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Duration 21 hours
Course Outline
Introduction to Object Detection
- Core concepts in object detection
- Real-world applications of object detection
- Key performance metrics for evaluating detection models
YOLOv7 Overview
- Installation and initial setup of YOLOv7
- Architectural details and components of YOLOv7
- Benefits of YOLOv7 compared to other detection models
- Differences between various YOLOv7 variants
YOLOv7 Training Workflow
- Data preparation and annotation strategies
- Training models using leading deep learning frameworks (e.g., TensorFlow, PyTorch)
- Fine-tuning pre-trained models for custom detection needs
- Evaluation and tuning to achieve optimal performance
Implementing YOLOv7
- Building YOLOv7 applications in Python
- Integration with OpenCV and other vision libraries
- Deployment on edge devices and cloud platforms
Advanced Concepts
- Implementing multi-object tracking with YOLOv7
- Applications of YOLOv7 in 3D object detection
- Using YOLOv7 for video object detection
- Optimization techniques for real-time performance
Requirements
- Proficiency in Python programming
- A solid grasp of deep learning fundamentals
- Familiarity with basic computer vision concepts
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 3900 € + VAT*
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