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products:sbc:vim3:npu:npu-prebuilt-demo-usage

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NPU Prebuilt Demo Usage

  1. Please follow this docs to upgrade the system to latest version before run any NPU demos.
  2. Just support Opencv4

install OpenCV4

Install-OpenCV4.sh
sudo apt install libopencv-dev python3-opencv

Get NPU Demo

NPU Demo is not installed on the board by default. You need to download it from github first

1) Clone to the board through the git command.

get-npu-demo-from-demo.sh
 cd {workspace}
 git clone --recursive https://github.com/khadas/aml_npu_demo_binaries

2) Or download the compressed package directly, and then unzip it to the board.

  There are three directories in NPU Demo:

detect_demo

  1. detect_demo: A collection of yolo series models for camera dynamic recognition.

detect_demo_picture

  1. detect_demo_picture: A collection of yolo series models that identify pictures.

inceptionv3

  1. inceptionv3: Identify the inception model of the picture

Inception Model

  1. The inception model does not need to install any libraries into the system. Enter the inceptionv3 directory.
  2. imagenet_slim_labels.txt is a label file. After the result is identified, the label corresponding to the result can be queried in this file.
 $ cd {workspace}/aml_npu_demo_binaries/inceptionv3
 $ ls
 dog_299x299.jpg  goldfish_299x299.jpg  imagenet_slim_labels.txt  VIM3  VIM3L

If your board is VIM3, enter the VIM3 directory, if it is VIM3L, then enter the VIM3L directory. Here is VIM3 as an example.

1  $ cd {workspace}/aml_npu_demo_binaries/inceptionv3/VIM3
2  $ inceptionv3  inception_v3.nb  run.sh

1  $ cd {workspace}/aml_npu_demo_binaries/inceptionv3/VIM3
2  $ ./run.sh
3  Create Neural Network: 59ms or 59022us
4  Verify...
5  Verify Graph: 0ms or 739us
6  Start run graph [1] times...
7  Run the 1 time: 20.00ms or 20497.00us
8  vxProcessGraph execution time:
9  Total   20.00ms or 20540.00us
10 Average 20.54ms or 20540.00us
11 --- Top5 ---
12 2: 0.833984
13 795: 0.009102
14 974: 0.003592
15 408: 0.002207
16 393: 0.002111

By querying imagenet_slim_labels.txt, the result is a goldfish, which is also correctly identified.You can use the method above to identify other images.

Last modified: 2022/09/16 02:34 by ivan