diff --git a/pyproject.toml b/pyproject.toml
index 9167aac..ff3dce9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -18,6 +18,7 @@ dynamic = ["version"]
 
 dependencies = [
     'boto3',
+    'fastremap',
     'lightning',
     'more_itertools',
     'networkx',
diff --git a/src/deep_neurographs/graph_utils.py b/src/deep_neurographs/graph_utils.py
index 361e564..c0877ec 100644
--- a/src/deep_neurographs/graph_utils.py
+++ b/src/deep_neurographs/graph_utils.py
@@ -60,12 +60,13 @@ def get_irreducibles(swc_dict, swc_id=None, prune=True, depth=16, smooth=True):
 
     """
     # Build dense graph
+    swc_dict["idx"] = dict(zip(swc_dict["id"], range(len(swc_dict["id"]))))
     dense_graph = swc_utils.to_graph(swc_dict)
     if prune:
         dense_graph = prune_short_branches(dense_graph, depth)
 
     # Extract nodes
-    leafs, junctions = get_irreducible_nodes(dense_graph, swc_dict)
+    leafs, junctions = get_irreducible_nodes(dense_graph)
     if len(leafs) == 0:
         return False, None
 
@@ -100,7 +101,7 @@ def get_irreducibles(swc_dict, swc_id=None, prune=True, depth=16, smooth=True):
     return swc_id, irreducibles
 
 
-def get_irreducible_nodes(graph, swc_dict):
+def get_irreducible_nodes(graph):
     """
     Gets irreducible nodes (i.e. leafs and junctions) of a graph.
 
@@ -315,7 +316,8 @@ def init_edge_attrs(swc_dict, i):
         Edge attribute dictionary.
 
     """
-    return {"radius": [swc_dict["radius"][i]], "xyz": [swc_dict["xyz"][i]]}
+    j = swc_dict["idx"][i] 
+    return {"radius": [swc_dict["radius"][j]], "xyz": [swc_dict["xyz"][j]]}
 
 
 def upd_edge_attrs(swc_dict, attrs, i):
@@ -337,8 +339,9 @@ def upd_edge_attrs(swc_dict, attrs, i):
         Edge attribute dictionary.
 
     """
-    attrs["radius"].append(swc_dict["radius"][i])
-    attrs["xyz"].append(swc_dict["xyz"][i])
+    j = swc_dict["idx"][i] 
+    attrs["radius"].append(swc_dict["radius"][j])
+    attrs["xyz"].append(swc_dict["xyz"][j])
     return attrs
 
 
@@ -403,7 +406,8 @@ def set_node_attrs(swc_dict, nodes):
     """
     attrs = dict()
     for i in nodes:
-        attrs[i] = {"radius": swc_dict["radius"][i], "xyz": swc_dict["xyz"][i]}
+        j = swc_dict["idx"][i] 
+        attrs[i] = {"radius": swc_dict["radius"][j], "xyz": swc_dict["xyz"][j]}
     return attrs
 
 
@@ -434,7 +438,8 @@ def upd_node_attrs(swc_dict, leafs, junctions, i):
         Updated dictionary if "i" was contained in "junctions.keys()".
 
     """
-    upd_attrs = {"radius": swc_dict["radius"][i], "xyz": swc_dict["xyz"][i]}
+    j = swc_dict["idx"][i] 
+    upd_attrs = {"radius": swc_dict["radius"][j], "xyz": swc_dict["xyz"][j]}
     if i in leafs:
         leafs[i] = upd_attrs
     else:
diff --git a/src/deep_neurographs/intake.py b/src/deep_neurographs/intake.py
index 23250c3..792b479 100644
--- a/src/deep_neurographs/intake.py
+++ b/src/deep_neurographs/intake.py
@@ -207,6 +207,8 @@ def download_gcs_zips(bucket_name, cloud_path, min_size):
             cnt, t1 = report_progress(
                 i, len(zip_paths), chunk_size, cnt, t0, t1
             )
+        if len(swc_dicts) > 2000:
+            stop
     return swc_dicts
 
 
diff --git a/src/deep_neurographs/swc_utils.py b/src/deep_neurographs/swc_utils.py
index d8e6a0c..3cd6c51 100644
--- a/src/deep_neurographs/swc_utils.py
+++ b/src/deep_neurographs/swc_utils.py
@@ -60,9 +60,8 @@ def parse_local_swc(path, bbox=None, min_size=0):
 
 def parse_gcs_zip(zip_file, path, min_size=0):
     contents = read_from_gcs_zip(zip_file, path)
-    swc_dict = (
-        fast_parse(contents) if len(contents) > min_size else {"id": [-1]}
-    )
+    parse_bool = len(contents) > min_size
+    swc_dict = fast_parse(contents) if parse_bool else {"id": [-1]}
     return utils.get_swc_id(path), swc_dict
 
 
@@ -143,9 +142,14 @@ def fast_parse(contents):
     min_id = np.min(swc_dict["id"])
     swc_dict["id"] -= min_id
     swc_dict["pid"] -= min_id
+    swc_dict["radius"] /= 1000.0
     return swc_dict
 
 
+def reindex(arr, idxs):
+    return arr[idxs]
+    
+
 def get_contents(swc_contents):
     offset = [0, 0, 0]
     for i, line in enumerate(swc_contents):
@@ -333,10 +337,12 @@ def to_graph(swc_dict, graph_id=None, set_attrs=False):
 
 
 def __add_attributes(swc_dict, graph):
-    xyz = swc_dict["xyz"]
-    radii = swc_dict["radius"]
-    attrs = [{"xyz": xyz[i], "radius": radii[i]} for i in graph.nodes]
-    nx.set_node_attributes(graph, dict(zip(swc_dict["id"], attrs)))
+    attrs = dict()
+    for idx, node_id in enumerate(swc_dict["id"]):
+        attrs[node_id] = {
+            "xyz": swc_dict["xyz"][idx], "radius": swc_dict["radius"][idx]
+        }
+    nx.set_node_attributes(graph, attrs)
     return graph
 
 
diff --git a/src/deep_neurographs/utils.py b/src/deep_neurographs/utils.py
index f72695a..c9d1d8d 100644
--- a/src/deep_neurographs/utils.py
+++ b/src/deep_neurographs/utils.py
@@ -15,6 +15,7 @@
 import shutil
 from copy import deepcopy
 from io import BytesIO
+from skimage.color import label2rgb
 from time import time
 from zipfile import ZipFile
 
@@ -425,6 +426,11 @@ def write_json(path, contents):
         json.dump(contents, f)
 
 
+def write_txt(path, contents):
+    f = open(path, "w")
+    f.write(contents)
+    f.close()
+
 # --- coordinate conversions ---
 def world_to_img(neurograph, node_or_xyz):
     if type(node_or_xyz) == int:
@@ -500,6 +506,12 @@ def get_img_mip(img, axis=0):
     return np.max(img, axis=axis)
 
 
+def get_labels_mip(img, axis=0):
+    mip = np.max(img, axis=axis)
+    mip = label2rgb(mip)
+    return (255 * mip).astype(np.uint8)
+
+
 def normalize_img(img):
     img -= np.min(img)
     return img / np.max(img)