diff --git a/README.md b/README.md
index 53a5404..d64cdb3 100644
--- a/README.md
+++ b/README.md
@@ -132,7 +132,6 @@ You will need:
 - An Athena host URL.
 - An OAuth client ID and secret with access to the Athena environment.
 - An affiliate with Athena enabled.
-- `imagemagick` installed on your system and on your path at `magick`.
 
 
 #### Preparing your environment
diff --git a/common_utils/__init__.py b/common_utils/__init__.py
new file mode 100644
index 0000000..89c7128
--- /dev/null
+++ b/common_utils/__init__.py
@@ -0,0 +1,5 @@
+"""Utility package for testing and examples.
+
+This package contains helper functions that are not core to the client library,
+but are shared across the examples and the tests.
+"""
diff --git a/examples/utils/image_generation.py b/common_utils/image_generation.py
similarity index 74%
rename from examples/utils/image_generation.py
rename to common_utils/image_generation.py
index 7feb8f2..3b11b0b 100644
--- a/examples/utils/image_generation.py
+++ b/common_utils/image_generation.py
@@ -1,31 +1,31 @@
-"""Ultra-fast random image creation utilities for maximum throughput."""
+"""Ultra-fast random image creation utilities for maximum throughput.
+
+This file is intended to be used for generating benign test images for the
+purposes of integration testing the client, as is provided as a convenience
+for API consumers.
+"""
 
 import asyncio
-import io
 import random
 import time
 from collections.abc import AsyncIterator
 
-from PIL import Image, ImageDraw
+import cv2 as cv
+import numpy as np
 
 from resolver_athena_client.client.models import ImageData
 
 # Global cache for reusable objects and constants
-_image_cache: dict[
-    tuple[int, int], tuple[Image.Image, ImageDraw.ImageDraw]
-] = {}
+_image_cache: dict[tuple[int, int], np.ndarray] = {}
 _rng = random.Random()  # noqa: S311 - Not used for cryptographic purposes
 
 
-def _get_cached_image(
-    width: int, height: int
-) -> tuple[Image.Image, ImageDraw.ImageDraw]:
-    """Get cached image and draw objects, creating if needed."""
+def _get_cached_image(width: int, height: int) -> np.ndarray:
+    """Get cached image array, creating if needed."""
     key = (width, height)
     if key not in _image_cache:
-        img = Image.new("RGB", (width, height), (0, 0, 0))
-        draw = ImageDraw.Draw(img)
-        _image_cache[key] = (img, draw)
+        img = np.zeros((height, width, 3), dtype=np.uint8)
+        _image_cache[key] = img
     return _image_cache[key]
 
 
@@ -45,8 +45,9 @@ def create_random_image(
         PNG image bytes
 
     """
-    # Get cached image and draw objects
-    image, draw = _get_cached_image(width, height)
+    # Get cached image array
+    image = _get_cached_image(width, height)
+    img = image.copy()
 
     # Random background color
     bg_r, bg_g, bg_b = (
@@ -56,21 +57,24 @@ def create_random_image(
     )
 
     # Fill with background color
-    draw.rectangle([0, 0, width, height], fill=(bg_r, bg_g, bg_b))
+    img[:, :] = (bg_b, bg_g, bg_r)  # OpenCV uses BGR
 
     # Add single accent rectangle for visual variation
-    accent_color = (255 - bg_r, 255 - bg_g, 255 - bg_b)
+    accent_color = (255 - bg_b, 255 - bg_g, 255 - bg_r)  # BGR
     x1, y1 = width // 4, height // 4
     x2, y2 = (width * 3) // 4, (height * 3) // 4
-    draw.rectangle([x1, y1, x2, y2], fill=accent_color)
+    img = cv.rectangle(img, (x1, y1), (x2, y2), accent_color, thickness=-1)
 
     if img_format.upper() == "RAW_UINT8":
-        return image.tobytes()
+        return img.tobytes()
 
