03-evaluate.py 文件源码

def evaluate(input_path, n_jobs):

    aud, ann = zip(*crema.utils.get_ann_audio(input_path))

    test_idx = set(pd.read_json('index_test.json')['id'])

    # drop anything not in the test set
    ann = [ann_i for ann_i in ann if crema.utils.base(ann_i) in test_idx]
    aud = [aud_i for aud_i in aud if crema.utils.base(aud_i) in test_idx]

    stream = tqdm(zip(ann, aud), desc='Evaluating test set', total=len(ann))

    results = Parallel(n_jobs=n_jobs)(delayed(track_eval)(ann_i, aud_i)
                                      for ann_i, aud_i in stream)
    df = pd.DataFrame.from_dict(dict(results), orient='index')

    print('Results')
    print('-------')
    print(df.describe())

    df.to_json(os.path.join(OUTPUT_PATH, 'test_scores.json'))