def _load_validation_data(validation_leveldb, width, height):
    """
    Loads all of our validation data from our leveldb database, producing unrolled numpy input
    vectors ready to test along with their correct, expected target values.
    """

    print "\tLoading validation data..."
    input_vectors = []
    expected_targets = []

    db = plyvel.DB(validation_leveldb)
    for key, value in db:
        datum = Datum()
        datum.ParseFromString(value)

        data = np.fromstring(datum.data, dtype=np.uint8)
        data = np.reshape(data, (3, height, width))
        # Move the color channel to the end to match what Caffe wants.
        data = np.swapaxes(data, 0, 2) # Swap channel with width.
        data = np.swapaxes(data, 0, 1) # Swap width with height, to yield final h x w x channel.

        input_vectors.append(data)
        expected_targets.append(datum.label)

    db.close()

    print "\t\tValidation data has %d images" % len(input_vectors)

    return {
        "input_vectors": np.asarray(input_vectors),
        "expected_targets": np.asarray(expected_targets)
    }
dataset/ETHPy150Open BradNeuberg/cloudless/src/cloudless/train/predict.py/_load_validation_data/original