-    # Convert to PNG bytes
-    buffer = io.BytesIO()
-    image.save(buffer, format=img_format)
-    return buffer.getvalue()
+    # Convert to PNG/JPEG bytes
+    ext = f".{img_format.lower()}"
+    success, buf = cv.imencode(ext, img)
+    if not success:
+        err = f"Failed to encode image as {img_format}"
+        raise RuntimeError(err)
+    return buf.tobytes()
 
 
 def create_batch_images(
@@ -90,29 +94,32 @@ def create_batch_images(
 
     """
     images: list[bytes] = []
-    image, draw = _get_cached_image(width, height)
+    image = _get_cached_image(width, height)
 
     # Pre-calculate accent rectangle coordinates
     x1, y1 = width // 4, height // 4
     x2, y2 = (width * 3) // 4, (height * 3) // 4
 
     for _ in range(count):
+        img = image.copy()
         # Random background
         bg_r, bg_g, bg_b = (
             _rng.randint(0, 255),
             _rng.randint(0, 255),
             _rng.randint(0, 255),
         )
-        draw.rectangle([0, 0, width, height], fill=(bg_r, bg_g, bg_b))
+        img[:, :] = (bg_b, bg_g, bg_r)  # OpenCV uses BGR
 
         # Complement accent color
-        accent_color = (255 - bg_r, 255 - bg_g, 255 - bg_b)
-        draw.rectangle([x1, y1, x2, y2], fill=accent_color)
+        accent_color = (255 - bg_b, 255 - bg_g, 255 - bg_r)  # BGR
+        img = cv.rectangle(img, (x1, y1), (x2, y2), accent_color, thickness=-1)
 
         # Convert to PNG bytes
-        buffer = io.BytesIO()
-        image.save(buffer, format="PNG")
-        images.append(buffer.getvalue())
+        success, buf = cv.imencode(".png", img)
+        if not success:
+            msg = "Failed to encode image as PNG"
+            raise RuntimeError(msg)
+        images.append(buf.tobytes())
 
     return images
 
@@ -196,18 +203,7 @@ async def rate_limited_image_iter(
 def create_random_image_generator(
     max_images: int, rate_limit_min_interval_ms: int | None = None
 ) -> AsyncIterator[ImageData]:
-    """Generate a stream of random test images.
-
-    Args:
-    ----
-        max_images: Maximum number of images to generate
-        rate_limit_min_interval_ms: Minimum interval in ms between images
-
-    Yields:
-    ------
-        ImageData objects containing random image bytes
-
-    """
+    """Create an async generator for images with optional rate limiting."""
     if rate_limit_min_interval_ms is not None:
         return rate_limited_image_iter(rate_limit_min_interval_ms, max_images)
 
diff --git a/docs/api/transformers.rst b/docs/api/transformers.rst
index 22aff0c..5506dbc 100644
--- a/docs/api/transformers.rst
+++ b/docs/api/transformers.rst
@@ -241,7 +241,7 @@ Transformers accept configuration through their constructors:
 **ImageResizer Configuration:**
 
 * ``target_size``: Tuple of (width, height) for output dimensions
-* ``resampling``: PIL resampling algorithm (default: ``Image.LANCZOS``)
+* ``resampling``: OpenCV resampling algorithm (default: ``cv.INTER_LINEAR``)
 * ``maintain_aspect_ratio``: Whether to preserve aspect ratio (default: ``True``)
 
 **BrotliCompressor Configuration:**
diff --git a/examples/classify_single_example.py b/examples/classify_single_example.py
index b12041b..346d3db 100755
--- a/examples/classify_single_example.py
+++ b/examples/classify_single_example.py
@@ -10,7 +10,7 @@
 
 from dotenv import load_dotenv
 
-from examples.utils.image_generation import create_test_image
+from common_utils.image_generation import create_test_image
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import (
diff --git a/examples/example.py b/examples/example.py
index e4e8220..ce87722 100755
--- a/examples/example.py
+++ b/examples/example.py
@@ -10,7 +10,7 @@
 
 from dotenv import load_dotenv
 
-from examples.utils.image_generation import iter_images
+from common_utils.image_generation import iter_images
 from examples.utils.streaming_classify_utils import count_and_yield
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
diff --git a/pyproject.toml b/pyproject.toml
index 0ce20e1..7ba0386 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -27,7 +27,7 @@ dependencies = [
     "grpcio-tools>=1.74.0",
     "httpx>=0.25.0",
     "numpy>=2.2.6",
-    "pillow>=11.3.0",
+    "opencv-python-headless>=4.13.0.92"
 ]
 
