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Deep Dive into Object Detection with YOLO

Understanding the YOLOv7 Model Structure

Understand the YOLOv7 model structure by exploring its backbone, neck, auxiliary and lead heads. Learn how architecture and training optimizations improve detection accuracy while maintaining speed.

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YOLOv7 architecture is based on previous YOLO architectures of YOLOv4, YOLO-R, and scaled YOLOv4. YOLOv7 outperforms both convolution-based and transformer-based OD models.

What makes YOLOv7 more efficient?

The new model architecture focuses on two important aspects of a model:

  • Architecture optimization

  • Training process optimization (to improve the accuracy of detections without increasing the inference cost)

Architecture summary

YOLOv7 is designed to predict bounding boxes more accurately than the previous versions while maintaining the inference ...