examples/compute_features.py
def process(in_path, out_file, n_jobs, framesync):
    """Computes the features for the selected dataset or file."""
    if os.path.isfile(in_path):
        # Single file mode
        # Get (if they exitst) or compute features
        file_struct = msaf.io.FileStruct(in_path)
        file_struct.features_file = out_file
        compute_all_features(file_struct, framesync)
    else:
        # Collection mode
        file_structs = msaf.io.get_dataset_files(in_path)

        # Call in parallel
        return Parallel(n_jobs=n_jobs)(delayed(compute_all_features)(
            file_struct, framesync) for file_struct in file_structs)
def process(in_path, out_file, n_jobs, framesync):
    if os.path.isfile(in_path):
        # Single file mode
        # Get (if they exitst) or compute features
        file_struct = msaf.io.FileStruct(in_path)
        file_struct.features_file = out_file
        compute_all_features(file_struct, framesync)
    else:
        # Collection mode
        file_structs = msaf.io.get_dataset_files(in_path)

        # Call in parallel
        return Parallel(n_jobs=n_jobs)(delayed(compute_all_features)(
            file_struct, framesync) for file_struct in file_structs)
def process ( in_path , out_file , n_jobs , framesync ) : if os . path . isfile ( in_path ) : # Single file mode # Get (if they exitst) or compute features file_struct = msaf . io . FileStruct ( in_path ) file_struct . features_file = out_file compute_all_features ( file_struct , framesync ) else : # Collection mode file_structs = msaf . io . get_dataset_files ( in_path ) # Call in parallel return Parallel ( n_jobs = n_jobs ) ( delayed ( compute_all_features ) ( file_struct , framesync ) for file_struct in file_structs )
Computes the features for the selected dataset or file.
Computes the features for the selected dataset or file .