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CV Onboarding

Onboarding resources for University of Michigan Autonomous Robotic Vehicle Team (2025-26) Computer Vision Subteam.

How This Repository is Organized

The onboarding is divided into 6 sections:

  1. Introduction: Introduces what the CV Subteam does, and how to get started.
  2. Setup: Guides you through setting up your development environment.
  3. Programming: Focuses on Python, followed by an intro to OpenCV and PyTorch.
  4. Classical Computer Vision: Covers classical computer vision techniques using OpenCV.
  5. Machine Learning: Focuses on PyTorch usage in our projects and important architectures.
  6. Integration: Discusses how to integrate your work with other subteams and the overall project.

How to Use This Repository

Completing each section is a three-step process:

  1. Read: You will be assigned a section to read through. Complete the reading and take notes if required. Some sections may have videos to make it easier to follow along.
  • Note that most sections have code snippets. You do not need to understand it all, but try to correlate it with the reading. The code is mainly for reference later on during projects.
  1. Complete Checkpoint: After reading, make sure to complete the checkpoint for that section. This is usually a short task covering the main points of the section.
  2. Fill out the Form: In the last 10 minutes of each meeting (general and subteam), help us keep track by filling out this form: onboarding form.

General Flow of Onboarding Sessions + Schedule

  • Pranav presents an overview of the current week’s section (15-20 mins)
  • 1 hour - 1.5 hours on reading
  • 1 - 1.5 hours on checkpoint
  • Max Total Time = 3 hours 20 mins
  • Total meeting time = 1.5 hours (STM) + 2 hours (GM) = 3.5 hours

The onboarding is designed to be completed over the course of 6 weeks, with one section per week. However, this can be adjusted based on your availability and pace. The goal is to ensure you have a solid understanding of the material before moving on to the next section.

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