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
- Foundations of object detection
- Practical applications of object detection
- Key performance metrics for detection models
Understanding YOLOv7
- Installation and initial setup of YOLOv7
- Analysis of YOLOv7 architecture and core components
- Benefits of YOLOv7 compared to other detection models
- Overview of YOLOv7 variants and their distinctions
The YOLOv7 Training Workflow
- Data preparation and annotation techniques
- Training models using frameworks such as TensorFlow and PyTorch
- Adapting pre-trained models for custom detection tasks
- Evaluation and optimisation for peak performance
Putting YOLOv7 into Practice
- Writing YOLOv7 code in Python
- Integrating with OpenCV and other computer vision libraries
- Deploying YOLOv7 on edge devices and cloud infrastructure
Advanced Applications
- Implementing multi-object tracking with YOLOv7
- Applying YOLOv7 to 3D object detection
- Using YOLOv7 for video-based object detection
- Optimising YOLOv7 for real-time efficiency
Requirements
- Familiarity with Python programming
- Foundational understanding of deep learning
- Basic knowledge of computer vision
Target Audience
- Computer vision engineers
- Machine learning researchers
- Data scientists
- Software developers
21 Hours
Testimonials (1)
Hands on and the practical
