diff --git a/nodes/composite.py b/nodes/composite.py
index 1e4fe80..88e8b1f 100644
--- a/nodes/composite.py
+++ b/nodes/composite.py
@@ -1,7 +1,4 @@
 import torch
-import cvcuda
-import cv2
-import numpy as np
 
 
 class Composite:
@@ -35,41 +32,19 @@ class Composite:
                 "mismatch number of backgrounds, foregrounds and foreground masks"
             )
 
-        if mode == "cpu":
-            inverse_masks = 1.0 - foreground_masks
+        if mode != "cuda" and mode != "cpu":
+            raise Exception("invalid mode")
 
-            fgs = foregrounds * foreground_masks.unsqueeze(-1)
-            bgs = backgrounds * inverse_masks.unsqueeze(-1)
-
-            fgs_np = (fgs * 255.0).clamp(0, 255).to(dtype=torch.uint8).cpu().numpy()
-            bgs_np = (bgs * 255.0).clamp(0, 255).to(dtype=torch.uint8).cpu().numpy()
-
-            results = []
-            for fg, bg in zip(fgs_np, bgs_np):
-                result = cv2.add(fg, bg)
-                results.append(result)
-
-            return (
-                torch.from_numpy(np.stack(results, axis=0).astype(np.float32) / 255.0),
-            )
-        elif mode == "cuda":
+        if mode == "cuda":
             foregrounds = foregrounds.to("cuda")
             backgrounds = backgrounds.to("cuda")
             foreground_masks = foreground_masks.to("cuda")
 
-            fgs = cvcuda.convertto(
-                cvcuda.as_tensor(foregrounds, "NHWC"), np.uint8, scale=255
-            )
-            bgs = cvcuda.convertto(
-                cvcuda.as_tensor(backgrounds, "NHWC"), np.uint8, scale=255
-            )
-            fgmasks = cvcuda.convertto(
-                cvcuda.as_tensor(foreground_masks.unsqueeze(-1), "NHWC"),
-                np.uint8,
-                scale=255,
-            )
-            result = cvcuda.composite(fgs, bgs, fgmasks, 3)
+        inverse_masks = 1.0 - foreground_masks
 
-            return (torch.as_tensor(result.cuda()) / 255.0,)
-        else:
-            raise Exception("invalid mode")
+        fgs = foregrounds * foreground_masks.unsqueeze(-1)
+        bgs = backgrounds * inverse_masks.unsqueeze(-1)
+
+        results = fgs + bgs
+
+        return (results,)
diff --git a/nodes/gaussian_blur.py b/nodes/gaussian_blur.py
index a7111fe..0df9bef 100644
--- a/nodes/gaussian_blur.py
+++ b/nodes/gaussian_blur.py
@@ -1,7 +1,6 @@
 import torch
-import cvcuda
-import cv2
-import numpy as np
+
+from torchvision.transforms import v2
 
 
 class GaussianBlur:
@@ -27,29 +26,17 @@ class GaussianBlur:
         sigma: int = 5,
         mode: str = "cuda",
     ):
-        if mode == "cpu":
-            images_np = (
-                (images * 255.0).clamp(0, 255).to(dtype=torch.uint8).cpu().numpy()
-            )
+        if mode != "cuda" and mode != "cpu":
+            raise Exception("invalid mode")
 
-            results = []
-            for image in images_np:
-                result = cv2.GaussianBlur(
-                    image, (kernel_size, kernel_size), sigma, sigma
-                )
-                results.append(result)
-
-            return (
-                torch.from_numpy(np.stack(results, axis=0).astype(np.float32) / 255.0),
-            )
-        elif mode == "cuda":
+        if mode == "cuda":
             images = images.to("cuda")
 
-            result = cvcuda.gaussian(
-                cvcuda.as_tensor(images, "NHWC"),
-                (kernel_size, kernel_size),
-                (sigma, sigma),
-            )
-            return (torch.as_tensor(result.cuda()),)
-        else:
-            raise Exception("invalid mode")
+        gaussian_blur = v2.GaussianBlur((kernel_size, kernel_size), (sigma, sigma))
+        # torchvision expects a BCHW tensor
+        # Convert input BHWC -> BCHW
+        blurred = gaussian_blur(images.permute(0, 3, 1, 2))
+
+        # Comfy expects a BHWC tensor
+        # Convert output BCHW -> BHWC
+        return (blurred.permute(0, 2, 3, 1),)
diff --git a/pyproject.toml b/pyproject.toml
index 7273332..f7051ee 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,10 +4,8 @@ description = "ComfyUI nodes for editing background of images/videos with CUDA a
 version = "1.0.0"
 license = { file = "LICENSE" }
 dependencies = [
-  "opencv-python",
-  "numpy",
   "torch",
-  "https://github.com/CVCUDA/CV-CUDA/releases/download/v0.12.0-beta/cvcuda_cu12-0.12.0b0-cp311-cp311-linux_x86_64.whl",
+  "torchvision"
 ]
 
 [project.urls]
diff --git a/requirements.txt b/requirements.txt
index 81ae987..37f700a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,2 @@
-opencv-python
-numpy
 torch
-https://github.com/CVCUDA/CV-CUDA/releases/download/v0.12.0-beta/cvcuda_cu12-0.12.0b0-cp311-cp311-linux_x86_64.whl
\ No newline at end of file
+torchvision
\ No newline at end of file