課程大綱： Real-Time Object Detection with YOLO培訓(xùn)
Introduction
Overview of YOLO Pre-trained Models Features and Architecture
The YOLO Algorithm
Regression-based Algorithms for Object Detection
How is YOLO Different from RCNN?
Utilizing the Appropriate YOLO Variant
Features and Architecture of YOLOv1-v2
Features and Architecture of YOLOv3-v4
Installing and Configuring the IDE for YOLO Implementations
The Darknet Implementation
The PyTorch and Keras Implementations
Executing the OpenCV and NumPy
Overview of Object Detection Using YOLO Pre-trained Models
Building and Customizing Python Command-Line Applications
Labeling Images Using the YOLO Framework
Image Classification Based on a Dataset
Detecting Objects in Images with YOLO Implementations
How do Bounding Boxes Work?
How Accurate is YOLO for Instance Segmentation?
Parsing the Command-line Arguments
Extracting the YOLO Class Labels, Coordinates, and Dimensions
Displaying the Resulting Images
Detecting Objects in Video Streams with YOLO Implementations
How is it Different from Basic Image Processing?
Training and Testing the YOLO Implementations on a Framework
Troubleshooting and Debugging
Summary and Conclusion
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