diff --git a/sexp_effects/primitive_libs/color_ops.py b/sexp_effects/primitive_libs/color_ops.py
index dd9076c..a0da497 100644
--- a/sexp_effects/primitive_libs/color_ops.py
+++ b/sexp_effects/primitive_libs/color_ops.py
@@ -8,14 +8,27 @@ import numpy as np
 import cv2
 
 
+def _to_numpy(img):
+    """Convert GPU frames or CuPy arrays to numpy for CPU processing."""
+    # Handle GPUFrame objects
+    if hasattr(img, 'cpu'):
+        return img.cpu
+    # Handle CuPy arrays
+    if hasattr(img, 'get'):
+        return img.get()
+    return img
+
+
 def prim_adjust(img, brightness=0, contrast=1):
     """Adjust brightness and contrast. Brightness: -255 to 255, Contrast: 0 to 3+."""
+    img = _to_numpy(img)
     result = (img.astype(np.float32) - 128) * contrast + 128 + brightness
     return np.clip(result, 0, 255).astype(np.uint8)
 
 
-def prim_mix_gray(img, amount):
+def prim_mix_gray(img_raw, amount):
     """Mix image with its grayscale version. 0=original, 1=grayscale."""
+    img = _to_numpy(img_raw)
     gray = 0.299 * img[:, :, 0] + 0.587 * img[:, :, 1] + 0.114 * img[:, :, 2]
     gray_rgb = np.stack([gray, gray, gray], axis=-1)
     result = img.astype(np.float32) * (1 - amount) + gray_rgb * amount
@@ -24,11 +37,13 @@ def prim_mix_gray(img, amount):
 
 def prim_invert_img(img):
     """Invert all pixel values."""
+    img = _to_numpy(img)
     return (255 - img).astype(np.uint8)
 
 
 def prim_shift_hsv(img, h=0, s=1, v=1):
     """Shift HSV: h=degrees offset, s/v=multipliers."""
+    img = _to_numpy(img)
     hsv = cv2.cvtColor(img, cv2.COLOR_RGB2HSV).astype(np.float32)
     hsv[:, :, 0] = (hsv[:, :, 0] + h / 2) % 180
     hsv[:, :, 1] = np.clip(hsv[:, :, 1] * s, 0, 255)
@@ -38,6 +53,7 @@ def prim_shift_hsv(img, h=0, s=1, v=1):
 
 def prim_add_noise(img, amount):
     """Add gaussian noise to image."""
+    img = _to_numpy(img)
     noise = np.random.normal(0, amount, img.shape)
     result = img.astype(np.float32) + noise
     return np.clip(result, 0, 255).astype(np.uint8)
@@ -45,6 +61,7 @@ def prim_add_noise(img, amount):
 
 def prim_quantize(img, levels):
     """Reduce to N color levels per channel."""
+    img = _to_numpy(img)
     levels = max(2, int(levels))
     factor = 256 / levels
     result = (img // factor) * factor + factor // 2
@@ -53,6 +70,7 @@ def prim_quantize(img, levels):
 
 def prim_sepia(img, intensity=1.0):
     """Apply sepia tone effect."""
+    img = _to_numpy(img)
     sepia_matrix = np.array([
         [0.393, 0.769, 0.189],
         [0.349, 0.686, 0.168],
@@ -65,6 +83,7 @@ def prim_sepia(img, intensity=1.0):
 
 def prim_grayscale(img):
     """Convert to grayscale (still RGB output)."""
+    img = _to_numpy(img)
     gray = 0.299 * img[:, :, 0] + 0.587 * img[:, :, 1] + 0.114 * img[:, :, 2]
     return np.stack([gray, gray, gray], axis=-1).astype(np.uint8)