def get_test_dataset():
x_return_test = np.zeros((117, size, size, size))
x_name_test = pd.read_csv("test.csv")['Id']
filenum = 0
for i in range(117):
x_file_temp = os.path.join(x_test_path, x_name_test[i] + '.npz')
x_voxel = np.array(np.load(x_file_temp)['voxel'])
x_seg = np.array(np.load(x_file_temp)['seg'])
x_temp = x_voxel * x_seg * 0.8 + x_voxel * 0.2
s = x_seg * x_voxel
sign = np.array(np.nonzero(s))
min1, low1, len1 = get_rec(sign, 0)
min2, low2, len2 = get_rec(sign, 1)
min3, low3, len3 = get_rec(sign, 2)
i_temp = 0
for i in range(low1, low1+len1):
j_temp = 0
for j in range(low2, low2+len2):
k_temp = 0
for k in range(low3, low3+len3):
x_return_test[filenum, i, j, k] = x_temp[min1 + i_temp, min2 + j_temp, min3 + k_temp]
k_temp += 1
j_temp += 1
i_temp += 1
filenum += 1
return x_return_test
def load_testdata():
x_return = np.zeros((117, size, size, size))
x_name = pd.read_csv("sampleSubmission.csv")[
'Id'] # 此处[' ']内填写的是sampleSubmission.csv内的第一列表头
filenum = 0
for i in range(117):
x_file_temp = os.path.join(x_test_path, x_name[i] + '.npz')
x_voxel = np.array(np.load(x_file_temp)['voxel'])
x_mask = np.array(np.load(x_file_temp)['seg'])
x_temp = x_voxel * x_mask * 0.8 + x_voxel * 0.2
list_xx_test = x_voxel * x_mask
list_xx_nz_test = np.array(np.nonzero(list_xx_test))
coor1min = list_xx_nz_test[0, :].min()
coor1max = list_xx_nz_test[0, :].max()
coor1len = coor1max - coor1min + 1
coor1bigger = coor1len - size
if coor1bigger > 0:
coor1min += coor1bigger // 2
coor1max -= coor1bigger - coor1bigger // 2
coor1len = size
coor1low = (size // 2) - (coor1len // 2)
coor1high = coor1low + coor1len
coor2min = list_xx_nz_test[1, :].min()
coor2max = list_xx_nz_test[1, :].max()
coor2len = coor2max - coor2min + 1
coor2bigger = coor2len - size
if coor2bigger > 0:
coor2min += coor2bigger // 2
coor2max -= coor2bigger - coor2bigger // 2
coor2len = size
coor2low = (size // 2) - (coor2len // 2)
coor2high = coor2low + coor2len
coor3min = list_xx_nz_test[2, :].min()
coor3max = list_xx_nz_test[2, :].max()
coor3len = coor3max - coor3min + 1
coor3bigger = coor3len - size
if coor3bigger > 0:
coor1min += coor3bigger // 2
coor3max -= coor3bigger - coor3bigger // 2
coor3len = size
coor3low = (size // 2) - (coor3len // 2)
coor3high = coor3low + coor3len
# print(file, coor1low, coor1high, coor2low, coor2high, coor3low, coor3high)
coorlist1 = 0
for coor1 in range(coor1low, coor1high):
coorlist2 = 0
for coor2 in range(coor2low, coor2high):
coorlist3 = 0
for coor3 in range(coor3low, coor3high):
x_return[filenum, coor1, coor2,
coor3] = x_temp[coor1min + coorlist1,
coor2min + coorlist2,
coor3min + coorlist3]
coorlist3 += 1
coorlist2 += 1
coorlist1 += 1
filenum += 1
return x_return
def load_traindata():
x_return = np.zeros((495, size, size, size))
x_name = pd.read_csv("train_val.csv")[
'Id'] # 此处[' ']内填写的是train_val.csv内的第一列表头
count_file = 0
for i in range(len(traindata_list)):
x_file_temp = os.path.join(traindata_path, x_name[i] + '.npz')
x_voxel = np.array(np.load(x_file_temp)['voxel'])
x_mask = np.array(np.load(x_file_temp)['seg'])
x_temp = x_voxel * x_mask * 0.8 + x_voxel * 0.2
list_xx = x_mask * x_voxel
list_xx_nz = np.array(np.nonzero(list_xx))
coor1min = list_xx_nz[0, :].min()
coor1max = list_xx_nz[0, :].max()
coor1len = coor1max - coor1min + 1
coor1bigger = coor1len - size
if coor1bigger > 0:
coor1min += coor1bigger // 2
coor1max -= coor1bigger - coor1bigger // 2
coor1len = size
coor1low = (size // 2) - (coor1len // 2)
coor1high = coor1low + coor1len
coor2min = list_xx_nz[1, :].min()
coor2max = list_xx_nz[1, :].max()
coor2len = coor2max - coor2min + 1
coor2bigger = coor2len - size
if coor2bigger > 0:
coor2min += coor2bigger // 2
coor2max -= coor2bigger - coor2bigger // 2
coor2len = size
coor2low = (size // 2) - (coor2len // 2)
coor2high = coor2low + coor2len
coor3min = list_xx_nz[2, :].min()
coor3max = list_xx_nz[2, :].max()
coor3len = coor3max - coor3min + 1
coor3bigger = coor3len - size
if coor3bigger > 0:
coor1min += coor3bigger // 2
coor3max -= coor3bigger - coor3bigger // 2
coor3len = size
coor3low = (size // 2) - (coor3len // 2)
coor3high = coor3low + coor3len
coorlist1 = 0
for coor1 in range(coor1low, coor1high):
coorlist2 = 0
for coor2 in range(coor2low, coor2high):
coorlist3 = 0
for coor3 in range(coor3low, coor3high):
x_return[count_file, coor1, coor2,
coor3] = x_temp[coor1min + coorlist1,
coor2min + coorlist2,
coor3min + coorlist3]
coorlist3 += 1
coorlist2 += 1
coorlist1 += 1
count_file += 1
return x_return