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
YOLOv7 Overview
- Installing and setting up YOLOv7
- Architecture and core components of YOLOv7
- Benefits of YOLOv7 compared to other detection models
- Overview of YOLOv7 variants and their distinctions
YOLOv7 Training Workflow
- Preparing and annotating data
- Training models with major deep learning frameworks like TensorFlow and PyTorch
- Adapting pre-trained models for custom detection needs
- Assessing and tuning models for peak performance
Implementing YOLOv7
- Building YOLOv7 solutions in Python
- Integrating with OpenCV and other vision libraries
- Deploying YOLOv7 on edge devices and cloud environments
Advanced Concepts
- Tracking multiple objects with YOLOv7
- Applying YOLOv7 to 3D object detection
- Utilizing YOLOv7 for video-based object detection
- Optimizing YOLOv7 for real-time processing
Requirements
- Proficiency in Python programming.
- Familiarity with the fundamentals of deep learning.
- Basic knowledge of computer vision concepts.
Target Audience
- Computer vision engineers
- Machine learning researchers
- Data scientists
- Software developers
21 Hours
Testimonials (1)
Hands on and the practical
