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.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+superpoint_bs1_om-A8W8.om filter=lfs diff=lfs merge=lfs -text
+superpoint_bs1.om filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,67 @@
+---
+language:
+- zh
+tags:
+- hisilicon
+- hispark
+- npu
+- openharmony
+- modelzoo
+- pytorch
+---
+
+# SuperPoint
+
+SuperPoint模型的全卷积神经网络架构对全尺寸图像进行操作，并在单次前向传递中产生伴随固定长度描述符的兴趣点检测。该模型有一个单一的共享编码器来处理和减少输入图像的维数。在编码器之后，该架构分成两个解码器“头”，它们学习任务特定权重——一个用于兴趣点检测，另一个用于感兴趣点描述。大多数网络参数在两个任务之间共享，这与传统系统不同，传统系统首先检测兴趣点，然后计算描述符，并且缺乏跨两个任务共享计算和表示的能力。
+
+## Mirror Metadata
+
+- Hugging Face repo: shadow-cann/hispark-modelzoo-superpoint
+- Portal model id: j3n1o7csso00
+- Created at: 2026-03-16 21:11:02
+- Updated at: 2026-03-26 09:35:38
+- Category: 计算机视觉
+
+## Framework
+
+- PyTorch
+
+## Supported OS
+
+- OpenHarmony
+- Linux
+
+## Computing Power
+
+- Hi3403V100 SVP_NNN
+- Hi3403V100 NNN
+
+## Tags
+
+- 特征点检测
+
+## Detail Parameters
+
+- 输入: 240x320
+- 参数量: 1.24M
+- 计算量: 13.116GFLOPs
+
+## Files In This Repo
+
+- superpoint_bs1_om-A8W8.om (编译模型 / A8W8)
+- superpoint_bs1.om (编译模型 / FP16; 编译模型 / OM 元数据 / A8W8)
+- superpoint_bs1.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据)
+- superPointNet_170000_checkpoint.pth (源模型 / 源模型下载)
+- 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=j3n1o7csso00
+- Upstream repository: https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/point/SuperPoint
+- License reference: https://github.com/eric-yyjau/pytorch-superpoint/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: 1702559012290562_cat_320x240_draw_keypoints.jpg

SVP_NNN_PC_V1.0.6.0.tgz

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