentication through facial recognition.
- Robotics and self-driving vehicles.