 [project.optional-dependencies]
diff --git a/src/resolver_athena_client/client/athena_options.py b/src/resolver_athena_client/client/athena_options.py
index 2a616d2..7902223 100644
--- a/src/resolver_athena_client/client/athena_options.py
+++ b/src/resolver_athena_client/client/athena_options.py
@@ -2,12 +2,13 @@
 
 from dataclasses import dataclass
 
-from PIL.Image import Resampling
-
 from resolver_athena_client.client.correlation import (
     CorrelationProvider,
     HashCorrelationProvider,
 )
+from resolver_athena_client.client.transformers.core import (
+    OpenCVResamplingAlgorithm,
+)
 
 
 @dataclass
@@ -69,4 +70,6 @@ class AthenaOptions:
     timeout: float | None = 120.0
     keepalive_interval: float | None = None
     compression_quality: int = 11  # Brotli quality level (0-11)
-    resampling_algorithm: Resampling = Resampling.LANCZOS
+    resampling_algorithm: OpenCVResamplingAlgorithm = (
+        OpenCVResamplingAlgorithm.BILINEAR
+    )
diff --git a/src/resolver_athena_client/client/transformers/core.py b/src/resolver_athena_client/client/transformers/core.py
index 6fea7b6..8041a28 100644
--- a/src/resolver_athena_client/client/transformers/core.py
+++ b/src/resolver_athena_client/client/transformers/core.py
@@ -6,10 +6,11 @@
 """
 
 import asyncio
-from io import BytesIO
+import enum
 
 import brotli
-from PIL import Image
+import cv2 as cv
+import numpy as np
 
 from resolver_athena_client.client.consts import EXPECTED_HEIGHT, EXPECTED_WIDTH
 from resolver_athena_client.client.models import ImageData
@@ -20,6 +21,19 @@
 _expected_raw_size = EXPECTED_WIDTH * EXPECTED_HEIGHT * 3
 
 
+class OpenCVResamplingAlgorithm(enum.Enum):
+    """Open CV Resampling Configuration.
+
+    Enum for ease of configuration and type-safety when selecting OpenCV
+    resampling algorithms.
+    """
+
+    NEAREST = cv.INTER_NEAREST
+    BOX = cv.INTER_AREA
+    BILINEAR = cv.INTER_LINEAR
+    LANCZOS = cv.INTER_LANCZOS4
+
+
 def _is_raw_bgr_expected_size(data: bytes) -> bool:
     """Detect if data is already a raw BGR array of expected size."""
     return len(data) == _expected_raw_size
@@ -27,7 +41,9 @@ def _is_raw_bgr_expected_size(data: bytes) -> bool:
 
 async def resize_image(
     image_data: ImageData,
-    sampling_algorithm: Image.Resampling = Image.Resampling.LANCZOS,
+    sampling_algorithm: OpenCVResamplingAlgorithm = (
+        OpenCVResamplingAlgorithm.BILINEAR
+    ),
 ) -> ImageData:
     """Resize an image to expected dimensions.
 
