def build_all(self):
constellations = []
for filename in glob.glob('Constellations/*.jpg'):
# Read in Image
img = cv2.imread(filename, cv2.IMREAD_COLOR)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Threshold to binary
thresh = 100
img = cv2.threshold(img, thresh, 255, cv2.THRESH_BINARY)[1]
# Isolated unwanted text elements
text = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)[1]
dilated = cv2.dilate(text, np.ones((11, 11)))
# Remove text elements leaving only stars in red and lines in blue
img[dilated > 250] = 0
# Find stars
shapedetector = ShapeDetector()
stars = shapedetector.get_stars(img)
x, y, mags = shapedetector.detect_stars(stars)
lines = shapedetector.detect_lines(img)
con = Constellation(x, y, mags, lines)
con.align_constellation()
constellations.append(con)
return sorted(constellations, key=attrgetter('number_of_stars'))
def build_ursa_major(self):
# Read in Image
img = cv2.imread('Constellations/UrsaMajor.jpg', cv2.IMREAD_COLOR)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#Threshold to binary
thresh = 100
img = cv2.threshold(img, thresh, 255, cv2.THRESH_BINARY)[1]
#Isolated unwanted text elements
text = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)[1]
dilated = cv2.dilate(text, np.ones((11, 11)))
#Remove text elements leaving only stars in red and lines in blue
img[dilated > 250] = 0
#Find stars
shapedetector = ShapeDetector()
stars = shapedetector.get_stars(img)
x, y, mags = shapedetector.detect_stars(stars)
lines = shapedetector.detect_lines(img)
con = Constellation(x, y, mags, lines)
con.align_constellation()
return Constellation(x, y, mags, lines)
def main():
sd = ShapeDetector()
# Constallation Object
cd = ConstellationBuilder()
file = sys.argv[1]
constellations = cd.build_all()
for constellation in constellations:
fig, ax = plt.subplots()
plt.scatter(constellation.stars_x, constellation.stars_y)
# plt.axis([0, 8, -5, 0])
for i, txt in enumerate(constellation.stars_mags):
ax.annotate(txt,
(constellation.stars_x[i], constellation.stars_y[i]))
for line in constellation.lines:
plt.plot((line.item(0), line.item(2)),
(-line.item(1), -line.item(3)),
'ro-',
linewidth=2,
markersize=0)
plt.show()
# Read in Image
img = cv2.imread(file, cv2.IMREAD_COLOR)
final_img = cv2.imread(file, cv2.IMREAD_COLOR)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# cv2.imshow('Starting Image', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
#Threshold to binary
thresh = 100
img = cv2.threshold(img, thresh, 255, cv2.THRESH_BINARY)[1]
stars = sd.get_all(img)
x, y, mags = sd.detect_stars(stars)
fig, ax = plt.subplots()
plt.scatter(x, y)
for i, txt in enumerate(mags):
ax.annotate(2 * txt, (x[i], y[i]))
#Find two brightest stars in image and mark them
cd = ConstellationDetector(constellations)
sorted_mags = order_mags(mags)
l1, l2 = sorted_mags[0], sorted_mags[1]
x_test = x.copy()
y_test = y.copy()
mags_test = mags.copy()
for j in range(0, len(mags)):
for constellation in constellations:
for i in range(j, len(mags) - 1):
tx, ty, lines, t_scale, matched = cd.search_for_constellation(
constellation, x_test, y_test, mags_test, sorted_mags[j],
sorted_mags[i])
if matched:
break
if matched:
break
if matched:
break
plt.plot(x_test[l1], y_test[l1], 'r+')
plt.plot(x_test[l2], y_test[l2], 'y+')
if matched:
plt.plot(tx, ty, 'y*')
for line in lines:
plt.plot((line.item(0), line.item(2)),
(-line.item(1), -line.item(3)),
'ro-',
linewidth=2,
markersize=0)
# Draw constellation on image
draw_stars(tx, ty, t_scale, final_img)
draw_lines(lines, final_img)
plt.show()
height, width, channels = img.shape
final_img = cv2.resize(final_img, (width * 2, height * 2))
cv2.imshow('Finished Product', final_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
