Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Object Detection
- Fundamentals of object detection
- Practical applications of object detection
- Key performance metrics for detection models
Overview of YOLOv7
- Installing and setting up YOLOv7
- Understanding the YOLOv7 architecture and components
- Benefits of YOLOv7 compared to other detection models
- Differences between various YOLOv7 variants
YOLOv7 Training Process
- Preparing and annotating data
- Training models using leading deep learning frameworks (such as TensorFlow and PyTorch)
- Fine-tuning pre-trained models for custom detection needs
- Evaluating and tuning models for optimal results
Implementing YOLOv7
- Writing YOLOv7 implementations in Python
- Integrating with OpenCV and other vision libraries
- Deploying YOLOv7 on edge devices and cloud infrastructure
Advanced Topics
- Tracking multiple objects with YOLOv7
- Applying YOLOv7 to 3D object detection
- Detecting objects in video streams using YOLOv7
- Optimizing YOLOv7 for high-performance real-time inference
Requirements
- Proficiency in Python programming
- A solid grasp of deep learning fundamentals
- Basic knowledge of computer vision principles
Target Audience
- Computer vision engineers
- Machine learning researchers
- Data scientists
- Software developers
21 Hours
Testimonials (1)
Hands on and the practical