@@ -49,31 +65,23 @@ def process_image() -> tuple[bytes, bool]:
             return image_data.data, False  # No transformation needed
 
         # Try to load the image data directly
-        input_buffer = BytesIO(image_data.data)
-
-        with Image.open(input_buffer) as image:
-            # Convert to RGB if needed
-            rgb_image = image.convert("RGB") if image.mode != "RGB" else image
-
-            # Resize if needed
-            if rgb_image.size != _target_size:
-                resized_image = rgb_image.resize(
-                    _target_size, sampling_algorithm
-                )
-            else:
-                resized_image = rgb_image
-
-            rgb_bytes = resized_image.tobytes()
-
-            # Convert RGB to BGR by swapping channels
-            bgr_bytes = bytearray(len(rgb_bytes))
-
-            for i in range(0, len(rgb_bytes), 3):
-                bgr_bytes[i] = rgb_bytes[i + 2]
-                bgr_bytes[i + 1] = rgb_bytes[i + 1]
-                bgr_bytes[i + 2] = rgb_bytes[i]
-
-            return bytes(bgr_bytes), True  # Data was transformed
+        img_data_buf = np.frombuffer(image_data.data, dtype=np.uint8)
+        img = cv.imdecode(img_data_buf, cv.IMREAD_COLOR)
+
+        if img is None:
+            err = "Failed to decode image data for resizing"
+            raise ValueError(err)
+
+        if img.shape[0] == EXPECTED_HEIGHT and img.shape[1] == EXPECTED_WIDTH:
+            resized_img = img
+        else:
+            resized_img = cv.resize(
+                img, _target_size, interpolation=sampling_algorithm.value
+            )
+
+        # OpenCV loads in BGR format by default, so we can directly convert to
+        # bytes
+        return resized_img.tobytes(), True  # Data was transformed
 
     # Use thread pool for CPU-intensive processing
     resized_bytes, was_transformed = await asyncio.to_thread(process_image)
diff --git a/tests/client/transformers/test_core.py b/tests/client/transformers/test_core.py
index 878ab43..2c41538 100644
--- a/tests/client/transformers/test_core.py
+++ b/tests/client/transformers/test_core.py
@@ -1,9 +1,8 @@
 """Test core transformation functions."""
 
-from io import BytesIO
-
+import cv2 as cv
+import numpy as np
 import pytest
-from PIL import Image
 
 from resolver_athena_client.client.consts import (
     EXPECTED_HEIGHT,
@@ -19,11 +18,24 @@
 def create_test_image(
     width: int = 100, height: int = 100, mode: str = "RGB"
 ) -> bytes:
-    """Create a test image with specified dimensions."""
-    img = Image.new(mode, (width, height), color="red")
-    img_bytes = BytesIO()
-    img.save(img_bytes, format="PNG")
-    return img_bytes.getvalue()
+    """Create a test image with specified dimensions using OpenCV."""
+    # Map mode to OpenCV color shape
+    if mode == "RGB":
+        color = (255, 0, 0)  # Red in RGB
+        img = np.full((height, width, 3), color, dtype=np.uint8)
+    elif mode == "L":
+        color = 76  # Red in grayscale
+        img = np.full((height, width), color, dtype=np.uint8)
+    else:
+        err = f"Unsupported mode: {mode}"
+        raise ValueError(err)
+
+    success, buf = cv.imencode(".png", img)
+    if not success:
+        err = "Failed to encode image to PNG"
+        raise RuntimeError(err)
+
+    return buf.tobytes()
 
 
 @pytest.mark.asyncio
diff --git a/tests/client/transformers/test_hash_pipeline.py b/tests/client/transformers/test_hash_pipeline.py
index dcbfeda..8c2cbc1 100644
--- a/tests/client/transformers/test_hash_pipeline.py
+++ b/tests/client/transformers/test_hash_pipeline.py
@@ -1,10 +1,10 @@
 """Tests for hash list behavior throughout the transformation pipeline."""
 
