def test_results_file_needs_to_be_a_csv_file(self, mock_isfile):
params = [
'Predictions.py', '/path/to/resnet50.h5', '/path/to/dir/images/',
'/path/to/dir/save_images', 'results.txt'
]
mock_isfile.return_value = True
self.assertTrue('Name of the file needs to end with .csv!' in
validation_util.get_errors(params))
def test_needs_to_be_h5_file(self, mock_isfile):
mock_isfile.return_value = True
params = [
'Predictions.py', '/path/to/file/resnet50.txt',
'/path/to/dir/images/', '/path/to/dir/save_images', 'results.csv'
]
self.assertTrue(
'File should be a .h5 file!' in validation_util.get_errors(params))
def test_result_file_cant_exists_before_running_predictions(
self, mock_isfile):
mock_isfile.return_value = True
params = [
'Predictions.py', '/path/to/resnet50.h5', '/path/to/dir/images/',
'/path/to/dir/save_images', 'results.csv'
]
self.assertTrue(params[4] + " file of this name already exists!" in
validation_util.get_errors(params))
def test_path_to_trained_model_needs_to_be_correct(self, mock_isfile):
mock_isfile.return_value = False
params = [
'Predictions.py', '/wrong/path/to/resnet50.h5',
'/path/to/dir/images/', '/path/to/dir/save_images', 'results.csv'
]
self.assertTrue(
params[1] +
' not a correct path!' in validation_util.get_errors(params))
def test_path_to_image_directory_needs_to_be_correct(self, mock_isdir):
mock_isdir.return_value = False
params = [
'Predictions.py', '/path/to/resnet50.h5',
'/path/to/wrong/dir/images/', '/path/to/dir/save_images',
'results.csv'
]
self.assertTrue(
params[2] +
' not a correct directory!' in validation_util.get_errors(params))
def main(arg):
# set the modified tf session as backend in keras
keras.backend.tensorflow_backend.set_session(get_session())
# make image save path if it doesn't exist
if arg[3] is not None and not os.path.exists(arg[3]):
os.makedirs(arg[3])
errors = get_errors(arg)
# check that there are no errors in the given arguments
if not errors:
[a, trained_model_path, read_image_directory_path, save_image_directory_path, predictions_csv] = arg
save_prediction_to_csv(trained_model_path, read_image_directory_path, save_image_directory_path, predictions_csv)
else:
print('Given arguments are wrong:')
for error in errors: print(error)
def test_cant_have_too_few_arguments(self):
params = ['param1', 'param2', 'param3']
self.assertTrue(
"Too few arguments!" in validation_util.get_errors(params))
def test_cant_have_too_many_arguments(self):
params = ['param1', 'param2', 'param3', 'param4', 'param5', 'param6']
self.assertTrue(
"Too many arguments!" in validation_util.get_errors(params))