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 / A16W8)
• —yolov9sFP16Hi3403V100-NNN.om (编译模型 / FP16 / FP16)
• —yolov9s.pt (源模型 / 源模型下载)
• —yolov9s.onnx (源模型 / 源模型下载)

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.
• —Cover image: 1737486946598914_202103071025384.jpg