diff --git a/dlclive/graph.py b/dlclive/graph.py
deleted file mode 100644
index 72b3b76..0000000
--- a/dlclive/graph.py
+++ /dev/null
@@ -1,139 +0,0 @@
-"""
-DeepLabCut Toolbox (deeplabcut.org)
-© A. & M. Mathis Labs
-
-Licensed under GNU Lesser General Public License v3.0
-"""
-
-
-import tensorflow as tf
-
-vers = (tf.__version__).split(".")
-if int(vers[0]) == 2 or int(vers[0]) == 1 and int(vers[1]) > 12:
-    tf = tf.compat.v1
-else:
-    tf = tf
-
-
-def read_graph(file):
-    """
-    Loads the graph from a protobuf file
-
-    Parameters
-    -----------
-    file : string
-        path to the protobuf file
-
-    Returns
-    --------
-    graph_def :class:`tensorflow.tf.compat.v1.GraphDef`
-        The graph definition of the DeepLabCut model found at the object's path
-    """
-
-    with tf.io.gfile.GFile(file, "rb") as f:
-        graph_def = tf.GraphDef()
-        graph_def.ParseFromString(f.read())
-        return graph_def
-
-
-def finalize_graph(graph_def):
-    """
-    Finalize the graph and get inputs to model
-
-    Parameters
-    -----------
-    graph_def :class:`tensorflow.compat.v1.GraphDef`
-        The graph of the DeepLabCut model, read using the :func:`read_graph` method
-
-    Returns
-    --------
-    graph :class:`tensorflow.compat.v1.GraphDef`
-        The finalized graph of the DeepLabCut model
-    inputs :class:`tensorflow.Tensor`
-        Input tensor(s) for the model
-    """
-
-    graph = tf.Graph()
-    with graph.as_default():
-        tf.import_graph_def(graph_def, name="DLC")
-    graph.finalize()
-
-    return graph
-
-
-def get_output_nodes(graph):
-    """
-    Get the output node names from a graph
-
-    Parameters
-    -----------
-    graph :class:`tensorflow.Graph`
-        The graph of the DeepLabCut model
-
-    Returns
-    --------
-    output : list
-        the output node names as a list of strings
-    """
-
-    op_names = [str(op.name) for op in graph.get_operations()]
-    if "concat_1" in op_names[-1]:
-        output = [op_names[-1]]
-    else:
-        output = [op_names[-1], op_names[-2]]
-
-    return output
-
-
-def get_output_tensors(graph):
-    """
-    Get the names of the output tensors from a graph
-
-    Parameters
-    -----------
-    graph :class:`tensorflow.Graph`
-        The graph of the DeepLabCut model
-
-    Returns
-    --------
-    output : list
-        the output tensor names as a list of strings
-    """
-
-    output_nodes = get_output_nodes(graph)
-    output_tensor = [out + ":0" for out in output_nodes]
-    return output_tensor
-
-
-def get_input_tensor(graph):
-    input_tensor = str(graph.get_operations()[0].name) + ":0"
-    return input_tensor
-
-
-def extract_graph(
-    graph, tf_config=None
-) -> tuple[tf.Session, tf.Tensor, list[tf.Tensor]]:
-    """
-    Initializes a tensorflow session with the specified graph and extracts the model's inputs and outputs
-
-    Parameters
-    -----------
-    graph :class:`tensorflow.Graph`
-        a tensorflow graph containing the desired model
-    tf_config :class:`tensorflow.ConfigProto`
-
-    Returns
-    --------
-    sess :class:`tensorflow.Session`
-        a tensorflow session with the specified graph definition
-    outputs :class:`tensorflow.Tensor`
-        the output tensor(s) for the model
-    """
-
-    input_tensor = get_input_tensor(graph)
-    output_tensor = get_output_tensors(graph)
-    sess = tf.Session(graph=graph, config=tf_config)
-    inputs = graph.get_tensor_by_name(input_tensor)
-    outputs = [graph.get_tensor_by_name(out) for out in output_tensor]
-
-    return sess, inputs, outputs
diff --git a/dlclive/pose.py b/dlclive/pose.py
deleted file mode 100644
index 3e69bb9..0000000
--- a/dlclive/pose.py
+++ /dev/null
@@ -1,120 +0,0 @@
-"""
-DeepLabCut Toolbox (deeplabcut.org)
-© A. & M. Mathis Labs
-
-Licensed under GNU Lesser General Public License v3.0
-"""
-
-
-import numpy as np
-
-
