Add files using upload-large-folder tool

README.md

@@ -0,0 +1,65 @@
+---
+language:
+- zh
+tags:
+- hisilicon
+- hispark
+- npu
+- openharmony
+- modelzoo
+- pytorch
+---
+
+# VGG16
+
+VGGNet是牛津大学计算机视觉组（Visual Geometry Group）和Google DeepMind公司的研究员一起研发的深度卷积神经网络，它探索了卷积神经网络的深度与其性能之间的关系，通过反复堆叠3*3的小型卷积核和2*2的最大池化层，成功地构筑了16~19层深的卷积神经网络。VGGNet相比之前state-of-the-art的网络结构，错误率大幅下降，VGGNet论文中全部使用了3*3的小型卷积核和2*2的最大池化核，通过不断加深网络结构来提升性能。
+
+## Mirror Metadata
+
+- Hugging Face repo: shadow-cann/hispark-modelzoo-vgg16
+- Portal model id: ht96f9b50o00
+- Created at: 2025-11-17 11:25:12
+- Updated at: 2025-11-29 14:49:58
+- Category: 计算机视觉
+
+## Framework
+
+- PyTorch
+
+## Supported OS
+
+- OpenHarmony
+- Linux
+
+## Computing Power
+
+- Hi3403V100 SVP_NNN
+- Hi3403V100 NNN
+
+## Tags
+
+- 分类
+
+## Detail Parameters
+
+- 输入: 224x224
+- 参数量: 138.358M
+- 计算量: 31.007GFLOPs
+
+## Files In This Repo
+
+- vgg16.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据; 编译模型 / OM 元数据 / a8w8)
+- vgg16-397923af.pth (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=ht96f9b50o00
+- Upstream repository: https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16
+- License reference: https://github.com/pytorch/vision/blob/main/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: 1712668134146051_panda1.jpg

SVP_NNN_PC_V1.0.6.0.tgz

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:536b103d08e9490f968207326798e1fc50ea4234888b73db729cd6e6a04c5d8b
+size 31072256

