def setUp(self): self.asl = AslDb() self.training_set = self.asl.build_training(FEATURES) self.test_set = self.asl.build_test(FEATURES) self.models = train_all_words(self.training_set, SelectorConstant)
test_SLM = BasicSLM("SLM_data/corpus_sentences.txt", verbose=False) feature_set = features_custom selector = SelectorCV training_set = asl.build_training(feature_set) testing_set = asl.build_test(feature_set) train_words = training_set.words test_words = testing_set.wordlist #train_words = ['FISH', 'BOOK', 'VEGETABLE'] #test_words = ['FISH', 'BOOK', 'VEGETABLE'] sentences = testing_set.sentences_index sentences = [sentences[i] for i in sentences] models_dict = train_all_words(training_set, selector, train_words, verbose=False, features=feature_set) test_probs, test_guesses = recognize_words(models_dict, testing_set, test_words, verbose=False) acc_before = report_recognizer_results(test_words, test_probs, test_guesses, selector, test_SLM, feature_set) with open("recognizer_results/raw_results.txt", 'w') as file: json.dump((test_probs, test_guesses, test_words, sentences), file) #test_SLM_probs = get_SLM_probs(test_guesses, test_probs, test_SLM) #new_probs, new_guesses = normalise_and_combine(test_words, test_probs, test_SLM_probs, test_guesses, 1)