def main(input_dir=None):
# Input the faces of the Cube
if input_dir is None:
captured_faces, captured_imgs = capture_faces()
else:
input_imgs = load_imgs_from_dir(input_dir)
captured_faces, captured_imgs = capture_faces_from_images(input_imgs)
# Get the color classifier
clf_yuv = get_classifier()
# Predict the face colors from the input images
faces = np.array(captured_faces)
pred_colors_yuv, pred_proba_yuv = label_images(clf_yuv, [faces])
colors_cube = np.array(pred_colors_yuv).reshape((6, 3, 3))
# Inspect / adjust results if necessary. This step can modify pred_colors_yuv2.
check_images(captured_imgs, captured_faces, colors_cube, clf_yuv)
plt.show()
# Define the cube using the updated colors
c = Cube(colors_cube)
# Solve and retain moves
initial_state = c.export_state()
s = Solver(c)
s.solve()
solve_moves = c.recorded_moves
# Display the solution
sg = SolutionGallery(initial_state, solve_moves)
plt.show()
if self.i > 0:
self.i = self.i - 1
# Undo the last move to put cube in previous state
self.c.perform_move(opposite_move(self.solve_moves[self.i]))
# Display the next move
move = self.solve_moves[self.i]
self.c.cube_plot(ax=self.ax1, title_str=move.replace('1', ''))
add_move_annotation(self.ax1, move)
else:
self.c.cube_plot(ax=self.ax1, title_str='Initial State')
plt.draw()
return event
if __name__ == '__main__':
# Create a random cube
c = Cube()
c.randomize_state()
initial_state = c.export_state()
# Solve and retain moves
s = Solver(c)
s.solve()
# Display the solution
sg = SolutionGallery(s.initial_state, s.solve_moves)
sg.show()
