class LegoPatternDetector(object):
def __init__(self):
self.homography = self.compute_homography()
self.pattern = SharedPattern()
def compute_homography(self):
src_points = json.load(open('rect.json'))
dst_points = [[0, 0], [GRID_SIZE, 0], [GRID_SIZE, GRID_SIZE],
[0, GRID_SIZE]]
return cv2.findHomography(numpy.asarray(src_points, float),
numpy.asarray(dst_points, float))[0]
def process_image(self, img):
img = cv2.warpPerspective(img, self.homography, (GRID_SIZE, GRID_SIZE))
self.update_notes(img)
self.mute_tracks(img)
return img
def update_notes(self, img):
for track in range(self.pattern.num_tracks):
for step in range(self.pattern.num_steps):
color = average_cell_color_hsv(img, track, step)
if is_clear_color_hsv(color):
self.pattern.clear_step(track, step)
elif is_note_color_hsv(color):
self.pattern.set_step(track, step)
def mute_tracks(self, img):
for track in range(self.pattern.num_tracks):
color = average_cell_color_hsv(img, track + 8, 0)
if is_clear_color_hsv(color):
self.pattern.unmute(track)
else:
self.pattern.mute(track)
class LegoPatternDetector(object):
def __init__(self):
self.homography = self.compute_homography()
self.pattern = SharedPattern()
def compute_homography(self):
src_points = json.load(open('rect.json'))
dst_points = [
[0, 0],
[GRID_SIZE, 0],
[GRID_SIZE, GRID_SIZE],
[0, GRID_SIZE]]
return cv2.findHomography(
numpy.asarray(src_points, float),
numpy.asarray(dst_points, float))[0]
def process_image(self, img):
img = cv2.warpPerspective(img, self.homography, (GRID_SIZE, GRID_SIZE))
self.update_notes(img)
self.mute_tracks(img)
return img
def update_notes(self, img):
for track in range(self.pattern.num_tracks):
for step in range(self.pattern.num_steps):
color = average_cell_color_hsv(img, track, step)
if is_clear_color_hsv(color):
self.pattern.clear_step(track, step)
elif is_note_color_hsv(color):
self.pattern.set_step(track, step)
def mute_tracks(self, img):
for track in range(self.pattern.num_tracks):
color = average_cell_color_hsv(img, track + 8, 0)
if is_clear_color_hsv(color):
self.pattern.unmute(track)
else:
self.pattern.mute(track)
def __init__(self):
self.homography = self.compute_homography()
self.pattern = SharedPattern()
def __init__(self):
self.homography = self.compute_homography()
self.pattern = SharedPattern()