(1, 0): 2,
(0, 1): 3,
(1, 1): 4,
(1, -1): 5,
(-1, 1): 6,
(-1, -1): 7
}
dir_dict2 = [[-1, 0], [0, -1], [1, 0], [0, 1]]
dir_dict3 = [[-1, -1], [1, -1], [1, 1], [-1, 1]]
# Object: assign cost-to-go to elements of the centerline
# Method: breadth-first search
# Set goal location
skel = np.asarray(skel_3d(mazeData), dtype=int)
skel[42, 178:185] = 1
start = [42, 184]
#
plt.imshow(skel + mazeData)
plt.show()
# Initialize centerline cost-to-go map
costMap = np.copy(mazeData)
pgrad = np.copy(mazeData)
flowMapCol = 0 * mazeData
flowMapRow = 0 * mazeData
goal = [158, 18]
#[158, 18]
#[22, 56]
(1, -1): 5,
(-1, 1): 6,
(-1, -1): 7
}
dir_dict2 = [[-1, 0], [0, -1], [1, 0], [0, 1]]
dir_dict3 = [[-1, -1], [1, -1], [1, 1], [-1, 1]]
# Object: assign cost-to-go to elements of the centerline
# Method: breadth-first search
import skimage
raw_img = plt.imread(os.path.join(ROOT_PATH, mapfile + '.png'))
bw = raw_img[:, :, 0]
bw[bw < 1] = 0
skel = np.asarray(skel_3d(bw), dtype=np.int16) / 255
## For Map0522
# start = [77, 453]
## For Map 523
# start = [183, 450]
## For map 0524
start = [213, 570]
skel_Frontier = [start]
cost = 100
pgradSkel = np.copy(skel)
pgradSkel[skel_Frontier[-1][0], skel_Frontier[-1][1]] = cost