Deep Learning Object Detection by Training & Deploying YOLOX

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Neuralearn Dot AI

6:43:21

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1 - Introduction

1 - Welcome.mp4

01:04

2 - General Introduction.mp4

06:47

3 - About this Course.mp4

02:57

4 - Link to code.html

2 - Theoritical background

5 - Haar Cascades and Histogram of gradients.mp4

36:53

6 - Convolutional Neural Networks.mp4

24:06

7 - RCNNFastRCNN FaterRCNN.mp4

07:06

3 - Single Stage Algorithms

8 - Understanding YOLO You Only look once.mp4

25:05

9 - Understanding YOLOX.mp4

14:06

4 - Dataset Preparation

1 - Creation of Custom dataset.html

10 - Pascal VOC dataset.mp4

15:43

11 - Preparing a custom dataset with Remo.mp4

20:12

12 - Assignment.html

5 - Finetuning and Testing

13 - Testing and FInetuning on Custom Dataset.mp4

01:00:56

14 - Wandb integration.mp4

17:05

15 - Running inference on Onnx model.mp4

08:16

16 - Assignment.html

6 - Deployment

17 - Understanding how APIs work.mp4

19:54

18 - Building an API with Fastapi.mp4

01:37:15

19 - Deploying on heroku.mp4

18:24

20 - Load testing with Locust.mp4

24:06

21 - Integration with C.mp4

03:26

22 - Assignment.html

Description

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++

Who is this for?

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

More details

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 Haarcascades
Deep Learning algorithms like Convolutional neural networks, YOLO and YOLOX
Object detection labeling formats like Pascal VOC.
Creation of a custom dataset with Remo
Conversion of our custom dataset to the Pascal VOCÂ format.
Finetuning and testing YOLOXÂ model with custom dataset
Conversion of finetuned model to Onnx format
Experiment tracking with Wandb
How APIs work and building your own API with Fastapi
Deploying an APIÂ to the Cloud
Load testing a deployed API with Locust
Running 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.

Enjoy!!!

Who this course is for:
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

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