def __init__(self):
super().__init__()
self.__model = NoveltyDetector()
self.__threshold = Project.latest_threshold()
self.__should_test = True # TODO: assign True on dataset change
self.test_results = TestResults()
self.__training_thread = None
def on_finished_predicting(self, result):
image_path = result['image_paths'][0]
image_name = os.path.basename(image_path)
inspected_image_dir_path = Project.project_path(
) + self.__INSPECTED_IMAGES_DIR_NAME
score = result['scores'][0]
self.ui.loader_label.clear()
if score >= Project.latest_threshold():
self.ui.result.setCurrentWidget(self.ui.OK)
move(image_path, inspected_image_dir_path + '/OK_' + image_name)
self.ui.ok_score.setText('スコア: ' + str(score))
self.ok_counter += 1
else:
ng_image = QPixmap(str(image_path))
self.ui.ng_image.setPixmap(ng_image.scaled(
self.ui.ng_image.size()))
self.ui.result.setCurrentWidget(self.ui.NG)
self.ui.ng_score.setText('スコア: ' + str(score) + '\n閾値: ' +
str(Project.latest_threshold()))
move(image_path, inspected_image_dir_path + '/NG_' + image_name)
self.ng_counter += 1
self.ui.inspect_button.setDisabled(False)
self.ui.inspect_existing_image_button.setDisabled(False)
