YOLOv7 architecture, Data Annotation, Training on Custom Dataset, Object Detection, Study Case (Project)
What you will learn
How to run, from scratch, a YOLOv7 program to detect 80 object classes in < 10 minutes
How to install and train YOLOv7 using your own Custom Dataset and perform Object Detection for image, video and Real-Time using Webcam/Camera
YOLOv7 architecture and how it really works
How to find dataset
Data annotation/labeling using LabelImg
Automatic Dataset splitting
How to visualize training performance using TensorBoard
Real-World Project: Masker detection using YOLOv7
Why take this course?
π [YOLOv7 Custom Object Detection Course] π
Course Headline:
“Unlock the Power of AI with YOLOv7 for Custom Object Detection!”
Course Description:
Welcome to the YOLOv7 Custom Object Detection Course (FREE), where you will dive into the world of Advanced Artificial Intelligence! This course is meticulously designed to provide you with a comprehensive understanding of YOLOv7 architecture, data annotation, and custom object detection. π
What You’ll Learn:
- Quickstart with YOLOv7: π
- Run a YOLOv7 program to detect 80 types of objects in under 10 minutes. This hands-on introduction sets the pace for an engaging learning experience.
- Understanding Convolutional Neural Networks (CNNs): π§
- Gain insights into the convolution process, pooling layer, flattening, and more, which are fundamental building blocks of any CNN model.
- YOLOv7 Architecture: ποΈ
- Dive deep into the architecture of YOLOv7, understanding its components and how it differs from previous versions.
- Dataset Acquisition: π
- Learn how to source or compile your dataset for training an object detection model.
- Data Annotation with LabelImg: π₯οΈ
- Follow a step-by-step guide to accurately label your data, which is a pivotal step in the training process and will significantly impact your model’s performance.
- Automatic Dataset Splitting: π
- Master the art of splitting your dataset efficiently into training, validation, and test sets with minimal manual intervention.
- YOLOv7 Installation: π οΈ
- Get a detailed step-by-step guide on setting up YOLOv7 from scratch, ensuring you have all the necessary tools and libraries ready for your project.
- Training YOLOv7: π€
- Configure and train YOLOv7 using your custom dataset while monitoring the progress and optimizing performance parameters.
- Tensorboard Visualization: π
- Utilize Tensorboard to visualize your training results, providing valuable insights into how your model is learning over time.
- Testing with Real-World Applications: π
- Test the trained YOLOv7 model on images, videos, and live webcam feeds, putting your new skills to practical use.
- Real World Project: Robust Mask Detector: π
- Apply what you’ve learned by creating a robust mask detector as part of a real-world project, demonstrating the versatility and effectiveness of YOLOv7 in diverse scenarios.
What Next? π
After mastering the basics of YOLOv7, expand your expertise with our advanced courses: “YOLOv7-YOLOv8-YOLOv9: 3 in 1 course”. This will cover powerful features and additional capabilities of these versions, pushing the boundaries of what’s possible with object detection.
π Important Note:
Udemy’s Free Course option allows for up to 2 HOURS of lectures, which means this course is an introduction to YOLOv7 object detection. To fully explore Pose Estimation and Image Segmentation, as well as delve deeper into the capabilities of YOLOv7 and other versions, we encourage you to continue your learning journey with our comprehensive courses on offer. π
Join us on this exciting AI adventure and transform your data into intelligent insights with YOLOv7! π