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- 1726646426140674_graspnet_16_9.jpg +3 -0
- README.md +61 -0
- graspnet[该模型文件仅用于非商用].onnx +3 -0
- model-card.json +200 -0
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README.md
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---
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| 2 |
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language:
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- zh
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tags:
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- hisilicon
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| 6 |
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- hispark
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| 7 |
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- npu
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| 8 |
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- openharmony
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| 9 |
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- modelzoo
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| 10 |
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- pytorch
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---
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# GraspNet
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GraspNet是一种基于点云输入的多阶段抓取姿态预测模型,由抓取视角估计和抓取姿态生成两个阶段组成,通过特征提取、视角估计、局部特征提取、抓取参数估计和预测解码一系列处理,最终生成包含抓取评分、抓取宽度、抓取高度、抓取深度、旋转矩阵、抓取中心点和物体ID的预测结果,旨在解决机器人抓取任务中的6D抓取姿态估计问题。
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## Mirror Metadata
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- Hugging Face repo: shadow-cann/hispark-modelzoo-graspnet
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- Portal model id: iodtp8ht0400
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- Created at: 2026-02-09 19:42:15
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- Updated at: 2026-02-12 11:24:22
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- Category: 计算机视觉
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## Framework
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| 26 |
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- PyTorch
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## Supported OS
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| 31 |
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- OpenEuler
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| 32 |
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## Computing Power
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| 34 |
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| 35 |
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- Hi3591PV100
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| 36 |
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## Tags
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- 具身智能
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## Detail Parameters
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- 计算量: 71.121GFLOPs
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- 输入: 720x1280
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- 参数量: 2.397M
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| 47 |
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## Files In This Repo
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| 48 |
+
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| 49 |
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- graspnet[该模型文件仅用于非商用].onnx (源模型 / 源模型下载; 源模型 / 源模型元数据)
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| 50 |
+
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| 51 |
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## Upstream Links
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| 52 |
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| 53 |
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- Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=iodtp8ht0400
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| 54 |
+
- Upstream repository: https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/README.md
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| 55 |
+
- License reference: https://github.com/graspnet/graspnet-baseline/blob/main/LICENSE
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| 56 |
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| 57 |
+
## Notes
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| 58 |
+
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| 59 |
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- This repository was mirrored from the HiSilicon Developer Portal model card and local downloads captured on 2026-03-27.
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| 60 |
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- File ownership follows the portal card mapping, not just filename similarity.
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| 61 |
+
- Cover image: 1726646426140674_graspnet_16_9.jpg
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graspnet[该模型文件仅用于非商用].onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:080a0171649a4a2f4c6a9310d871c33c661f078b1cbcf424b2939291b901ccc2
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| 3 |
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size 4942215
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model-card.json
ADDED
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@@ -0,0 +1,200 @@
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| 1 |
+
{
|
| 2 |
+
"name": "GraspNet",
|
| 3 |
+
"id": "iodtp8ht0400",
|
| 4 |
+
"description": "GraspNet是一种基于点云输入的多阶段抓取姿态预测模型,由抓取视角估计和抓取姿态生成两个阶段组成,通过特征提取、视角估计、局部特征提取、抓取参数估计和预测解码一系列处理,最终生成包含抓取评分、抓取宽度、抓取高度、抓取深度、旋转矩阵、抓取中心点和物体ID的预测结果,旨在解决机器人抓取任务中的6D抓取姿态估计问题。",
|
| 5 |
+
"category": "计算机视觉",
|
| 6 |
+
"framework": [
|
| 7 |
+
"PyTorch"
|
| 8 |
+
],
|
| 9 |
+
"supportOs": [
|
| 10 |
+
"OpenEuler"
|
| 11 |
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],
|
| 12 |
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"computingPower": [
|
| 13 |
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"Hi3591PV100"
|
| 14 |
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|
| 15 |
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"tags": [
|
| 16 |
+
"具身智能"
|
| 17 |
+
],
|
| 18 |
+
"repositoryUrl": "https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/README.md",
|
| 19 |
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"licenseUrl": "https://github.com/graspnet/graspnet-baseline/blob/main/LICENSE",
|
| 20 |
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"downloads": [
|
| 21 |
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{
|
| 22 |
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"fileName": "graspnet[该模型文件仅用于非商用].onnx",
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| 23 |
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"variants": [
|
| 24 |
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"源模型 / 源模型下载",
|
| 25 |
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"源模型 / 源模型元数据"
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| 26 |
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]
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| 27 |
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}
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| 28 |
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"apiDetail": {
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"createdBy": 139761718403620,
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"creationDate": "2026-02-09 19:42:15",
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"creationUserCN": "bazinga",
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"lastUpdatedBy": null,
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"lastUpdateDate": "2026-02-12 11:24:22",
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"rowIdx": -1,
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"id": "iodtp8ht0400",
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| 38 |
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"name": "GraspNet",