model-card.json

@@ -0,0 +1,326 @@
+{
+  "name": "VGG16",
+  "id": "ht96f9b50o00",
+  "description": "VGGNet是牛津大学计算机视觉组（Visual Geometry Group）和Google DeepMind公司的研究员一起研发的深度卷积神经网络，它探索了卷积神经网络的深度与其性能之间的关系，通过反复堆叠3*3的小型卷积核和2*2的最大池化层，成功地构筑了16~19层深的卷积神经网络。VGGNet相比之前state-of-the-art的网络结构，错误率大幅下降，VGGNet论文中全部使用了3*3的小型卷积核和2*2的最大池化核，通过不断加深网络结构来提升性能。",
+  "category": "计算机视觉",
+  "framework": [
+    "PyTorch"
+  ],
+  "supportOs": [
+    "OpenHarmony",
+    "Linux"
+  ],
+  "computingPower": [
+    "Hi3403V100 SVP_NNN",
+    "Hi3403V100 NNN"
+  ],
+  "tags": [
+    "分类"
+  ],
+  "repositoryUrl": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16",
+  "licenseUrl": "https://github.com/pytorch/vision/blob/main/LICENSE",
+  "downloads": [
+    {
+      "fileName": "vgg16.onnx",
+      "variants": [
+        "源模型 / 源模型下载",
+        "源模型 / 源模型元数据",
+        "编译模型 / OM 元数据 / a8w8"
+      ]
+    },
+    {
+      "fileName": "vgg16-397923af.pth",
+      "variants": [
+        "源模型 / 源模型下载",
+        "源模型 / 源模型元数据"
+      ]
+    },
+    {
+      "fileName": "SVP_NNN_PC_V1.0.6.0.tgz",
+      "variants": [
+        "附加资源 / 附加资源"
+      ]
+    }
+  ],
+  "apiDetail": {
+    "createdBy": 138418613601624,
+    "creationDate": "2025-11-17 11:25:12",
+    "creationUserCN": "ahau15",
+    "lastUpdatedBy": null,
+    "lastUpdateDate": "2025-11-29 14:49:58",
+    "lastUpdateUserCN": "ahau15",
+    "rowIdx": -1,
+    "id": "ht96f9b50o00",
+    "name": "VGG16",
+    "isBeta": 0,
+    "betaVersionDesc": "",
+    "description": "VGGNet是牛津大学计算机视觉组（Visual Geometry Group）和Google DeepMind公司的研究员一起研发的深度卷积神经网络，它探索了卷积神经网络的深度与其性能之间的关系，通过反复堆叠3*3的小型卷积核和2*2的最大池化层，成功地构筑了16~19层深的卷积神经网络。VGGNet相比之前state-of-the-art的网络结构，错误率大幅下降，VGGNet论文中全部使用了3*3的小型卷积核和2*2的最大池化核，通过不断加深网络结构来提升性能。",
+    "parentId": "ht96f9b50o00",
+    "coverImageId": 1712668134146051,
+    "coverImageUrl": "https://openxinhuo-board-image.obs.cn-east-3.myhuaweicloud.com/1712668134146051%2Fpanda1.jpg",
+    "modelEffectId": null,
+    "modelEffectUrl": "",
+    "computerVersion": [
+      "分类"
+    ],
+    "naturalLanguageProcess": [],
+    "multimodal": [],
+    "video": [],
+    "framework": [
+      "PyTorch"
+    ],
+    "modelRepository": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16",
+    "originModel": [
+      {
+        "id": "1712668270526466",
+        "name": "vgg16.onnx",
+        "url": null,
+        "size": "553434827"
+      },
+      {
+        "id": "1712668270460930",
+        "name": "vgg16-397923af.pth",
+        "url": null,
+        "size": "553433881"
+      }
+    ],
+    "originModelLink": null,
+    "dataSet": "https://image-net.org/",
+    "modelLicense": "https://github.com/pytorch/vision/blob/main/LICENSE",
+    "detailParams": [
+      {
+        "name": "输入",
+        "value": "224x224"
+      },
+      {
+        "name": "参数量",
+        "value": "138.358M"
+      },
+      {
+        "name": "计算量",
+        "value": "31.007GFLOPs"
+      }
+    ],
+    "quickStart": {
+      "url": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16",
+      "markDownUrl": "",
+      "developLanguage": [
+        {
+          "language": "C++",
+          "context": "{\"ops\":[{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#080808\"},\"insert\":\"VGG16模型可以通过以下代码完成快速推理\"},{\"attributes\":{\"text-indent\":\"0px\"},\"insert\":\"\\n\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"#include \\\"model.h\\\"\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"#include \\\"log.h\\\"\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\\n\"},{\"insert\":\"using namespace Infer;\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\\n\"},{\"insert\":\"int main()\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"{\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    EnvInit();\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    std::string omModelPath = \\\"/path/to/model.om\\\"; // VGG16模型文件路径 \"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    std::string imagePath = \\\"/path/to/image.jpg\\\"; // 输入图片路径\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    std::unique_ptr<Model> model = std::make_unique<Model>();\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    if (model->Load(omModelPath, ModelType::VGG16) != 0) {\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        LOG(ERROR) << \\\"fail to load model\\\";\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        