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Duration 21 hours
Course Outline
Introduction to Object Detection
- Fundamentals of object detection
- Practical applications of object detection
- Key performance metrics for evaluating detection models
YOLOv7 Overview
- Installation and initial setup of YOLOv7
- Understanding the YOLOv7 architecture and its components
- Key advantages of YOLOv7 compared to other detection models
- Differences between YOLOv7 variants
The YOLOv7 Training Process
- Preparing and annotating data
- Training models using major deep learning frameworks like TensorFlow and PyTorch
- Adapting pre-trained models for specific detection needs
- Evaluating and tuning for peak performance
Implementing YOLOv7
- Building YOLOv7 implementations in Python
- Working with OpenCV and other vision libraries
- Deployment strategies for edge devices and cloud environments
Advanced Concepts
- Tracking multiple objects with YOLOv7
- Applying YOLOv7 to 3D object detection
- Detecting objects in video streams
- Optimizing YOLOv7 for real-time efficiency
Requirements
- Proficiency in Python programming
- Foundational knowledge of deep learning
- Basics of computer vision
Target Audience
- Computer vision engineers
- Machine learning researchers
- Data scientists
- Software developers
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 4800 € + VAT*
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