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)