 import hashlib
-from io import BytesIO
 
+import cv2 as cv
+import numpy as np
 import pytest
-from PIL import Image
 
 from resolver_athena_client.client.consts import EXPECTED_HEIGHT, EXPECTED_WIDTH
 from resolver_athena_client.client.models import ImageData
@@ -21,10 +21,17 @@
 
 def create_test_png_image(width: int = 200, height: int = 200) -> bytes:
     """Create a test PNG image with specified dimensions."""
-    img = Image.new("RGB", (width, height), color=(255, 0, 0))
-    buffer = BytesIO()
-    img.save(buffer, format="PNG")
-    return buffer.getvalue()
+
+    # Create a red RGB image using numpy
+    img = np.zeros((height, width, 3), dtype=np.uint8)
+    img[:] = (255, 0, 0)  # Red color
+
+    # Encode image as PNG to memory
+    success, buffer = cv.imencode(".png", img)
+    if not success:
+        err = "Failed to encode image as PNG"
+        raise RuntimeError(err)
+    return buffer.tobytes()
 
 
 @pytest.mark.asyncio
diff --git a/tests/functional/conftest.py b/tests/functional/conftest.py
index e7cd324..88385d5 100644
--- a/tests/functional/conftest.py
+++ b/tests/functional/conftest.py
@@ -1,8 +1,8 @@
 import os
-import shutil
-import subprocess
 import uuid
 
+import cv2 as cv
+import numpy as np
 import pytest
 import pytest_asyncio
 from dotenv import load_dotenv
@@ -14,7 +14,30 @@
     EXPECTED_WIDTH,
     MAX_DEPLOYMENT_ID_LENGTH,
 )
-from tests.utils.image_generation import create_test_image
+
+
+def _create_base_test_image_opencv(width: int, height: int) -> np.ndarray:
+    """Create a test image using only OpenCV2.
+
+    Creates a simple test pattern with background and accent colors.
+
+    Args:
+        width: Image width in pixels
+        height: Image height in pixels
+
+    Returns:
+        numpy array in BGR format suitable for cv.imencode
+    """
+    # Create a simple test image with random colors
+    # Background color (blue-green)
+    img_bgr = np.zeros((height, width, 3), dtype=np.uint8)
+    img_bgr[:, :] = (100, 150, 200)  # BGR format
+
+    # Add an accent rectangle for visual variation
+    x1, y1 = width // 4, height // 4
+    x2, y2 = (width * 3) // 4, (height * 3) // 4
+    return cv.rectangle(img_bgr, (x1, y1), (x2, y2), (200, 100, 50), -1)
+
 
 SUPPORTED_TEST_FORMATS = [
     "gif",
@@ -25,13 +48,15 @@
     "pbm",
     "pgm",
     "ppm",
-    "pxm",
     "pnm",
     "sr",
     "ras",
     "tiff",
     "pic",
     "raw_uint8",
+    # pxm - OpenCV2 has issues with this format, the docs state it's
+    # supported, but pxm is also used to mean PBM/PGM/PPM which are supported,
+    # so it's unclear if this format is truly supported.
 ]
 
 
@@ -91,47 +116,40 @@ def valid_formatted_image(
     request: pytest.FixtureRequest,
     tmp_path_factory: pytest.TempPathFactory,
 ) -> bytes:
-    image_format = request.param
-    if (magick_path := shutil.which("magick")) is None and (
-        magick_path := shutil.which("convert")
-    ) is None:
-        pytest.fail(
-            "ImageMagick 'magick' or 'convert' command not found - cannot "
-            "run multi-format test"
-        )
+    """Generate test images in various formats using OpenCV2.
 
+    Images are cached to disk to avoid regenerating on every test run.
+    """
+    image_format = request.param
     image_dir = tmp_path_factory.mktemp("images")
+    base_image = _create_base_test_image_opencv(EXPECTED_WIDTH, EXPECTED_HEIGHT)
 
-    base_image_format = "png"
-    base_image = create_test_image(
-        EXPECTED_WIDTH, EXPECTED_HEIGHT, img_format=base_image_format
-    )
-    base_image_path = image_dir / "base_image.png"
-    if not base_image_path.exists():
-        with base_image_path.open("wb") as f:
-            _ = f.write(base_image)
-
-    if image_format == base_image_format:
-        return base_image
-
+    # Handle raw_uint8 format separately - return raw BGR bytes
     if image_format == "raw_uint8":
-        return create_test_image(
-            EXPECTED_WIDTH, EXPECTED_HEIGHT, img_format="raw_uint8"
-        )
+        return base_image.tobytes()
 
