Skip to content

Scanning the Tree

Jump to bottom
Diamond edited this page Dec 1, 2023 · 3 revisions

The tree scanning code is the core foundation of this project. The whole idea is to give people a 2D image to draw onto the tree rather than having to guess where the LEDs are. This page outlines how to scan the Christmas tree for the led-points.csv file which lists the physical coordinates of the LED bulbs on a 2D plane. The code for this will be in the christmas repo.

Requirements

  • Any video camera. I used my Pixel 6a recording at 60fps.
  • The setup with the rpi-worm program loaded in.
    • Prefer 200ms for the delay.
    • Make sure the number of LEDs match up. Check --help for more information.

Steps

Building the tools

Run make. This will compile all tools and, if you're already in the Nix shell, put those tools into $PATH, which is important for the instructions underneath.

Recording the video

Record the video of the ACM tree while the worm program is running.

It is recommended that you record with a stabilizer or tripod. If you don't have one, you can use a stack of books or something. The less shaky the video, the better the results will be.

It is also recommended that you record at 60fps. This will give you more frames to work with and more lee-way when you're trying to find the timestamp of the first LED turning on.

If you use Android, it is recommended that you use the Open Camera app. It has a lot of useful features, including the ability to tune down the ISO and exposure time, which will reduce the amount of noise in the video.

Finding the timestamp

Find the timestamp of the frame where the first LED turns on.

You might want to use , and . to go frame by frame. Some video players like mpv support this.

It's OK if you're off by a few frames. You can always run the process again.

Extracting the frames

Run extract-frames.

Examples:

extract-frames --start-time 1.9 path/to/video.mp4
extract-frames --start-time 1:25 path/to/video.mp4 path/to/frames/output

Keep --num-leds and --worm-speed the same as the worm program.

Resizing the frames

Run ffmpeg-bulk to resize the images to a reasonable size, e.g. 512px.

Examples:

ffmpeg-bulk.sh -y -vf scale=512:512:force_original_aspect_ratio=decrease \
    path/to/frames/output \
    path/to/frames/output-small/?.jpg

This step is optional, but it will make using the data points much easier.

Threshold-masking the frames

Run ffmpeg-bulk again with ffutil to apply a threshold mask to the images.

Examples:

ffmpeg-bulk.sh -y $(ffutil threshold 288x512 0.8) \
    path/to/frames/output-small \
    path/to/frames/output-threshold/?.jpg

If any of the LEDs are not visible in the thresholded images, the next step will fail. You can try adjusting the threshold value (0.8 in the example above).

Finding the LED positions

Run big-spot to find the positions of the LEDs in the thresholded images. The output will be in a led-points.csv file containing (x, y, area).

Examples:

big-spot -o path/to/frames/output-threshold/data path/to/frames/output-threshold

If any of the coordinates are off, you can try running big-spot again with the --output-png flag, which will output all chosen spots for each frame in a PNG file. You can then open the PNG file and see if the spots are correct.

The PNG files are not required for the next step. Only the led-points.csv file is required.

Clone this wiki locally