Computer Vision Course
Build Real-World Edge AI Apps with Jetson Nano in 2 Weeks!ENROLL
Jetson is Great for Computer Vision.
For On-Edge Computer Vision Projects, the Jetson Nano provides the following benefits:
Compatibly with TensorFlow, PyTorch etc.
But How Do I Get Started with Jetson for AI-CV Applications?
Jetson Computer Vision Course
Be at the Cutting-Edge of Computer Vision.
- Setting up any Jetson for AI.
- DeepStream SDK
- 6 x Real-World Edge-CV Jetson Applications.
OS Image + Code
8 Hours+ Content
"If you want to develop your own State-of-the-art, Low-Powered & Portable Machine Vision models On-Edge,
then this course is for you!"
Introduction to Jetson.
- Overview of Course
- Jetson Nano Features
- Applications of Jetson
- Jetson Variants Comparison
Getting Started with Jetson.
- How Jetson is better than RPi.
- Which SD-Card to buy.
- How to download image & flash SD-Card
- Running Image on Jetson for the first time.
Installing Libraries & Setting up AI Computer
- Installing python and other supportive libraries.
- Explanation on various libraries and their usage e.g opencv, pytorch etc.
- Installing OpenCV from scratch with CUDA support.
- Installing other supportive libraries.
- Installing Pytorch and torchvision.
Computer Vision Basics on Jetson + PyTorch
- How to perform some basic image operations using OpenCV
- PyTorch and torchvision Basics & How to use it.
- Combining OpenCV & Torch to perform basic image operations.
- Object detection introduction and how it is performed.
- Brief about different YOLO versions.
- Demo of object detection using YOLOX
YOLOX object detection on Custom Dataset
- Number Plate Dataset & annotation for object detection.
- Train the model on some existing dataset.
- Perform object detection using pre-trained model for ANPR.
TensorRT Intro & Setup
- What is TensorRT (TRT)?
- TensorRT benefits.
- Installing dependencies for TRT.
- Setting up the environment for TRT.
Optimising YOLOX Model using TensorRT.
- Converting the YOLOX model to TensorRT
- Testing TensorRT model
- Comparing Results
What is DeepStream?
- Introduction to DeepStream.
- How it works?
- DeepStream Demo
- DeepStream Applications
- Setting up an environment for DeepStream SDK
- Testing the DeepStream SDK on Jetson.
Running DeepStream SDK with Multiple IP cameras
- Setting IP cameras with DeepStream.
- Performing multiple camera synchronisation using DeepStream SDK.
- Perform object detection on multiple cameras simultaneously.
App 1 - Vehicle Counting + Tracking
- Vehicle Detection
- Object Tracking for Vehicles
- Counting Vehicles
App 2 - YOLOv7 Automatic Number Plate Recognition [ANPR]
- Introduction to Training with the Jetson.
- How to annotate data in YOLOv7 format?
- Brief about Google colab and setting environment for training data.
- Training the model on custom dataset of number plates
- Extract number plate using YOLO model
- Apply Paddle-OCR to extract alphabets & digits on license plates.
App 3 - Pose Estimation on Jetson
- How pose estimation is performed?
- Installing PoseNet library.
- Implementing PoseNet estimation on Jetson.
App 4 - Fake Face Classification
- What is DeepFake?
- Perform training on videos of DeepFake.
- Fake/real video classification on pre-trained model.
App 5 - Face Recognition and Attendance - Clock in, clock out.
- Introduction to Face Recognition.
- Implementing face recognition.
- Face recognition for Attendance System.
Once you complete the course, you will graduate with an Official Certificate embedded with a unique ID that you can share on LinkedIn.
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