computer vision (CV)

Computer vision (CV) is a field of computer science and artificial intelligence that enables computers to derive meaning from images and video, such as recognizing which objects a picture contains and where they sit in the frame.

The field is organized around a set of standard tasks:

• Image classification, which assigns one or more labels to a whole image
• Object detection, which locates each object with a bounding box and a label
• Segmentation, which labels individual pixels as belonging to a class or an object instance
• Keypoint and pose estimation, which locates specific points such as body joints
• Depth estimation and object tracking, which extend the same ideas to distance and to video frames

What separates these tasks is how finely they describe the picture. The switcher below re-annotates one scene under the first four tasks and shows the data that each one returns:

Early systems relied on hand-engineered features such as edges and corners. Modern ones learn features from data, first with convolutional networks and more recently with vision transformers, which split an image into fixed-size patches and apply self-attention across them.

Multimodal large language models now fold many of these tasks into the same prompt-driven interface used for text, describing a scene or reading a chart on request. OpenCV and torchvision remain the common Python entry points for classical and deep-learning pipelines.

Related Resources

Course

Traditional Face Detection Using Python

In this course on face detection with Python, you'll learn about a historically important algorithm for object detection that can be successfully applied to finding the location of a human face within an image.

intermediate data-science machine-learning

For additional information on related topics, take a look at the following resources:

• Image Segmentation Using Color Spaces in OpenCV + Python (Tutorial)
• Image Processing With the Python Pillow Library (Tutorial)
• Traditional Face Detection With Python (Tutorial)
• Python AI: How to Build a Neural Network & Make Predictions (Tutorial)
• Building a Neural Network & Making Predictions With Python AI (Course)
• Process Images Using the Pillow Library and Python (Course)
• Traditional Face Detection With Python (Quiz)
• Python AI: How to Build a Neural Network & Make Predictions (Quiz)