YOLOv7 YOLOv8 YOLOv9 - Deep Learning Course

YOLO evolution, Train Custom Dataset, Object Detection, Pose Estimation, Instance Segmentation, Image Classification

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YOLOv7 YOLOv8 YOLOv9 - Deep Learning Course

What You Will Learn!

How to run, from scratch, a YOLOv7, YOLOv8, & YOLOv9 program to detect 80 object classes in < 10 minutes
How to install and train YOLOv7, YOLOv8, & YOLOv9 using your own 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
4 Real-World Projects: Masker Detection, Weather Image/Video Classification, Coffee Leaf Diseases Segmentation Squat Counter
YOLOv7 & YOLOv8 architecture and how it really works
How to find dataset
Data annotation/labeling using LabelImg
Automatic Dataset splitting
How to train YOLOv7, YOLOv8, and YOLOv9 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

Description

Welcome to the YOLOv7, YOLOv8, & YOLOv9 Deep Learning Course, a 3 COURSES IN 1. YOLOv7, YOLOv8, and YOLOv9 are the current three best object detection deep learning models. They are fast and very accurate. YOLOv9 is the latest official 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 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 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, and YOLOv9 installation

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

16. Visualize your training result using Tensorboard

17. Test the trained YOLOv7, YOLOv8, and YOLOv9 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

Who Should Attend!

Professionals who want to quickly grasp and apply YOLOv7, YOLOv8, and YOLOv9.
Undergraduate/Graduate students who are taking computer vision using deep learning as their final project
Any one who is interested in learning Deep Learning and How to Apply it in solving Computer Vision problem

TAKE THIS COURSE