Huggingface Computer Vision Course Github

Leo Migdal

-Nov 18, 2025, 10:28 PM

huggingface computer vision course github

This is the repository for a community-led course on Computer Vision. Over 60 contributors from the Hugging Face Computer Vision community have worked together on the content for this course. The result you have in front of you is as diverse as the community. A typical educational course is created by a small group of people, who try to match the tone of each other closely. We took a different road. While following a plan on which content we wanted to include, all authors had freedom in the choice of their style.

Other members of the community reviewed the content and approved or made change suggestions. The outcome is a truly unique course and proof of what a strong open-source community can achieve. If you want to contribute content or suggest some typo/bug fixes, head over to the Contribution Guidelines. If you are curious about the Hugging Face Computer Vision Community, read on 🔽 There was an error while loading. Please reload this page.

Community Computer Vision Course documentation Welcome to the Community Computer Vision Course and get access to the augmented documentation experience Welcome to the community-driven course on computer vision. Computer vision is revolutionizing our world in many ways, from unlocking phones with facial recognition to analyzing medical images for disease detection, monitoring wildlife, and creating new images. Together, we’ll dive into the fascinating world of computer vision!

Throughout this course, we’ll cover everything from the basics to the latest advancements in computer vision. It’s structured to include various foundational topics, making it friendly and accessible for everyone. We’re delighted to have you join us for this exciting journey! There was an error while loading. Please reload this page. You can create a release to package software, along with release notes and links to binary files, for other people to use.

Learn more about releases in our docs. This is the repository for a community-led course on Computer Vision. Over 60 contributors from the Hugging Face Computer Vision community have worked together on the content for this course. The result you have in front of you is as diverse as the community. A typical educational course is created by a small group of people, who try to match the tone of each other closely. We took a different road.

While following a plan on which content we wanted to include, all authors had freedom in the choice of their style. Other members of the community reviewed the content and approved or made change suggestions. The outcome is a truly unique course and proof of what a strong open-source community can achieve. If you want to contribute content or suggest some typo/bug fixes, head over to the Contribution Guidelines. If you are curious about the Hugging Face Computer Vision Community, read on 🔽 There was an error while loading.

Please reload this page. There was an error while loading. Please reload this page. Use alt + click/return to exclude labels. There was an error while loading. Please reload this page.

This document provides a comprehensive overview of the Computer Vision Course repository hosted at https://github.com/huggingface/computer-vision-course. This community-driven educational resource covers a wide range of computer vision topics from fundamentals to advanced techniques. The purpose of this overview is to explain the repository's structure, learning objectives, and how content is organized. For information about certification and learning paths, see Certification and Learning Path. The Computer Vision Course is a comprehensive educational resource developed collaboratively by over 60 contributors from the Hugging Face Computer Vision community. The course is designed to provide both theoretical knowledge and practical implementations, making complex computer vision concepts accessible to learners of various skill levels.

The course content is organized into 13 distinct units, each focusing on specific aspects of computer vision. The repository follows a logical file structure that maps to these units. The following table provides a comprehensive overview of all course units and their primary content focus: Community Computer Vision Course documentation and get access to the augmented documentation experience Apart from videos, about which we talked in the last chapter, another common form of visual data comes in the 3-dimensional form.

While for 2D images we usually have the two dimensions, commonly labelled as x and y, for 3D images we have three dimensions, referred to as x, y and z. “But wait,” I hear you say, “videos also have three dimensions!” That is completely correct - videos have the two spatial dimensions, x and y, and the temporal dimension, t. The difference with 3D data is that here all three dimensions are of a spatial nature. This helps us to create a better model of our world and our perceptive capabilities. That is why one very common field for 3D applications nowadays is Mixed Reality applications, in which we try to merge the digital and analog worlds. You will learn more about applications of 3D Computer Vision in the first chapter after this introduction.

Right after that, we will take a look at the historical developments of 3D applications - all the way from the 19th century to today. There was an error while loading. Please reload this page. There was an error while loading. Please reload this page.

Huggingface Computer Vision Course Github

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