pyledstrip-detector

Automatically detects the physical 2D position of each LED on an LED strip using a camera and Gray code structured light.

How it works

1. Detection (detector.py): The LED strip is illuminated with Gray code patterns using pyledstrip. A camera captures each pattern, and per-pixel Gray code decoding maps every camera pixel to the LED index it sees. The median pixel position for each LED is exported as a JSON heightmap.

2. Post-processing (process_led_map.py): The raw heightmap is cleaned up — missing LEDs are filled in by linear interpolation, the path is smoothed with a Savitzky-Golay filter, and coordinates are optionally converted to metric units (metres, assuming 5 mm LED pitch by default).

Setup

Install dependencies (OpenCV, NumPy, matplotlib, pyledstrip, pyperclip):

pip install opencv-python numpy matplotlib pyledstrip pyperclip

Connect your LED strip and point a camera at it.

Usage

Step 1 — Detect LED positions

python detector.py --host <pyledstrip-host> [pyledstrip options]

This flashes Gray code patterns on the strip, captures frames from the default camera (/dev/video0), and writes the raw LED map to data/heightmap.<timestamp>.json.

Step 2 — Post-process the map

python process_led_map.py --infile data/heightmap.<timestamp>.json --outfile led_map.json

If --infile is omitted, the filename is read from the clipboard. If --outfile is omitted, it defaults to <infile>.processed.json.

Output format

Both scripts produce a JSON array of LED positions:

[
  { "id": 0, "x": 0.042, "y": 0.015 },
  { "id": 1, "x": 0.047, "y": 0.016 }
]

Files

File	Description
detector.py	Captures Gray code frames and decodes LED positions
ledworld.py	LedWorld / Led data model with interpolation, smoothing, and metric conversion
process_led_map.py	CLI wrapper for post-processing a raw heightmap
test_ledworld.py	Unit tests for LedWorld serialisation
data/	Output directory for generated heightmaps (JSON files excluded from git)

Running tests

python -m unittest test_ledworld.py