diff --git a/omnigibson/scene_graphs/graph_builder.py b/omnigibson/scene_graphs/graph_builder.py
index 81d668309..1f987748c 100644
--- a/omnigibson/scene_graphs/graph_builder.py
+++ b/omnigibson/scene_graphs/graph_builder.py
@@ -4,7 +4,6 @@
 import torch as th
 from matplotlib import pyplot as plt
 from PIL import Image
-from torchvision.transforms import ToPILImage, ToTensor
 
 from omnigibson import object_states
 from omnigibson.object_states.factory import get_state_name
@@ -12,6 +11,7 @@
 from omnigibson.robots import BaseRobot
 from omnigibson.sensors import VisionSensor
 from omnigibson.utils import transform_utils as T
+from omnigibson.utils.numpy_utils import pil_to_tensor
 
 
 def _formatted_aabb(obj):
@@ -289,14 +289,10 @@ def _draw_graph():
     robot_view = (robot_camera_sensor.get_obs()[0]["rgb"][..., :3]).to(th.uint8)
     imgheight, imgwidth, _ = robot_view.shape
 
-    pil_transform = ToPILImage()
-    torch_transform = ToTensor()
-
-    # check imgheight and imgwidth; if they are too small, we need to upsample the image to 1280x1280
+    # check imgheight and imgwidth; if they are too small, we need to upsample the image to 640x640
     if imgheight < 640 or imgwidth < 640:
-        robot_view = torch_transform(
-            pil_transform((robot_view.permute(2, 0, 1).cpu())).resize((640, 640), Image.BILINEAR)
-        ).permute(1, 2, 0)
+        # Convert to PIL Image to upsample, then write back to tensor
+        robot_view = pil_to_tensor(Image.fromarray(robot_view.cpu().numpy()).resize((640, 640), Image.BILINEAR))
         imgheight, imgwidth, _ = robot_view.shape
 
     figheight = 4.8
diff --git a/omnigibson/utils/numpy_utils.py b/omnigibson/utils/numpy_utils.py
index 1d540c27b..fda0a3164 100644
--- a/omnigibson/utils/numpy_utils.py
+++ b/omnigibson/utils/numpy_utils.py
@@ -15,3 +15,7 @@ def vtarray_to_torch(vtarray, dtype=th.float32, device="cpu"):
     else:
         assert device.startswith("cuda")
         return th.tensor(np.array(vtarray), dtype=dtype, device=device)
+
+
+def pil_to_tensor(pil_image):
+    return th.tensor(np.array(pil_image), dtype=th.uint8)
diff --git a/setup.py b/setup.py
index f69a32992..82eae318b 100644
--- a/setup.py
+++ b/setup.py
@@ -22,8 +22,8 @@
     packages=find_packages(),
     install_requires=[
         "gymnasium>=0.28.1",
-        "numpy~=1.23.5",
-        "scipy~=1.10.1",
+        "numpy>=1.23.5",
+        "scipy>=1.10.1",
         "GitPython~=3.1.40",
         "transforms3d~=0.4.1",
         "networkx~=3.2.1",
@@ -35,7 +35,7 @@
         "h5py~=3.10.0",
         "cryptography~=41.0.7",
         "bddl~=3.5.0",
-        "opencv-python~=4.8.1",
+        "opencv-python>=4.8.1",
         "nest_asyncio~=1.5.8",
         "imageio~=2.33.1",
         "imageio-ffmpeg~=0.4.9",
@@ -46,8 +46,7 @@
         "aenum~=3.1.15",
         "rtree~=1.2.0",
         "graphviz~=0.20",
-        "numba~=0.60.0",
-        "torchvision~=0.18.1",
+        "numba>=0.60.0",
     ],
     extras_require={
         "isaac": ["isaacsim-for-omnigibson>=4.1.0"],