def main():
parser = argparse.ArgumentParser()
parser.add_argument("-e", "--expected_rois_file", type=str, required=True)
parser.add_argument("-a", "--actual_rois_file", type=str, required=True)
parser.add_argument("-i", "--images_folder", type=str, required=False)
parser.add_argument("-o", "--result_file", type=str, required=False)
args = parser.parse_args()
expected_rois_file = args.expected_rois_file
actual_rois_file = args.actual_rois_file
images_folder = args.images_folder
expected_metadata = proto_api.read_metadata(expected_rois_file)
actual_metadata = proto_api.read_metadata(actual_rois_file)
random.seed(1337)
expected_dictionary = proto_api.create_metadata_dictionary(
expected_metadata, True)
actual_dictionary = proto_api.create_metadata_dictionary(
actual_metadata, False)
min_size = 25
statistics_dict = get_model_statistics(expected_dictionary,
actual_dictionary, images_folder,
min_size)
output_statistics(statistics_dict, args.result_file)
def main():
log_util.config(__file__)
logger = logging.getLogger(__name__)
# parse arguments
args = sys.argv[1:]
args = parse_args(args)
# get metadata
expected_metadata = meta.read_metadata(args.expected_rois_file)
actual_metadata = meta.read_metadata(args.actual_rois_file)
# calculate best thresholds
best_thresholds = get_thresholds(
meta.create_metadata_dictionary(expected_metadata, True),
meta.create_metadata_dictionary(actual_metadata, True))
io_utils.json_dump(best_thresholds, args.result_file)
def __evaluate_traffic_signs(self):
resolutions = [self.resolution]
score_threshold_per_class = dict([
(class_label, self.lowest_score_threshold)
for class_label in self.rois_labels.classes.keys()
])
actual_metadata = predict_folder(
self.model,
self.images_folder,
None,
resolutions,
self.rois_labels,
score_threshold_per_class,
draw_predictions=False,
max_number_of_images=self.max_number_of_images,
log_level=0)
actual_dict = meta.create_metadata_dictionary(actual_metadata, True)
for file_name in list(self.expected_dict.keys()):
if file_name not in actual_dict:
del self.expected_dict[file_name]
statistics_dict = get_model_statistics(self.expected_dict, actual_dict,
None, self.roi_min_side_size)
self.logger.info(statistics_dict['Total'])
def __init__(self,
generator,
ground_truth_proto_file,
train_proto_file,
resolution=2592,
max_number_of_images=100,
roi_min_side_size=25,
lowest_score_threshold=0.5):
self.generator = generator
self.ground_truth_proto_file = ground_truth_proto_file
self.rois_labels = RoisLabels(train_proto_file)
self.resolution = resolution
self.lowest_score_threshold = lowest_score_threshold
self.images_folder = os.path.dirname(
os.path.abspath(ground_truth_proto_file))
self.max_number_of_images = max_number_of_images
self.logger = logging.getLogger(__name__)
self.expected_metadata = meta.read_metadata(
self.ground_truth_proto_file)
self.expected_dict = meta.create_metadata_dictionary(
self.expected_metadata, True)
self.roi_min_side_size = roi_min_side_size
self.logger = logging.getLogger(__name__)
super().__init__()
def __get_rois_dict_from_file_name(self):
roi_metadata = meta.read_metadata(self.rois_file_name)
rois_dict = meta.create_metadata_dictionary(roi_metadata)
return rois_dict