DepthAI FFC - Modular Cameras

BW1098FFC

Use DepthAI on your existing host. Since the AI/vision processing is done on the Myriad X, a typical desktop could handle tens of DepthAIs plugged in (the effective limit is how many USB ports the host can handle).

Requirements

Board Layout

BW1098FFC layout
Reference table

A. 5V IN

E. Left Camera Port

B. USB3C

F. DepthAI Module

C. Right Camera Port

G. Myriad X GPIO Access

D. Color Camera Port

What’s in the box?

  • BW1098FFC Carrier Board

  • USB3C cable (3 ft.)

  • Power Supply

Setup

Follow the steps below to setup your DepthAI device.

  1. Connect your modular cameras.

    The FFC (flexible flat cable) Connectors on the BW1098FFC require care when handling. Once inserted and latched, the connectors are robust, but they are easily susceptible to damage during the de-latching process when handling the connectors, particularly if to much force is applied during this process.

    The video below shows a technique without any tool use to safely latch and delatch these connectors.

    Connecting the Modular Cameras to BW1098FFC

    Once the flexible flat cables are securely latched, you should see something like this:

    BW1098FFC Connected to Modular Cameras

    Note

    Note when looking at the connectors, the blue stripe should be facing up.

    BW1098FFC modular camera top side

    Warning

    Make sure that the FFC cables connect to the camera is on the top side of the final setup to avoid inverted images and wrong swap_left_and_right_cameras setup.

  2. Connect your host to the DepthAI USB carrier board.

  3. Connect the DepthAI USB power supply (included).

  4. Calibrate the cameras.

Verify installation

We’ll execute a DepthAI example Python script to ensure your setup is configured correctly. Follow these steps to test DepthAI:

  1. Start a terminal session.

  2. Clone the depthai example repository.

git clone https://github.com/luxonis/depthai.git
  1. Access your local copy of depthai.

cd [depthai repo]
  1. Install the example repository requirements.

python -m pip install -r requirements.txt
  1. Run demo script.

python3 depthai_demo.py

The script launches a window, starts the cameras, and displays a video stream annotated with object localization metadata:

Depth projection

In the screenshot above, DepthAI identified a TV monitor (1.286 m from the camera) and a chair (3.711 m from the camera).

See the list of object labels in our pre-trained OpenVINO model tutorial.

Got questions?

We’re always happy to help with code or other questions you might have.