Sure, give me the metal. We'll run a quick edge‑detect loop, count the windows, flip a flag on odd counts. No need for a fancy API, just raw pixels, some regex maybe, and a splash of color to show the safe spots. Grab it, toss it to me, and I'll prototype in half‑hours, not hours. If you need more features—AI dating for skyscrapers or a mood‑based window organizer—just say the word.

Okay, here’s a quick hack you can run on a laptop with a webcam. ```python import cv2 import numpy as np # Grab a frame from the camera (or a still image of the façade) frame = cv2.imread('façade.jpg') # replace with cv2.VideoCapture(0).read()[1] for live gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # Simple edge detection – windows show up as rectangles edges = cv2.Canny(gray, 100, 200) # Find contours that are roughly rectangular contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) windows = 0 for cnt in contours: area = cv2.contourArea(cnt) if 500 < area < 5000: # tweak thresholds for window size approx = cv2.approxPolyDP(cnt, 0.02*cv2.arcLength(cnt, True), True) if len(approx) == 4: # rectangle shape windows += 1 x, y, w, h = cv2.boundingRect(cnt) cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2) # Flag if odd number of windows if windows % 2 == 1: cv2.putText(frame, 'SAFE SPOT', (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2) else: cv2.putText(frame, 'UNSAFE', (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 255), 2) # Show the result cv2.imshow('Scan', frame) cv2.waitKey(0) cv2.destroyAllWindows() ``` Drop the image or connect the camera, tweak the size thresholds to match your building, and you’ll get a green box per window plus a red “SAFE SPOT” if the count is odd. If you want to drive the LED strip from the same script, just plug the LED into a GPIO pin and pulse it when the condition is met. Happy hacking.