YOLO11s-seg
YOLO系列网络模型是最为经典的one-stage算法,也是目前工业领域使用最多的目标检测网络,YOLO11网络模型是YOLO系列的最新版本,在继承了原有YOLO网络模型优点的基础上,在架构和训练方法上进行了重大改进,具有更高的检测精度、速度和效率。YOLO11s-seg作为实例分割的模型,比检测模型更进一步,包括识别图像中的各个对象并将它们与图像的其余部分分割开来。
Mirror Metadata
- Hugging Face repo: shadow-cann/hispark-modelzoo-yolo11s-seg
- Portal model id: i9j5c2fl6k00
- Created at: 2025-12-25 17:25:35
- Updated at: 2025-12-30 20:02:18
- Category: 计算机视觉
Framework
- PyTorch
Supported OS
- OpenHarmony
- Linux
Computing Power
- Hi3403V100 SVP_NNN
- Hi3403V100 NNN
Tags
- 目标检测
Detail Parameters
- 输入: 640x640
- 参数量: 10.123M
- 计算量: 38.183GFLOPs
Files In This Repo
- yolo11s-seg.pt (源模型 / 源模型下载; 源模型 / 源模型元数据)
- yolo11s-seg.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据)
- SVP_NNN_PC_V1.0.6.0.tgz (附加资源 / 附加资源)
Upstream Links
- Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=i9j5c2fl6k00
- Upstream repository: https://gitee.com/Hispark/modelzoo/tree/master/samples/samples_GPL/built-in/yolo11s-seg
- License reference: https://github.com/ultralytics/ultralytics/blob/master/LICENSE
Notes
- This repository was mirrored from the HiSilicon Developer Portal model card and local downloads captured on 2026-03-27.
- File ownership follows the portal card mapping, not just filename similarity.
- Cover image: 1701430507536385_yolo11s-seg.jpg
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