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)