Train And Deploy Yolox Object Detection Models To The Cloud

Finetuning and testing a YOLOX model on custom built dataset. Creating and deploying object detection API to cloud

What you'll learn

Master the basics of Object detection

Understanding pre-deep learning algorithms like haarcascades

Understanding deep learning algorithms like YOLO and YOLOX

Create your own dataset with Remo

Understanding the Pascal VOC dataset

Convert your custom dataset to Pascal VOC Format

Testing and training YOLOX model on custom dataset

Integrating Wandb for experiment tracking

Converting trained model to Onnx format

Understanding how APIs work

Building Object detection API with Fastapi

Deploying API to the Cloud

Load testing the API with Locust

Running the object detection model in c++

Requirements

Basic Knowledge of Python

Access to an internet connection, as we shall be using Google Colab (free version)

Description

Object detection algorithms are everywhere. With creation of much more efficient models from the early 2010s, these algorithms which now are built using deep learning models are achieving unprecedented performances.In this course, we shall take you through an amazing journey in which you'll master different concepts with a step by step approach. We shall start from understanding how object detection algorithms work, to deploying them to the cloud, while observing best practices.You will learn:Pre-deep learning object detection algorithms like HaarcascadesDeep Learning algorithms like Convolutional neural networks, YOLO and YOLOXObject detection labeling formats like Pascal VOC.Creation of a custom dataset with RemoConversion of our custom dataset to the Pascal VOC format.Finetuning and testing YOLOX model with custom datasetConversion of finetuned model to Onnx formatExperiment tracking with WandbHow APIs work and building your own API with FastapiDeploying an API to the CloudLoad testing a deployed API with LocustRunning object detection model in c++If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.YOU'LL ALSO GET:Lifetime access to This CourseFriendly and Prompt support in the Q&A sectionUdemy Certificate of Completion available for download30-day money back guaranteeEnjoy!!!

Overview

Section 1: Introduction

Lecture 1 Welcome

Lecture 2 General Introduction

Lecture 3 About this Course

Lecture 4 Link to code

Section 2: Theoritical background

Lecture 5 Haar Cascades and Histogram of gradients

Lecture 6 Convolutional Neural Networks

Lecture 7 RCNN,FastRCNN, FaterRCNN

Section 3: Single Stage Algorithms

Lecture 8 Understanding YOLO (You Only look once)

Lecture 9 Understanding YOLOX

Section 4: Dataset Preparation

Lecture 10 Pascal VOC dataset

Lecture 11 Preparing a custom dataset with Remo

Lecture 12 Assignment

Section 5: Finetuning and Testing

Lecture 13 Testing and FInetuning on Custom Dataset

Lecture 14 Wandb integration

Lecture 15 Running inference on Onnx model

Lecture 16 Assignment

Section 6: Deployment

Lecture 17 Understanding how APIs work

Lecture 18 Building an API with Fastapi

Lecture 19 Deploying on heroku

Lecture 20 Load testing with Locust

Lecture 21 Integration with C++

Lecture 22 Assignment

Beginner Python Developers curious about applying deep learning techniques like YOLO,Software developers interested in using A.I and deep learning for object detection,Students interested in learning about object detection and how it can be applied practically,AI Practitioners wanting to master how to deploy AI Models to the cloud very easily,Software developers who want to learn how state of art object detection models are built and trained using deep learning.,Students who study different Object Detection Algorithms and want to Train YOLO with Custom Data.,Students who study Computer Vision and want to know how to use YOLO and its variants like YOLOX for Object Detection