English | Size: 6.1 GB
Genre: eLearning
Train Custom Dataset, Object Detection, Pose Estimation, Instance Segmentation, Image Classification, Cool Web Dashboard
What you’ll learn
How to run, from scratch, a YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 program to detect 80 object classes in < 10 minutes
How to install and train YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLO11 using Custom Dataset & perform Object Detection for image, video & Real-Time using Webcam
Object Detection, Instance Segmentation, Pose Estimation, Image Classification, Object Tracking + Real-World Projects
8 Real Projects: Various Vehicle Counter Web App, Person Counter, Squat Counter, Weather Classification, Leaf Diseases, Cattle Counter, X-Ray Classification
YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLO11 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, YOLO v10, YOLO11 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
Real World Project #7: Person Counter using YOLO11 + Bytetrack
Real World Project #8: X-Ray Image Classification using YOLO11
Welcome to the YOLOv7, YOLOv8, YOLOv9, YOLOv10, & YOLOv11 Deep Learning Course, a 5 COURSES IN 1. YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are the current five best object detection deep learning models. They are fast and very accurate. YOLOv11 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 & YOLO11 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, YOLOv10, and YOLO11 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, YOLOv10, and YOLOv11 installation
15. Train YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLO 11 on your own custom dataset
16. Visualize your training result using Tensorboard
17. Test the trained YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLO11 models on image, video, and real-time using webcam.
18. YOLOv7 New Features: Pose Estimation
19. YOLOv7 New Features: Instance Segmentation
20. YOLOv8 New Features: Instance Segmentation & Object Tracking
21. YOLO11 : Object Detection, Object Tracking, Instance Segmentation, & Image Classification
22. Real World Project #1: Robust mask detector using YOLOv7 and YOLOv8
23. Real World Project #2: Weather YOLOv8 classification application
24. Real World Project #3: Coffee Leaf Diseases Segmentation application
25. Real World Project #4: YOLOv7 Squat Counter application
26. Real World Project #5: Various Vehicle Counter and Speed Estimation Web App with Cool Dashboard using YOLOv9 + Streamlit
27. Real World Project #6: Cattle Counter using YOLOv10 + Bytetrack
28. Real World Project #7: Person Counter using YOLOv11 + Bytetrack
29. Real World Project #8: X-Ray Image Classification using YOLO11
[b]Who this course is for:[/b]
Professionals who want to quickly grasp and apply YOLOv7, YOLOv8, YOLOv9, YOLOv10, and YOLO11 on real projects
Undergraduate/Graduate students who are taking computer vision using deep learning as their final project
Anyone who is interested in learning Deep Learning and How to Apply it in solving Computer Vision problem
[center][img]https://i.imgur.com/yMNlxlr.png[/img][/center]
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