Maybe if I share videos of half-finished projects it’ll motivate me to finish them!
Category: Video
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Controlling monitor inputs with DDC
I’m really happy that most modern monitors support DDC so that we can programmatically change settings rather than go through clunky OSDs.
The problem
At my desk I have my Mac Studio and my latest gaming PC and they both share a triple monitor setup. When I want to switch the monitors between the two, I either need to:
- Turn on auto-switching mode
- Manually change the input x 3
Auto-switching kinda worked, but has quirks I can’t live with. One is when I’m playing a game on the PC and the Mac wakes up for whatever reason, the PC receives a signal that hardware has been connected or disconnected and the screen freezes. It seems like a firmware bug to me – if an input is being actively used the others should be ignored.
The manual route is pretty bad as well. The M32U‘s input switchers are on the back of the monitor, which is pretty much the worst spot possible. Only the far right monitor is slightly more convenient to access.
How DDC solves it
By using m1ddc on the Mac we can easily script a way to switch between the two machines. 🎉 This means I can create a keyboard shortcut to toggle the inputs, a physical button, or even run it from an external computer. Hooray!
Edit: Now with web appi-ness!
I threw together a quick Flask app that can be accessed from any device on my network to switch inputs. Neato!
Note: Once I connect the left monitor the same way I connect the other two, the transition should be more in sync. Currently it’s a little slower due to the HDMI connection.
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It’s the little things
Since restoring a couple Mac OS 9 machines and playing with them, I’ve noticed some nice touches in various places.
One is that when you have the Platinum Sounds enabled and drag a window, the sound effect will pan in stereo with the window’s horizontal location.
I probably didn’t pick it up very well by recording with my iPhone, but just imagine it gets louder on the speaker the window is closest to. Pretty cool!
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Custom sounds in macOS
Just add them to ~/Library/Sounds!
See the GitHub repo for a parts list, wiring diagram, and Arduino code.
I plan to do a more thorough write-up on my plasma-ball project, but for now here’s the video, some pictures, and a link to the repo.
In Part 1 of my ‘Raspberry Pi + Garage door’ series, I showed a super simple way to control a garage door with a script that could potentially be ran from the Internet.
This part expands on that and tackles the issue: ‘How do I know the state of my garage door if I’m not at home?’
Because the code operates no differently than someone pressing a single button on the remote control, you would normally have to look with your own eyes to see if you were closing, stopping, or opening the garage door. This can be an issue when your eyes are nowhere close to it.
I wanted to come up with a solution that didn’t involve running new equipment such as a switch to detect the door’s orientation. I decided to utilize what I already had in the garage: A camera. Namely, this one: Foscam FI8910W
The idea is to use the camera to grab an image, pipe that image into OpenCV to detect known objects, and then declare the door open or closed based off of those results.
I whipped up a couple of shapes in Photoshop to stick on the inside of my door:
I then cropped out the shapes from the above picture to make templates for OpenCV to match.
The basic algorithm is this:
- Get the latest image from the camera
- Look for our templates with OpenCV
- If all objects (templates) were detected, the door is closed – otherwise it’s open
To help make step 3 more accurate, I added a horizontal threshold value which is defined in the configuration file. Basically, we’re using this to make sure we didn’t get a false positive – if the objects we detect are horizontally aligned, we can be pretty certain we have the right ones.
I was happy to find that the shapes worked well in low-light conditions. This may be due to the fact that my garage isn’t very deep so the IR range is sufficient, as well as the high contrast of black shapes on white paper.
Currently I have some experimental code in the project for detecting state changes. This will not only provide more information (e.g. the door is opening because we detect the pentagon has gone up x pixels), but is good for events (e.g. when the alarm system is on, let me know if the door has any state change).
I’ve tested running this on the Raspberry Pi and it works fine, though it can be a good bit slower than a full-blown machine. I have a Raspberry Pi 2 on order and it’ll be interesting to see the difference. Since this code doesn’t need anything specific to the Raspberry Pi, someone may prefer to run it on a faster box to get more info in the short time span it takes for a door to open or close.
I’ve created a video to demo the script in action!
Experimental code: https://github.com/twstokes/arduino-gyrocube
Varying the speed on an RC car motor with the Arduino using PWM.
It’s not a serious competition until you’ve put a microcontroller inside your gingerbread house. Since we were going for the Charlie Brown theme, I ripped apart and adapted a musical card that played ‘Linus and Lucy’. I also rigged up some LEDs to blink with the music. Video below the pictures.
