def generate_training_result():
""" It should be very careful to use this method,
since it will replace all the result files.
"""
arg_exp = 20
dataset_matrix_hash = data_file_helper.get_dataset_matrix_hash(
data_file_helper.FONT_TRAINING_PATH, range(1, 10)
)
mb = MultipleSvm.train_and_save_variables(
Smo, dataset_matrix_hash, 200, 0.0001, 1000, arg_exp, data_file_helper.SUPPLEMENT_RESULT_PATH
)
generate_standard_supplement_number_ragions(file_path, the_digit, data_file_helper.SUPPLEMENT_TRAINING_PATH)
def main():
# generate_supplement_number_ragion()
# generate_supplement_result()
pass
main()
def test_generate_supplement_number_ragion(file_name, simple_svm, supplement_svm):
file_path = os.path.join(data_file_helper.SUPPLEMENT_TRAINING_PATH, file_name)
the_ragion = Image.load_from_txt(file_path)
the_number_matrix = numpy.matrix(the_ragion.reshape(1, FULL_SIZE))
# simple_svm.dag_classify(the_number_matrix).must_equal(
# extract_cal_digit(file_path),
# failure_msg="simple file path: {0}".format(file_path))
supplement_svm.dag_classify(the_number_matrix).must_equal(
extract_real_digit(file_path), failure_msg="supplement file path: {0}".format(file_path)
)
with test(generate_supplement_number_ragion):
simple_svm = MultipleSvm.load_variables(Smo, data_file_helper.FONT_RESULT_PATH)
supplement_svm = MultipleSvm.load_variables(Smo, data_file_helper.SUPPLEMENT_RESULT_PATH)
filenames = data_file_helper.filter_filenames_with_nums(data_file_helper.SUPPLEMENT_TRAINING_PATH, range(10))
for file_name in filenames:
test_generate_supplement_number_ragion(file_name, simple_svm, supplement_svm)
