Raspberry Pi by Pi Foundation

Yes, I see the question from FANT0MAS. To clarify, Synthiam ARC can be installed on a Raspberry Pi 4 running Windows 11, which is currently the recommended setup for the best performance when using Windows on a Raspberry Pi. The Raspberry Pi 4 is specifically mentioned because it is a well-tested and widely used model with sufficient resources to handle Windows 11 and ARC.

The Raspberry Pi 5 has not been released as of my knowledge cutoff date, so I cannot provide information on that model. If a new version, such as the Raspberry Pi 5, has been released after my knowledge cutoff date, it would be best to refer to the latest documentation and support articles on the Synthiam website for compatibility and recommendations.

@Athena, Now that the Raspberry Pi 5 is available. But the WOR Windows 11 documents appear to say that WIFI is not available. So how do we connect the Rasberry Pi 5 to the remote controlling computer ?

If the Raspberry Pi 5's Wi-Fi is not supported in the current Windows 11 installation, you can connect it to a remote controlling computer using a wired Ethernet connection. Here are some steps you can follow:

1. Ethernet Connection:

   • Connect the Raspberry Pi 5 to your network using an Ethernet cable. This will allow it to communicate with other devices on the same network, including your remote controlling computer.

2. USB Wi-Fi Adapter:

   • If you prefer a wireless connection, you can use a compatible USB Wi-Fi adapter that is supported by Windows 11. Plug the adapter into one of the USB ports on the Raspberry Pi 5, and it should allow you to connect to your Wi-Fi network.

3. Remote Desktop Software:

   • Once connected to the network, you can use remote desktop software to control the Raspberry Pi 5 from another computer. Windows Remote Desktop, VNC, or other similar tools can be used for this purpose.

4. Check for Updates:

   • Keep an eye on updates for Windows 11 on Raspberry Pi, as driver support for the built-in Wi-Fi may be added in the future.

For the latest information and compatibility details, it's always a good idea to check the official documentation or community forums related to Windows on Raspberry Pi.

I recently installed an EZB server on my Pi 3b+ and was having issues running it with a PiCamera.

I believe in 2022 they made the picamera library obsolete and replaced it with Picamera2. It seems that the Blueberry Server still uses the original removed picamera module, which causes and error.

I am trying to work on a fix for this although am stuck replacing the old capture_continuous function with one that works in Picamera 2 as well as the ARC software.

If anyone has a fix for this please let me know so I can continue using this software for my project.

Below is a possible workaround you can try while waiting for an official update to the Blueberry Server. The original PiCamera library’s capture_continuous function isn’t available in Picamera2, but you can simulate continuous capture by setting up your own loop that retrieves frames one at a time using Picamera2’s APIs. For example:

import time
from picamera2 import Picamera2

# Initialize and configure the camera
picam2 = Picamera2()
# Use a video configuration for continuous capture; adjust as needed for your use case.
video_config = picam2.create_video_configuration()
picam2.configure(video_config)
picam2.start()

try:
    while True:
        # Capture one frame as a numpy array
        frame = picam2.capture_array()

        # Process the frame or pass it along to the ARC software
        # For example, you might send the frame to a function that handles camera feed processing:
        # process_frame(frame)
        
        # Adjust the sleep time to control your effective frame rate
        time.sleep(0.1)
except KeyboardInterrupt:
    # Allow clean exit on interrupt (Ctrl+C)
    pass
finally:
    picam2.stop()

A Few Points to Consider

1. Frame Rate and Performance:
   Adjust the sleep duration in the loop (or implement a more robust timing mechanism) to achieve the desired frame rate without overloading the processor.

2. Integration with ARC:
   Depending on how the Blueberry Server expects to receive camera frames, you might need to convert or process the frames (e.g., encoding to JPEG or converting the numpy array to a format compatible with ARC hooks).

3. Threading or Asynchronous Handling:
   If the ARC software is doing other processing concurrently, consider running the capture loop in a separate thread or using asynchronous methods to prevent blocking the main execution thread.

4. Testing and Adjustments:
   The Picamera2 API is still evolving, and performance might vary between camera modules and Raspberry Pi models. Test thoroughly on your target hardware (Pi 3B+ in your case) and adjust the configuration settings as needed.

I hope this workaround helps you keep your project moving! If you encounter further issues or have questions about integrating the captured frames into ARC, feel free to ask for more guidance.