Raspberry Pi

In order to rotate a DSI-connected LCD screen like the Raspberry Pi 7″ LCD screen by 180 degrees, append

lcd_rotate=2

to /boot/config.txt

By default, the Raspberry Pi 4 USB-C port is not set to Host mode and therefore it’s not possible.

In order to set the USB-C port to host mode, add the following line to the end of /boot/config.txt (in the [all] section):

dtoverlay=dwc2,dr_mode=host

and

reboot

If you are trying to work with your StereoPi, you might have a situation in which Ethernet and USB are not working while the Raspberry Pi boots up and HDMI output works fine.

The reasons for this is that you are trying to power your board using the MicroUSB connector instead of using the USB power cable that comes with your StereoPi. The USB power cable is the one that has an USB Type-A connector at one end and the small white plug with a red and a black lead on the other side.

How to fix

• Unplug the MicroUSB cable from the StereoPi
• Unplug the USB power cable from
• Now plug in only the USB power cable
• In case your StereoPi doesn’t boot up immediately, switch the small switch on the StereoPi (which is adjacent to the socket where you connected the USB power cable) to the other side

Once your StereoPi has finished booting up, Ethernet and USB will work immediately

Why don’t USB & Ethernet work with the MicroUSB cable

If you are powering your StereoPi using the MicroUSB connector, only the Compute Module will be powered. All the functions of the StereoPi board, including USB power to the USB ports and the Ethernet chip will not receive power. Even if you have plugged in both MicroUSB and the USB power connector, you might have switched off the power switch – all will appear normal, as the Raspberry Pi boots up properly, but the StereoPi will not be powered properly.

Note that switching on the power from the USB power cable after the StereoPi has booted up will not fix the issue: While this will give power to the components on the StereoPi board, the operating system which is running on the StereoPi will not properly recognize the components. You need to reboot the StereoPi in order for the operating system to recognize all StereoPi components and initialize them correctly.

For more information on how to power the StereoPi, see the StereoPi wiki which contains a section on how to properly power the board.

The following code enables stereoscopic output (side-by-side mode) for the Raspberry Pi 3.

tvservice -e "CEA_3D_SBS 32"

It has been tested with a StereoPi 1 using a Raspberry Pi 3 Compute module and an ASUS VG series stereoscopic (shutter-style) monitor).

The default credentials for SSH login for the StereoPi SLP image are:

Username: root

Passwort: root

In our previous post How to capture RaspberryPi camera 10-bit raw image in Python we showed how you can use the picamera Python library to capture raw 10-bit image data.

The PNG image format supports storing 16-bit image data. This post shows you how to do that using the NumPy arrays we generated in our previous post. We are using the pypng library.

with open('16bit.png', 'wb') as outfile:
    writer = png.Writer(width=rawimg.shape[1], height=rawimg.shape[0], bitdepth=16, greyscale=False)
    # rawimg is a (w, h, 3) RGB uint16 array
    # but PyPNG needs a (w, h*3) array
    png_data = np.reshape(rawimg, (-1, rawimg.shape[1]*3))
    # Scale 10 bit data to 16 bit values (else it will appear black)
    # NOTE: Depending on your photo and the settings,
    #  it might still appear quite dark!
    png_data *= int(2**6)
    writer.write(outfile, png_data)

Note that the resulting PNGs are ~9.9 Megabytes in size and saving them using pypng takes about 27 seconds to save the image on my Raspberry Pi 3!

For comparison, the raw NumPy data is ~29 Megabytes whereas the compressed NumPy data is 9.3 Megabytes,

• Raw NumPy data (np.save): 29 Megabytes, takes 0.11 seconds to save.
• Compressed NumPy data (np.savez_compressed): 9.3 Megabytes, take 12 seconds to save.

So if your motivation for using PNG is to save space, you might be better off using NumPy compressed data, especially if you need to save many camera frames in quick succession and hence are limited.

In case you need to use PNGs, you might want to check Pypy since pypng is a pure Python library and hence might benefit from Pypy’s increased execution speed. However, in practice, pypy3 is more than 10x slower. Please read our detailed analysis at Is pypng 16-bit PNG encoding faster using pypy on the Raspberry Pi?

Full example:

#!/usr/bin/env python3
import picamera
import picamera.array
import numpy as np
import png

# Capture image
print("Capturing image...")
with picamera.PiCamera() as camera:
    with picamera.array.PiBayerArray(camera) as stream:
        camera.capture(stream, 'jpeg', bayer=True)
        # Demosaic data and write to rawimg
        # (stream.array contains the non-demosaiced data)
        rawimg = stream.demosaic()

# Write to PNG
print("Writing 16-bit PNG...")
with open('16bit.png', 'wb') as outfile:
    writer = png.Writer(width=rawimg.shape[1], height=rawimg.shape[0], bitdepth=16, greyscale=False)
    # rawimg is a (w, h, 3) RGB uint16 array
    # but PyPNG needs a (w, h*3) array
    png_data = np.reshape(rawimg, (-1, rawimg.shape[1]*3))
    # Scale 10 bit data to 16 bit values (else it will appear black)
    # NOTE: Depending on your photo and the settings,
    #  it might still appear quite dark!
    png_data *= int(2**6)
    writer.write(outfile, png_data)