YOLOv6m: Object Detection
YOLOv6 is an advanced real-time object detection model based on the "You Only Look Once" framework. It achieves faster inference speeds while maintaining high accuracy, making it suitable for various edge devices and high-performance servers. YOLOv6 enhances its ability to detect small objects and improves the model's generalization performance by optimizing the network architecture and introducing new loss functions. Additionally, YOLOv6 supports multi-scale training, ensuring excellent performance across different resolutions. It is widely applied in areas such as video surveillance, autonomous driving, and intelligent security.
Source model
- Input shape: 1x3x640x640
- Number of parameters: 33.24M
- Model size: 133.20MB
- Output shape: 1x8400x85
The source model can be found here
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Inference & Model Conversion
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