2.4. Run trained neural network on the FPGA board

Blueoil prepared demonstration scripts to showcase the examples of classification and object detection using a DE10-Nano Kit board and USB camera.

2.4.1. Setup

  • The DE10-Nano: Prepare the board and create Linux system on microSD card. (Please see the detail in Installation)
  • USB camera: After setting up the DE10-Nano board, connect the USB camera to De10-Nano board. Make sure the camera is recognized by the device.

2.4.2. Preparation

  • From the Setup step, you should be able to login to the DE10-Nano through ssh inside an xterm program.

    $ ssh -X root@{DE10-Nano's IP}
    
  • Preparing the /demo (generated as output by blueoil convert) directory contains the following on the DE10-Nano:

demo
 ├── fpga
 │   └── soc_system.rbf
 ├── models
 │   ├── lib
 │   │   └── lib_fpga.so
 │   └── meta.yaml
 └── python
     ├── lmnet
     ├── requirements.txt
     └── usb_camera_demo.py

2.4.3. Update FPGA configuration

Explore into the demo/fpga directory, and copy soc_system.rbf to boot partition (/dev/mmcblk0p1).

  $ cd demo/fpga
  $ sudo mount /dev/mmcblk0p1 /media
  $ cp soc_system.rbf /media
  $ reboot

2.4.4. Run the demonstration

Explore into the demo/python directory, and execute the following command on the device.

$ cd demo/python
$ pip install -r requirements.txt
$ python usb_camera_demo.py \
      -l ../models/lib/lib_fpga.so \
      -c ../models/meta.yaml