-def extract_cnn_output(outputs, cfg):
-    """
-    Extract location refinement and score map from DeepLabCut network
-
-    Parameters
-    -----------
-    outputs : list
-        List of outputs from DeepLabCut network.
-        Requires 2 entries:
-            index 0 is output from Sigmoid
-            index 1 is output from pose/locref_pred/block4/BiasAdd
-
-    cfg : dict
-        Dictionary read from the pose_cfg.yaml file for the network.
-
-    Returns
-    --------
-    scmap : ?
-        score map
-
-    locref : ?
-        location refinement
-    """
-
-    scmap = outputs[0]
-    scmap = np.squeeze(scmap)
-    locref = None
-    if cfg["location_refinement"]:
-        locref = np.squeeze(outputs[1])
-        shape = locref.shape
-        locref = np.reshape(locref, (shape[0], shape[1], -1, 2))
-        locref *= cfg["locref_stdev"]
-    if len(scmap.shape) == 2:  # for single body part!
-        scmap = np.expand_dims(scmap, axis=2)
-    return scmap, locref
-
-
-def argmax_pose_predict(scmap, offmat, stride):
-    """
-    Combines score map and offsets to the final pose
-
-    Parameters
-    -----------
-    scmap : ?
-        score map
-
-    offmat : ?
-        offsets
-
-    stride : ?
-        ?
-
-    Returns
-    --------
-    pose :class:`numpy.ndarray`
-        pose as a numpy array
-    """
-
-    num_joints = scmap.shape[2]
-    pose = []
-    for joint_idx in range(num_joints):
-        maxloc = np.unravel_index(
-            np.argmax(scmap[:, :, joint_idx]), scmap[:, :, joint_idx].shape
-        )
-        offset = np.array(offmat[maxloc][joint_idx])[::-1]
-        pos_f8 = np.array(maxloc).astype("float") * stride + 0.5 * stride + offset
-        pose.append(np.hstack((pos_f8[::-1], [scmap[maxloc][joint_idx]])))
-    return np.array(pose)
-
-
-def get_top_values(scmap, n_top=5):
-    batchsize, ny, nx, num_joints = scmap.shape
-    scmap_flat = scmap.reshape(batchsize, nx * ny, num_joints)
-    if n_top == 1:
-        scmap_top = np.argmax(scmap_flat, axis=1)[None]
-    else:
-        scmap_top = np.argpartition(scmap_flat, -n_top, axis=1)[:, -n_top:]
-        for ix in range(batchsize):
-            vals = scmap_flat[ix, scmap_top[ix], np.arange(num_joints)]
-            arg = np.argsort(-vals, axis=0)
-            scmap_top[ix] = scmap_top[ix, arg, np.arange(num_joints)]
-        scmap_top = scmap_top.swapaxes(0, 1)
-
-    Y, X = np.unravel_index(scmap_top, (ny, nx))
-    return Y, X
-
-
-def multi_pose_predict(scmap, locref, stride, num_outputs):
-    Y, X = get_top_values(scmap[None], num_outputs)
-    Y, X = Y[:, 0], X[:, 0]
-    num_joints = scmap.shape[2]
-    DZ = np.zeros((num_outputs, num_joints, 3))
-    for m in range(num_outputs):
-        for k in range(num_joints):
-            x = X[m, k]
-            y = Y[m, k]
-            DZ[m, k, :2] = locref[y, x, k, :]
-            DZ[m, k, 2] = scmap[y, x, k]
-
-    X = X.astype("float32") * stride + 0.5 * stride + DZ[:, :, 0]
-    Y = Y.astype("float32") * stride + 0.5 * stride + DZ[:, :, 1]
-    P = DZ[:, :, 2]
-
-    pose = np.empty((num_joints, num_outputs * 3), dtype="float32")
-    pose[:, 0::3] = X.T
-    pose[:, 1::3] = Y.T
-    pose[:, 2::3] = P.T
-
-    return pose
diff --git a/dlclive/pose_estimation_tensorflow/graph.py b/dlclive/pose_estimation_tensorflow/graph.py
index 9c9769b..20c4203 100644
--- a/dlclive/pose_estimation_tensorflow/graph.py
+++ b/dlclive/pose_estimation_tensorflow/graph.py
@@ -5,7 +5,6 @@
 Licensed under GNU Lesser General Public License v3.0
 """
 
-
 import tensorflow as tf
 
 vers = (tf.__version__).split(".")
diff --git a/dlclive/pose_estimation_tensorflow/pose.py b/dlclive/pose_estimation_tensorflow/pose.py
index 3e69bb9..b7f9cd7 100644
--- a/dlclive/pose_estimation_tensorflow/pose.py
+++ b/dlclive/pose_estimation_tensorflow/pose.py
@@ -5,7 +5,6 @@
 Licensed under GNU Lesser General Public License v3.0
 """
 
-
 import numpy as np