Seeed Studio Grove Vision AI & SenseCAP A1101 firmware

Edge Impulse enables developers to create the next generation of intelligent device solutions with embedded Machine Learning. This repository contains the Edge Impulse firmware for the Seeed Studio Grove Vision AI module and for the SenseCAP A1101. This device supports all Edge Impulse features, including ingestion, remote management, and inferencing.

See our tutorials on how to use both devices with Edge Impulse Studio

• Grove Vision AI Module
• SenseCAP A1101

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NOTE

If you are using the Grove Vision AI module or SenseCAP A1101 with Edge Impulse for the first time, upgrade the firmware on the USB-UART BL702 converter.

1. Download the following firmware from Edge Impulse CDN server.
2. Follow the instruction to flash the BL702 firmware.

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Source code organization

• You can find the main firmware source code here:

  Synopsys_PA8535_EM9D_DFSS_SDK_3.3/app/scenario_app/edge_impulse_visionai Synopsys_PA8535_EM9D_DFSS_SDK_3.3/app/scenario_app/edge_impulse_sensecap

• To build the firmware, use the following makefile:

  Synopsys_PA8535_EM9D_DFSS_SDK_3.3/makefile and pass APP_TYPE (one of: edge_impulse_visionai or edge_impulse_cansecap)

• If you want to deploy your model (exported as a C++ Library from Studio), extract the exported zip file content into:

  Synopsys_PA8535_EM9D_DFSS_SDK_3.3/app/scenario_app/edge_impulse_visionai/ei-model Synopsys_PA8535_EM9D_DFSS_SDK_3.3/app/scenario_app/edge_impulse_sensecap/ei-model

Reporting issues

This repository is a snapshot of the Edge Impulse internal code base, therefore PRs won't be merged. If you find any bugs or want to contribute use our Developer Forum to submit them.

How to build the firmware?

You can build firmware using the provided Dockerfile (the most straightforward solution). Another option is a native local build.

Build firmware using Docker

1. Make sure you have Docker installed.

2. Build the container:

   docker build -t seeed-vision-ai-build .

3. Run the build script using

   docker run -v $PWD:/app seeed-vision-ai-build edge_impulse_visionai

   Or use edge_impulse_sensecap as a parameter to build firmware for SenseCAP A1101.

4. You can find the resulting firmware in firmware.uf2 file.

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NOTE If you build the firmware once and then swap the ML model, do a clean rebuild

docker run -v $PWD:/app seeed-vision-ai-build clean
docker run -v $PWD:/app seeed-vision-ai-build edge_impulse_visionai

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Build using native tools

We tested this build method on Ubuntu 20.04 and Fedora 36.

1. Install the required tools

   sudo apt install make
   sudo apt install python3-numpy

2. Download and install the GNU toolchain for ARC processors

   cd ~
   wget https://github.com/foss-for-synopsys-dwc-arc-processors/toolchain/releases/download/arc-2020.09-release/arc_gnu_2020.09_prebuilt_elf32_le_linux_install.tar.gz
   tar -xvf arc_gnu_2020.09_prebuilt_elf32_le_linux_install.tar.gz
   export PATH="$HOME/arc_gnu_2020.09_prebuilt_elf32_le_linux_install/bin:$PATH"

3. Build the firmware and convert it into UF2 format. For Grove Vision AI:

   cd firmware-seeed-vision-ai-internal/Synopsys_PA8535_EM9D_DFSS_SDK_3.3
   APP_TYPE=edge_impulse_visionai make
   make flash
   python3 tools/ufconv/uf2conv.py -t 0 -c tools/image_gen_cstm/output/output.img -o firmware.uf2

   Or use APP_TYPE=edge_impulse_sensecap for SenseCAP A1101.

Flashing the board

Grove Vision AI

1. Connect Grove Vision AI Module to the host PC via USB Type-C cable
2. Double-click the BOOT button on the Grove Vision AI Module to enter mass storage mode
3. After this, you will see a new storage drive shown on your file explorer as GROVEAI
4. Drag and drop the previous firmware.uf2 file to GROVEAI drive

Once the copying is finished, GROVEAI drive will disappear.

SenseCAP A1101

1. Connect SenseCAP A1101 to the host PC via USB Type-C cable
2. Double-click the button next to the USB-C socket to enter mass storage mode
3. After this, you will see a new storage drive shown on your file explorer as VISIONAI
4. Drag and drop the previous firmware.uf2 file to VISIONAI drive

How to view the camera stream?

1. Install Edge Impulse CLI tools

2. Connect your device to the PC, open the terminal/command line, and run:

   edge-impulse-run-impulse --debug

3. You should see an output similar to the one below. Open the link

   Edge Impulse impulse runner v1.15.1
   [SER] Connecting to /dev/tty.usbmodem21401
   [SER] Serial is connected, trying to read config...
   [SER] Retrieved configuration
   [SER] Device is running AT command version 1.7.0
   
   Want to see a feed of the camera and live classification in your browser? Go to http://127.0.0.1:4915
   

   Open the displayed link in a browser, and you will see the preview: