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
- How to use YOLOv7 & YOLOv8 new features: Instance Segmentation, Pose Estimation, Image Classification, Object Tracking + Real-world Projects
- 7 Real Projects: Various Vehicle Counter Web App, Person Counter, Squat Counter, Masker Detection, Weather Classification, Coffee Leaf Diseases, Cattle Counter
- YOLOv7, YOLOv8, YOLOv9, YOLOv10 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
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