return -1;\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    }\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    auto ret = model->Infer(imagePath, FileType::SingelImageFile);\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    if (ret.size() == 0) {\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        LOG(ERROR) << \\\"fail to infer model\\\";\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        model->Unload();\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        return -1;\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    }\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    if (model->Unload() != 0) {\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        LOG(ERROR) << \\\"fail to unload model\\\";\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"        return -1;\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    }\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    EnvDeinit();\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"    return 0;\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"insert\":\"}\"},{\"attributes\":{\"text-indent\":\"0px\",\"code-block\":\"plain\"},\"insert\":\"\\n\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#080808\"},\"insert\":\"备注：上述C++代码依赖的动态库与头文件位于\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#315fbd\",\"link\":\"https://gitee.com/HiSpark/modelzoo/tree/master/samples/common\"},\"insert\":\"/samples/common\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#080808\"},\"insert\":\"目录下，编译相关配置参考\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#315fbd\",\"link\":\"https://gitee.com/HiSpark/modelzoo/blob/master/samples/built-in/classification/VGG16/src/CMakeLists.txt\"},\"insert\":\"CMakeLists.txt\"},{\"attributes\":{\"background\":\"#ffffff\",\"size\":\"13px\",\"color\":\"#080808\"},\"insert\":\"。\"},{\"attributes\":{\"text-indent\":\"0px\"},\"insert\":\"\\n\\n\"}]}"
+        }
+      ]
+    },
+    "status": "released",
+    "currentHandler": "",
+    "currentHandlerName": null,
+    "jsonPath": "https://gitee.com/HiSpark/modelzoo-dev/blob/master/samples/built-in/classification/VGG16/VGG16.json",
+    "modelAdaptor": [
+      {
+        "createdBy": null,
+        "creationDate": null,
+        "creationUserCN": null,
+        "lastUpdatedBy": null,
+        "lastUpdateDate": null,
+        "lastUpdateUserCN": null,
+        "rowIdx": -1,
+        "id": "i8ttm5k1tc00",
+        "name": "Hi3403V100 SVP_NNN",
+        "modelId": "ht96f9b50o00",
+        "modelName": "VGG16",
+        "supportNames": [
+          "a8w8"
+        ],
+        "toolkit": [
+          {
+            "name": "CANN工具",
+            "url": "https://hispark-obs.obs.cn-east-3.myhuaweicloud.com/SVP_NNN_PC_V1.0.6.0.tgz",
+            "desc": "Al异构计算架构；提升计算效率的关键平台",
+            "imgId": "cann"
+          },
+          {
+            "name": "编译工具链",
+            "url": "https://gitee.com/HiSpark/pegasus/blob/Beta-v0.9.1/docs/Hi3403V100%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA%E6%8C%87%E5%8D%97/Hi3403V100%E7%8E%AF%E5%A2%83%E6%90%AD%E5%BB%BA%E6%8C%87%E5%8D%97.md#241%E5%AE%89%E8%A3%85clang%E4%BA%A4%E5%8F%89%E7%BC%96%E8%AF%91%E5%99%A8",
+            "desc": "高效编译，精准适配；AI性能优化，应用流畅运行",
+            "imgId": "tool"
+          },
+          {
+            "name": "SDK",
+            "url": "https://gitee.com/HiSpark/ss928v100_clang/tree/Beta-v0.9.1/ ",
+            "desc": "稳定、易用的设计；支撑客户快速产品量产",
+            "imgId": "sdk"
+          }
+        ],
+        "supportOs": [
+          "OpenHarmony",
+          "Linux"
+        ],
+        "supportQuantify": [
+          {
+            "createdBy": 132241120926760,
+            "creationDate": "2026-03-26 20:25:39",
+            "creationUserCN": "liaoshibin",
+            "lastUpdatedBy": 132241120926760,
+            "lastUpdateDate": "2026-03-26 20:25:39",
+            "lastUpdateUserCN": "liaoshibin",
+            "rowIdx": -1,
+            "id": "j6tn8j0ctk00",
+            "name": "a8w8",
+            "computingId": "i8ttm5k1tc00",
+            "computingName": "Hi3403V100 SVP_NNN",
+            "omOfflineModelUrl": null,
+            "omOfflineModelId": 1712669402923010,
+            "omOfflineModelSize": "138529095",
+            "omOfflineModelName": "vgg16.om",
+            "omOfflineModel": [
+              {
+                "id": "1712669402923010",
