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Open-weight model · Image classification

RK182X-CNN-ResNet50V2

by RKNNAI RKNNAI/RK182X-CNN-ResNet50V2

RK182X-CNN-ResNet50V2 is an open-weight model for image classification from RKNNAI, released under Apache License 2.0. Its published files total 26.3 MB.

本仓库提供由 onnx/models 转换得到的 RKNN CNN 模型。 - Model ID:RKNNAI/RK182X-CNN-ResNet50V2 - 模型显示名称:RK182X-CNN-ResNet50V2 - 源模型:onnx/models - 模型类型:CNN ModelScope 完整下载: Hugging Face 完整下载: ModelScope 指定配置下载: Hugging Face 指定配置下载: - 使用配套 RKNN Runtime 和驱动;运行前用 rknn-smi -v…

Parameters—
Context—
Weights26.3 MB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—

Model Card

By RKNNAI, published under apache-2.0, revision 3d99331309e7.

本仓库提供由 onnx/models 转换得到的 RKNN CNN 模型。 - Model ID:RKNNAI/RK182X-CNN-ResNet50V2 - 模型显示名称:RK182X-CNN-ResNet50V2 - 源模型:onnx/models - 模型类型:CNN ModelScope 完整下载: Hugging Face 完整下载: ModelScope 指定配置下载: Hugging Face 指定配置下载: - 使用配套 RKNN Runtime 和驱动;运行前用 rknn-smi -v 检查设备端版本。 - 源模型许可证:Apache License 2.0,正文见 LICENSE,归属和转换说明见 NOTICE。 - 本仓库交付物是源模型的 RKNN 转换衍生物,仍受源模型许可和使用限制约束。 - 同时遵守 RKNN Toolkit、RKNN Runtime 相关许可;本仓库不包含运行库。

Read RKNNAI's full model card

1. 模型介绍

本仓库提供由 onnx/models 转换得到的 RKNN CNN 模型。

  • Model ID:RKNNAI/RK182X-CNN-ResNet50V2
  • 模型显示名称:RK182X-CNN-ResNet50V2
  • 发布版本:v1.1.0
  • 源模型:onnx/models
  • 模型类型:CNN
  • 芯片字段:RK182X
  • 具体支持芯片:RK1820、RK1828

可用模型

发布版本 配置目录 支持芯片 分辨率 量化方式 NPU 核数
v1.1.0 ResNet50V2-224x224-w8a8-1 RK1820、RK1828 224x224 w8a8 1

2. 文件说明

文件或目录 说明
LICENSE 源模型许可证
NOTICE 许可、使用要求及归属说明
<配置目录>/ 配套模型文件
子目录 README.md 当前配置说明
子目录 config.json 模型配置与文件清单
子目录 SHA256SUMS 当前目录交付文件的 SHA-256 校验值(不包含自身)

3. 模型下载

ModelScope 完整下载:

modelscope download --model RKNNAI/RK182X-CNN-ResNet50V2 --revision v1.1.0 --local_dir ./RK182X-CNN-ResNet50V2

Hugging Face 完整下载:

hf download RKNNAI/RK182X-CNN-ResNet50V2 --revision v1.1.0 --local-dir ./RK182X-CNN-ResNet50V2

ModelScope 指定配置下载:

from modelscope import snapshot_download

snapshot_download(
    "RKNNAI/RK182X-CNN-ResNet50V2",
    revision="v1.1.0",
    allow_patterns=["README.md", "LICENSE", "NOTICE", "ResNet50V2-224x224-w8a8-1/**"],
    local_dir="./RK182X-CNN-ResNet50V2",
)

Hugging Face 指定配置下载:

hf download RKNNAI/RK182X-CNN-ResNet50V2 --revision v1.1.0 --include "README.md" "LICENSE" "NOTICE" "ResNet50V2-224x224-w8a8-1/**" --local-dir ./RK182X-CNN-ResNet50V2

4. SHA-256 校验

在配置目录执行:

cd ./RK182X-CNN-ResNet50V2/ResNet50V2-224x224-w8a8-1
sha256sum -c SHA256SUMS

所有条目显示 OK 后再部署。

5. 兼容性与限制

  • 支持芯片:RK1820、RK1828。
  • 使用配套 RKNN Runtime 和驱动;运行前用 rknn-smi -v 检查设备端版本。
  • 所选配置目录内的文件须配套使用。

6. 版权与许可证

  • 源模型许可证:Apache License 2.0,正文见 LICENSE,归属和转换说明见 NOTICE。
  • 本仓库交付物是源模型的 RKNN 转换衍生物,仍受源模型许可和使用限制约束。
  • 同时遵守 RKNN Toolkit、RKNN Runtime 相关许可;本仓库不包含运行库。

Identity and Version

Repository
RKNNAI/RK182X-CNN-ResNet50V2
Publisher
RKNNAI
Task
Image classification
Modality
Image
Library
Not stated by the source
Parameters
Not stated by the source
Languages
cnn
Revision
3d99331309e7861ff1d0333db7979b46a8e07ae1
First published
2026-09-24
Last updated
2026-09-28

Files and Weights

10 files, 26.3 MB in total.

Configuration1 file · 2.2 KB
Documentation4 files · 16.4 KB
Other4 files · 26.3 MB
Repository1 file · 1.7 KB
Every file
FileTypeSizeSHA-256
ResNet50V2-224x224-w8a8-1/config.jsonConfiguration2.2 KB —
LICENSEDocumentation11.4 KB —
NOTICEDocumentation475 B —
README.mdDocumentation2.7 KB —
ResNet50V2-224x224-w8a8-1/README.mdDocumentation1.8 KB —
ResNet50V2-224x224-w8a8-1/ResNet50V2-model_report.htmlOther74.5 KB —
ResNet50V2-224x224-w8a8-1/ResNet50V2.rknnOther196.7 KB 4021f099497c
ResNet50V2-224x224-w8a8-1/ResNet50V2.weightOther26.0 MB 397dbc06c832
ResNet50V2-224x224-w8a8-1/SHA256SUMSOther415 B —
.gitattributesRepository1.7 KB —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download from RKNNAI

Released by RKNNAI through its official repository on Hugging Face. Read the license.

Questions About RK182X-CNN-ResNet50V2

Can I use RK182X-CNN-ResNet50V2 commercially?

Yes. RK182X-CNN-ResNet50V2 is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

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