daps_detection.py 文件源码

def wrapper_nms(proposal_df, overlap=0.65):
    """Apply non-max-suppresion to a video batch.
    """
    vds_unique = pd.unique(proposal_df['video-name'])
    new_proposal_df = []
    for i, v in enumerate(vds_unique):
        idx = proposal_df['video-name'] == v
        p = proposal_df.loc[idx, ['video-name', 'f-init', 'f-end',
                                  'score', 'video-frames']]
        n_frames = np.int(p['video-frames'].mean())
        loc = np.stack((p['f-init'], p['f-end']), axis=-1)
        loc, score = nms_detections(loc, np.array(p['score']), overlap)
        n_proposals = score.shape[0]
        n_frames = np.repeat(p['video-frames'].mean(), n_proposals).astype(int)
        this_df = pd.DataFrame({'video-name': np.repeat(v, n_proposals),
                                'f-init': loc[:, 0], 'f-end': loc[:, 1],
                                'score': score,
                                'video-frames': n_frames})
        new_proposal_df.append(this_df)
    return pd.concat(new_proposal_df, axis=0)