Jetson Nano Computer Vision
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Module 1: Introduction to Jetson

Lecture 1.1: Jetson Introduction
Lecture 1.2: Explanation On How To Use It
Lecture 1.3: Course Overview
Jetson Introduction PDF
Jetson Course Complete Material.zip
Module 2 - Comparison of Jetson and Its Variants Along with RPi+SD Card Flashing

Lecture 2.1: How Jetson Is Better Than Raspberry Pi
Lecture 2.2: Comparison Among Different Variants
Lecture 2.3: SD Card Flashing
Lecture 2.4: Which Card To Buy
Lecture 2.5: Running Jetson For The First Time
Module 2 Slides
Module 3 - Installing Libraries and Setting Up AI Computer - Explain Dependencies and Their Use

Lecture 3.1: Various Libraries and Their Usage e.g. OpenCV PyTorch Etc.
Lecture 3.2: Installing Supportive Libraries
Lecture 3.3: Installing OpenCV From Scratch With CUDA Support
Lecture 3.4: Installing Other Supportive Libraries
Lecture 3.5: Installing PyTorch and TorchVision
Lecture_3.pdf
Module 3:Installing Libraries and Setting Up AI Computer Explain Dependencies and Their Use.zip
Installation-updated-latest.odt
Installation.odt
Module 4 - Computer Vision OpenCV Basics on Jetson + Pytorch

Lecture 4.1: Perform Some Basic Image Operations Using OpenCV
Lecture 4.2: Import Libraries, Image Read and Display
Lecture 4.3: Color Conversion
Lecture 4.4: Basic Filtration
Lecture 4.5: Transformation
Lecture 4.6: Edge Detection
Lecture 4.7 Morphological Operations
Lecture 4.8: Corner Detection
Lecture 4.9: Basics About PyTorch
Lecture 4.10: Basics About TorchVision
Lecture 4.11: Combining OpenCV and Torch To Perform Basic Image Operations
Module 5 - What is Object Detection + Yolo Object Detection

Lecture 5.1: Introduction to Object Detection and How It Is Performed
Lecture 5.2: YOLO Variants
Lecture 5 Slides
Module 6 - YOLO Object Detection on Custom Dataset (Number Plate Dataset)

Lecture 6.1: About The Dataset and Its Annotation for Object Detection
Lecture 6.2: Train The Model On Some Existing Dataset
Lecture 6.3: Perform Object Detection Using Pre-trained Model
Lecture 6 Slides
Module 7: Where to from here?

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Lecture 4.9: Basics About PyTorch

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