constellations.py

import cv2
import numpy as np

# Read the image
img = cv2.imread('sky.jpg')

# Convert the image to grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Use a threshold to detect stars in the image
thresh = cv2.threshold(gray, 240, 255, cv2.THRESH_BINARY)[1]

# Find the contours of the stars
contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
contours = contours[0] if len(contours) == 2 else contours[1]

# Loop through the contours and draw a circle around each star
for c in contours:
    x,y,w,h = cv2.boundingRect(c)
    cv2.circle(img, (x + w // 2, y + h // 2), w // 2, (255, 255, 0), 2)

# Use a brute force matcher to find the nearest stars
bf = cv2.BFMatcher()

# Extract the coordinates of the stars from the contours
star_coords = []
for c in contours:
    x,y,w,h = cv2.boundingRect(c)
    star_coords.append((x + w // 2, y + h // 2))

# Convert the star coordinates to a numerical array
star_coords = np.array(star_coords, dtype=np.float32)

# Use the numerical array of star coordinates as the query descriptors in the knnMatch() function
matches = bf.knnMatch(star_coords, star_coords, k=2)

# Loop through the matches and connect the nearest stars with lines
for m in matches:
    if len(m) == 2:
        a, b = m[0], m[1]
        # Use the queryIdx and trainIdx attributes of the cv2.DMatch objects to get the indexes of the matched stars
        star1_idx = a.queryIdx
        star2_idx = b.trainIdx
        # Use the indexes to get the coordinates of the matched stars

        # Use the indexes to get the coordinates of the matched stars
        star1_coord = tuple(map(int, star_coords[star1_idx]))
        star2_coord = tuple(map(int, star_coords[star2_idx]))
        # Draw a line between the matched stars
        # Use the star coordinates as a tuple of coordinates as the first and second arguments to the line() function
        cv2.line(img, star1_coord, star2_coord, (0, 255, 0), 2)

# Save the image with the detected constellations
cv2.imwrite('sky_with_constellations.jpg', img)