𝐂𝐎𝐌𝐏𝐔𝐓𝐄𝐑 𝐕𝐈𝐒𝐈𝐎𝐍 is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models machines can accurately identify and classify objects and then react to what they "see". It is the field of computer science that focuses on replicating parts of the complexity of the human vision system and enabling computers to identify and process objects in images and videos.
𝑪𝑶𝑴𝑷𝑼𝑻𝑬𝑹 𝑽𝑰𝑺𝑰𝑶𝑵 𝑺𝑬𝑹𝑰𝑬𝑺
Image classification is used to categorize whether an object is present in the likelihood of an image. Feature extraction is a part of the dimensionality reduction process, in which, an initial set of the raw data is divided and reduced into more manageable groups. Image classification is the process of categorizing and labeling groups of pixels or vectors within an image based on specific rules.
Object Detection is used to recognize the object with a bounding box in an image. Object detection is an important computer vision task used to detect instances of visual objects of certain classes (for example, humans, animals, cars, or buildings) in digital images such as photos or video frames. The goal of object detection is to develop computational models that provide the most fundamental information needed by computer vision applications.
Instance Segmentation is identifying each object instance for every known object within an image. Instance segmentation assigns a label to each pixel of the image. Instance segmentation is the task of detecting and delineating each distinct object of interest appearing in an image.
Python 6559 Version:v2.3.0 License: Permissive (Apache-2.0)