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.
Duration 21 hours
Course Outline
Foundations of Object Detection
- Core concepts of object detection
- Real-world applications of detection
- Key performance metrics for detection models
Introduction to YOLOv7
- Installation and initial configuration
- Understanding YOLOv7 architecture and components
- Benefits of YOLOv7 compared to alternative models
- Differences among various YOLOv7 variants
Training Workflow with YOLOv7
- Preparing and annotating datasets
- Training models using major deep learning frameworks (TensorFlow, PyTorch, etc.)
- Adapting pre-trained models for specific detection needs
- Optimizing for peak performance through evaluation and tuning
Practical Implementation
- Coding YOLOv7 applications in Python
- Collaborating with OpenCV and other vision libraries
- Deploying solutions on edge devices and cloud infrastructure
Advanced Concepts
- Tracking multiple objects using YOLOv7
- Applying YOLOv7 to 3D detection tasks
- Detecting objects within video streams
- Enhancing YOLOv7 for optimal real-time speed
Requirements
- Proficiency in Python programming
- Foundational understanding of deep learning
- Basical knowledge of computer vision
Target Audience
- Computer vision engineers
- Machine learning researchers
- Data scientists
- Software developers
Testimonials (1)
Hands on and the practical
