The End-to-End Computer Vision Bootcamp is designed from a real-world perspective and follows the data processing, development, and deployment pipeline paradigm using a variety of tools. Through hands-on exercises, attendees will learn the fundamentals of preprocessing custom images, speeding the development process using transfer learning for model training, and deployment of trained models for fast and scalable AI in production.
The content is structured in five modules with an additional introductory notebook and two challenge notebooks:
- Welcome to end-to-end computer vision bootcamp
- Lab 1: Data labeling and preprocessing
- Lab 2: Object detection using TAO YOLOv4
- Lab 3: Model deployment with Triton Inference Server
- Lab 4: Model deployment with DeepStream
- Lab 5: Measure object size using OpenCV
- Challenge 1: DeepStream SDK
- Challenge 2: Triton Inference Server
The tools and frameworks used in the bootcamp are as follows:
- NVIDIA® TAO Toolkit
- NVIDIA DeepStream SDK
- NVIDIA Triton™ Inference Server
- NVIDIA TensorRT™
- OpenCV
- Label Studio
The total bootcamp material would take approximately 8.5 hours. It is recommended to divide the teaching of the material into two days, covering the first two notebooks (Lab 1 and Lab 2) in one session and the rest in the next session.
A basic understanding of Deep Learning, Python programming, and familiarity with NVIDIA® NGC™ is required.
To deploy the Labs, please refer to the Deployment guide presented here
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