+                "name": "vgg16.om",
+                "url": null,
+                "size": "138529095"
+              }
+            ],
+            "omOfflineModelLink": null,
+            "releaseTime": "2025-11-17",
+            "boardOs": null,
+            "modelLicense": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16/LICENSE",
+            "modelPerformance": [
+              {
+                "performanceValue": "12.88",
+                "unit": "耗时（ms）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "77.65",
+                "unit": "性能（fps）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "133.486",
+                "unit": "单帧内存带宽（MB）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "143.195",
+                "unit": "内存（MB）",
+                "desc": ""
+              }
+            ],
+            "deleted": 0
+          }
+        ],
+        "deleted": 0
+      },
+      {
+        "createdBy": null,
+        "creationDate": null,
+        "creationUserCN": null,
+        "lastUpdatedBy": null,
+        "lastUpdateDate": null,
+        "lastUpdateUserCN": null,
+        "rowIdx": -1,
+        "id": "i8ttm5k1tc01",
+        "name": "Hi3403V100 NNN",
+        "modelId": "ht96f9b50o00",
+        "modelName": "VGG16",
+        "supportNames": [
+          "fp16"
+        ],
+        "toolkit": [
+          {
+            "name": "CANN工具",
+            "url": "",
+            "desc": "5.30.t11.7.b110； (请联系FAE获取)",
+            "imgId": "cann"
+          },
+          {
+            "name": "编译工具链",
+            "url": "",
+            "desc": "aarch64-mix210-linux-gcc；(请联系FAE获取)",
+            "imgId": "tool"
+          },
+          {
+            "name": "SDK",
+            "url": "",
+            "desc": "SS928 V100R001C02SPC022； (请联系FAE获取)",
+            "imgId": "sdk"
+          }
+        ],
+        "supportOs": [
+          "Linux"
+        ],
+        "supportQuantify": [
+          {
+            "createdBy": 132241120926760,
+            "creationDate": "2026-03-26 20:25:39",
+            "creationUserCN": "liaoshibin",
+            "lastUpdatedBy": 132241120926760,
+            "lastUpdateDate": "2026-03-26 20:25:39",
+            "lastUpdateUserCN": "liaoshibin",
+            "rowIdx": -1,
+            "id": "j6tn8j1otk00",
+            "name": "fp16",
+            "computingId": "i8ttm5k1tc01",
+            "computingName": "Hi3403V100 NNN",
+            "omOfflineModelUrl": null,
+            "omOfflineModelId": 1712670610882563,
+            "omOfflineModelSize": "277334329",
+            "omOfflineModelName": "vgg16.om",
+            "omOfflineModel": [
+              {
+                "id": "1712670610882563",
+                "name": "vgg16.om",
+                "url": null,
+                "size": "277334329"
+              }
+            ],
+            "omOfflineModelLink": null,
+            "releaseTime": "2025-11-17",
+            "boardOs": null,
+            "modelLicense": "https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/classification/VGG16/LICENSE",
+            "modelPerformance": [
+              {
+                "performanceValue": "30.74",
+                "unit": "耗时（ms）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "32.53",
+                "unit": "性能（fps）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "373.265",
+                "unit": "单帧内存带宽（MB）",
+                "desc": ""
+              },
+              {
+                "performanceValue": "582.809",
+                "unit": "内存（MB）",
+                "desc": ""
+              }
+            ],
+            "deleted": 0
+          }
+        ],
+        "deleted": 0
+      }
+    ],
+    "saveType": null,
+    "deleteType": null,
+    "latest": "Y",
+    "deleted": 0,
+    "modelPhase": "released",
+    "remark": null,
+    "fileInfo": null,
+    "reviewType": null,
+    "owner": "ahau15",
+    "ownerBy": 138418613601624,
+    "optional": null,
+    "optionalList": null,
+    "optionalBy": null,
+    "downloadNum": 8,
+    "collectNum": null,
+    "isCollect": null
+  }
+}

vgg16-397923af.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:397923af8e79cdbb6a7127f12361acd7a2f83e06b05044ddf496e83de57a5bf0
+size 553433881

vgg16.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c9d0bb14d956e3b85444350ce6acdb092c632b5088320ae35a05b68f0923dc24
+size 553434827