YOLOv7 YOLOv8 YOLOv9 YOLOv10 - Deep Learning Course

About Course

Welcome to the YOLOv7, YOLOv8, YOLOv9, & YOLOv10 Deep Learning Course, a 4 COURSES IN 1. YOLOv7, YOLOv8, YOLOv9, and YOLOv10 are the current four best object detection deep learning models. They are fast and very accurate. YOLOv10 is the latest version of YOLO whereas YOLOv8 is the most popular YOLO version of all.

What will you learn:

1. How to run, from scratch, a YOLOv7, YOLOv8, YOLOv9, & YOLOv10 program to detect 80 types of objects in < 10 minutes.

2. YOLO evolution from YOLO v1 to YOLO v8

3. What is the real performance comparison, based on our experiment

4. What are the advantages of YOLO compares to other deep learning models

5. What’s new in YOLOv7 and YOLOv8

6. How artificial neural networks work (neuron, perceptron, feed-forward network, hidden layers, fully connected layers, etc)

7. Different Activation functions and how they work (Sigmoid, tanh, ReLu, Leaky ReLu, Mish, and SiLU)

8. How convolutional neural networks work (convolution process, pooling layer, flattening, etc)

9. Different computer vision problems (image classification, object localization, object detection, instance segmentation, semantic segmentation)

10. YOLOv7, YOLOv8, YOLOv9, and YOLOv10 architecture in detail

11. How to find the dataset

12. How to perform data annotation using LabelImg

13. How to automatically split a dataset

14. A detailed step-by-step YOLOv7, YOLOv8, YOLOv9, and YOLOv10 installation

15. Train YOLOv7, YOLOv8, YOLOv9, and YOLOv10 on your own custom dataset

16. Visualize your training result using Tensorboard

17. Test the trained YOLOv7, YOLOv8, YOLOv9, and YOLOv10 models on image, video, and webcam.

18. YOLOv7 New Features: Pose Estimation

19. YOLOv7 New Features: Instance Segmentation

20. YOLOv8 New Features: Instance Segmentation & Object Tracking

20. Real World Project #1: Robust mask detector using YOLOv7 and YOLOv8

21. Real World Project #2: Weather YOLOv8 classification application

22. Real World Project #3: Coffee Leaf Diseases Segmentation application

23. Real World Project #4: YOLOv7 Squat Counter application

24. Real World Project #5: Various Vehicle Counter and Speed Estimation Web App with Cool Dashboard using YOLOv9 + Streamlit
25. Real World Project #6: Cattle Counter using YOLOv10 + Bytetrack

How to run, from scratch, a YOLOv7, YOLOv8, YOLOv9, & YOLOv10 program to detect 80 object classes in < 10 minutes
How to install and train YOLOv7, YOLOv8, YOLOv9, & YOLOv10 using Custom Dataset and perform Object Detection for image, video and Real-Time using Webcam/Camera
How to use YOLOv7 & YOLOv8 new features: Instance Segmentation, Pose Estimation, Image Classification, Object Tracking + Real-world Projects
6 Real Projects: Masker Detection, Weather Classification, Coffee Leaf Diseases Segmentation, Squat Counter, Various Vehicle Counter Web App, Cattle Counter
YOLOv7, YOLOv8 & YOLOv9 architecture and how it really works
How to find dataset
Data annotation/labeling using LabelImg
Automatic Dataset splitting
How to train YOLO v7, YOLO v8, YOLO v9, and YOLO v10 using custom dataset, transfer learning and resume training.
How to visualize training performance using TensorBoard
Easily understand The Fundametal Theory of Deep Learning and How exactly Convolutional Neural Networks Work
Real-World Project #1: Masker detection using YOLOv7 & YOLOv8
Real-World Project #2: Weather Image/Video Classification using YOLOv8
Real-World Project #3: Coffee Leaf Diseases Segmentation using YOLOv8
Real-World Project #4: Squat Counter based on YOLOv7 Pose Estimation
Real World Project #5: Various Vehicle Counter and Speed Estimation Web App with Cool Dashboard using YOLOv9 + Streamlit
Real World Project #6: Cattle Counter using YOLOv10 + Bytetrack

Course Content

Subtitle Guide – Hướng dẫn thêm phụ đề

Set up subtitle for video – Hướng dẫn thêm phụ đề

About Course

What Will You Learn?

Course Content

Subtitle Guide – Hướng dẫn thêm phụ đề

01 – Introduction

02 – How to run your first YOLOv7YOLOv8 Deep Learning program in 10 minutes

03 – A comprehensive overview of YOLO

04 – Understanding Deep Learning

05 – Understanding YOLOv7 & YOLOv8

06 – Tools Installation (Windows)

07 – Dataset Preparation

08 – YOLOv7, YOLOv8, and YOLOv9 prerequisites Installation (Windows)

09 – YOLOv7 Installation (Windows, Google Colab)

10 – YOLOv8 Installation (Windows, Google Colab)

11 – Perform Object Detection using YOLOv7 pretrained model on image, video, webcam

12 – Perform Object Detection using YOLOv8 pretrained model on image, video, webcam

13 – Training YOLOv7 detection model on custom dataset

14 – Training YOLOv8 detection model on custom dataset

15 – YOLOv7 & YOLOv8 Performance Measurement

16 – YOLOv7 New Features

17 – YOLOv8 New Features

18 – Training YOLOv8 Classification model on custom dataset (Real-World Project #2)

19 – Training YOLOv8 Segmentation model on custom dataset (Real-World Project #3)

20 – Real-World Project 4 Squat Counter

21 – YOLOv9 Object Detection