Introduction
RKNN-Toolkit is a software development kit that provides users with model conversion, inference and performance evaluation on PC and Rockchip NPU platforms(RK1808/RK1806/RK3399Pro/RV1109/RV1126).
RKNN-Toolkit-Lite provides Python programming interfaces for Rockchip NPU platform to help users deploy RKNN models and accelerate the implementation of AI applications.
Note:
- For the deployment of the RKNN model, please refer to:
- RK1808/RK1806/RV1109/RV1126: https://github.com/rockchip-linux/rknpu
- RK3399Pro: https://github.com/airockchip/RK3399Pro_npu
- For RK3566/RK3568/RK3588/RK3588S/RV1103/RV1106, please refer to:
Download
From version 1.3.0, some wheel packages are larger than 100MB, can not be uploaded directly. So, you need to go to the releases page to download. You can download from releases page: https://github.com/rockchip-linux/rknn-toolkit/releases
- All wheel packages are in compressed file: rknn-toolkit-v1.7.3-packages.tar.gz or rknn-toolkit-v1.7.3-packages.zip
- All examples, docs and platform-tools are in compressed file: Source code(zip) or Source code(tar.gz)
- You can also download all packages, docker image, examples, docs and platform-tools from baidu cloud: rknn-toolkit, fetch code: rknn
- You can download RKNN Toolkit Lite packages and examples from rknn-toolkit-lite
Checksums
MD5
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20db420731b4976b15b0fbddef9984e3 rknn_toolkit-1.7.3-cp36-cp36m-macosx_10_15_x86_64.whl
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0cdd9c288a748bcef84848fd5dc12d80 rknn_toolkit-1.7.3-cp37-cp37m-linux_aarch64.whl
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a24f157407e16bc255fc387404eb2030 rknn-toolkit-v1.7.3-packages.tar.gz
8dbeeecb06b9201b9f464909ad8d9544 rknn-toolkit-v1.7.3-packages.zip
4b50d8966908e80567843c3623e33d46 rknn_toolkit_lite-1.7.3-cp36-cp36m-linux_aarch64.whl
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17f10789ec42fdc687c3c02ef6dc1141 rknn_toolkit_lite-1.7.3-cp37-cp37m-linux_aarch64.whl
030a09ed522620aa6dfb4ccac578518b rknn_toolkit_lite-1.7.3-cp37-cp37m-linux_armv7l.whl
079aaf9c2c39b2c2a6858688ed733973 rknn_toolkit_lite-1.7.3-cp37-cp37m-macosx_10_15_x86_64.whl
b1b32a4e8803dd9303ab1a72ae8deccf rknn_toolkit_lite-1.7.3-cp38-cp38-linux_x86_64.whl
Feedback and Community Support
- QQ Group Chat: 1025468710 (full, please join group 2)
- QQ Group Chat2: 547021958