shadow-cann/hispark-modelzoo-yolov9s

YOLOv9s

YOLOv9s 是 Ultralytics 推出的目标检测模型，采用了 GELAN 架构和 PGI 训练策略。相比于之前的版本，YOLOv9 在保持高效推理的同时，通过可编程梯度信息（PGI）进一步提升了检测精度。该模型在 COCO 数据集上进行了训练和验证。

Mirror Metadata

• Hugging Face repo: shadow-cann/hispark-modelzoo-yolov9s
• Portal model id: j9brj6ooi000
• Created at: 2026-04-03 10:29:46
• Updated at: 2026-04-08 16:07:07
• 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

• 计算量: 29.526 GFLOPs
• 输入: 640x640
• 参数量: 7.240 M

Files In This Repo

• yolov9s.om (编译模型 / A16W8; 编译模型 / OM 元数据 / A16W8)
• yolov9s_om-FP16.om (编译模型 / FP16)
• yolov9s.pt (源模型 / 源模型下载; 源模型 / 源模型元数据)
• yolov9s.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据)

Upstream Links

• Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=j9brj6ooi000
• Upstream repository: https://gitee.com/Hispark/modelzoo/tree/master/samples/samples_GPL/built-in/yolov9s
• 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.