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import numpy as np
from scipy.ndimage import label
def generate_test_vecs(infile, strelfile, resultfile):
"test label with different structuring element neighborhoods"
def bitimage(l):
return np.array([[c for c in s] for s in l]) == '1'
data = [np.ones((7, 7)),
bitimage(["1110111",
"1100011",
"1010101",
"0001000",
"1010101",
"1100011",
"1110111"]),
bitimage(["1011101",
"0001000",
"1001001",
"1111111",
"1001001",
"0001000",
"1011101"])]
strels = [np.ones((3, 3)),
np.zeros((3, 3)),
bitimage(["010", "111", "010"]),
bitimage(["101", "010", "101"]),
bitimage(["100", "010", "001"]),
bitimage(["000", "111", "000"]),
bitimage(["110", "010", "011"]),
bitimage(["110", "111", "011"])]
strels = strels + [np.flipud(s) for s in strels]
strels = strels + [np.rot90(s) for s in strels]
strels = [np.fromstring(s, dtype=int).reshape((3, 3))
for s in set(t.astype(int).tostring() for t in strels)]
inputs = np.vstack(data)
results = np.vstack([label(d, s)[0] for d in data for s in strels])
strels = np.vstack(strels)
np.savetxt(infile, inputs, fmt="%d")
np.savetxt(strelfile, strels, fmt="%d")
np.savetxt(resultfile, results, fmt="%d")
generate_test_vecs("label_inputs.txt", "label_strels.txt", "label_results.txt")
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