|
| 39 |
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"isBeta": 1,
|
| 40 |
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"betaVersionDesc": "该模型跟随Hi3591P配套版本正式发布",
|
| 41 |
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"description": "GraspNet是一种基于点云输入的多阶段抓取姿态预测模型,由抓取视角估计和抓取姿态生成两个阶段组成,通过特征提取、视角估计、局部特征提取、抓取参数估计和预测解码一系列处理,最终生成包含抓取评分、抓取宽度、抓取高度、抓取深度、旋转矩阵、抓取中心点和物体ID的预测结果,旨在解决机器人抓取任务中的6D抓取姿态估计问题。",
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"parentId": "ikh50q5l0400",
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"computerVersion": [
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"具身智能"
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"naturalLanguageProcess": [],
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"multimodal": [],
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"PyTorch"
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"modelRepository": "https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/README.md",
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"originModelLink": "",
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"dataSet": "https://github.com/graspnet/graspnet-baseline/blob/main/doc/example_data",
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"modelLicense": "https://github.com/graspnet/graspnet-baseline/blob/main/LICENSE",
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"detailParams": [
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{
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"name": "计算量",
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"value": "71.121GFLOPs"
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{
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"name": "输入",
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"value": "720x1280"
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"context": "{\"ops\":[{\"insert\":\"模型可以通过以下代码完成快速推理\"},{\"attributes\":{\"blockquote\":true},\"insert\":\"\\n\"},{\"insert\":\"#include \\\"model.h\\\"\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"#include \\\"log.h\\\"\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\\n\"},{\"insert\":\"using namespace Infer;\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\\n\"},{\"insert\":\"int main()\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"{\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" EnvInit();\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" std::string omModelPath = \\\"/path/to/model.om\\\"; // 模型文件路径 \"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" std::string filePath= \\\"/path/to/file_list_1.json\\\"; // 输入文本文件路径\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" std::unique_ptr<Model> model = std::make_unique<Model>();\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" if (model->Load(omModelPath, ModelType::GraspNet) != 0) {\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" LOG(ERROR) << \\\"fail to load model\\\";\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" return -1;\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" }\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" auto ret = model->Infer(filePath, FileType::JsonFile);\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" if (ret.size() == 0) {\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" LOG(ERROR) << \\\"fail to infer model\\\";\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" model->Unload();\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" return -1;\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" }\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" if (model->Unload() != 0) {\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" LOG(ERROR) << \\\"fail to unload model\\\";\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" return -1;\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" }\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" EnvDeinit();\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\" return 0;\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"}\"},{\"attributes\":{\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"16px\",\"color\":\"#40485b\",\"line-height\":\"1.6\"},\"insert\":\"备注:上述C++代码依赖的动态库与头文件位于\"},{\"attributes\":{\"background\":\"transparent\",\"size\":\"16px\",\"color\":\"#095eab\",\"line-height\":\"1.6\",\"link\":\"https://gitee.com/HiSpark/modelzoo/tree/master/samples/common\"},\"insert\":\"/samples/common\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"16px\",\"color\":\"#40485b\",\"line-height\":\"1.6\"},\"insert\":\"目录下,编译相关配置参考\"},{\"attributes\":{\"background\":\"transparent\",\"size\":\"16px\",\"color\":\"#095eab\",\"line-height\":\"1.6\",\"link\":\"https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/src/CMakeLists.txt\"},\"insert\":\"CMakeLists.txt\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"16px\",\"color\":\"#40485b\",\"line-height\":\"1.6\"},\"insert\":\"。\"},{\"attributes\":{\"blockquote\":true},\"insert\":\"\\n\"}]}"
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| 89 |
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}
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| 90 |
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]
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| 91 |
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},
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"jsonPath": "https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/GraspNet.json",
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"modelName": "GraspNet",
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"fp16"
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| 111 |
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],
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| 114 |
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"url": "",
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| 116 |
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"desc": "7.7.0.1.238-linux.aarch64-spc001;(请联系FAE获取)",
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{
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"name": "SDK",
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"url": "",
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"desc": "7.7.0.1.231-openEuler24.03.aarch64-rc-spc001;(请联系FAE获取)",
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| 147 |
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{
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| 148 |
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"id": "1727953442570241",
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| 149 |
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"name": "graspnet_linux_aarch64[该模型文件仅用于非商用].om",
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"releaseTime": "2026-01-31",
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"modelLicense": "https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/embodied_intelligence/GraspNet/LICENSE",
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| 158 |
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"modelPerformance": [
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| 159 |
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| 160 |
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| 161 |
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| 163 |
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},
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{
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"performanceValue": "0.75",
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| 166 |
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"unit": "性能(fps)",
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| 167 |
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| 168 |
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},
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{
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| 180 |
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"latest": "Y",
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