+    # Check if image already exists in cache
     image_path = image_dir / f"test_image.{image_format}"
-    if not image_path.exists():
-        cmd = [magick_path, str(base_image_path), str(image_path)]
-        _ = subprocess.run(  # noqa: S603 - false positive :(
-            cmd,
-            check=True,
-            shell=False,
-        )
-
-        if not image_path.exists():
-            pytest.fail(
-                f"Failed to create {image_format} image with command: {cmd}"
-            )
-
-    with image_path.open("rb") as f:
-        return f.read()
+    if image_path.exists():
+        with image_path.open("rb") as f:
+            return f.read()
+
+    # Convert format using OpenCV2 and cache to disk
+    # Encode image in the target format
+    if image_format in ["pgm", "pbm"]:
+        # PGM and PBM are grayscale, so convert the image to grayscale
+        gray_image = cv.cvtColor(base_image, cv.COLOR_BGR2GRAY)
+        success, encoded = cv.imencode(f".{image_format}", gray_image)
+    else:
+        success, encoded = cv.imencode(f".{image_format}", base_image)
+
+    if not success:
+        pytest.fail(f"OpenCV failed to encode image in {image_format} format")
+
+    image_bytes = encoded.tobytes()
+
+    # Cache the image to disk
+    with image_path.open("wb") as f:
+        _ = f.write(image_bytes)
+
+    return image_bytes
diff --git a/tests/functional/test_classify_single.py b/tests/functional/test_classify_single.py
index ae29c60..3fd26ff 100644
--- a/tests/functional/test_classify_single.py
+++ b/tests/functional/test_classify_single.py
@@ -1,5 +1,6 @@
 import pytest
 
+from common_utils.image_generation import create_test_image
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import (
@@ -7,7 +8,6 @@
     create_channel_with_credentials,
 )
 from resolver_athena_client.client.models import ImageData
-from tests.utils.image_generation import create_test_image
 
 
 @pytest.mark.asyncio
diff --git a/tests/functional/test_classify_streaming.py b/tests/functional/test_classify_streaming.py
index fef9e14..9805e8f 100644
--- a/tests/functional/test_classify_streaming.py
+++ b/tests/functional/test_classify_streaming.py
@@ -3,9 +3,9 @@
 
 import pytest
 
+from common_utils.image_generation import create_random_image_generator
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import CredentialHelper
-from tests.utils.image_generation import create_random_image_generator
 from tests.utils.streaming_classify_utils import (
     classify_images,
     classify_images_break_on_first_result,
diff --git a/tests/functional/test_invalid_affiliate.py b/tests/functional/test_invalid_affiliate.py
index 974781e..6684ff2 100644
--- a/tests/functional/test_invalid_affiliate.py
+++ b/tests/functional/test_invalid_affiliate.py
@@ -3,6 +3,7 @@
 import pytest
 from dotenv import load_dotenv
 
+from common_utils.image_generation import create_test_image
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import (
@@ -11,7 +12,6 @@
 )
 from resolver_athena_client.client.exceptions import AthenaError
 from resolver_athena_client.client.models import ImageData
-from tests.utils.image_generation import create_test_image
 
 
 @pytest.mark.asyncio
diff --git a/tests/functional/test_invalid_image.py b/tests/functional/test_invalid_image.py
index 2f1758e..68eed41 100644
--- a/tests/functional/test_invalid_image.py
+++ b/tests/functional/test_invalid_image.py
@@ -2,8 +2,8 @@
 from collections.abc import AsyncIterator
 
 import pytest
-from PIL import UnidentifiedImageError
 
+from common_utils.image_generation import create_test_image
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import (
@@ -13,7 +13,6 @@
 from resolver_athena_client.client.consts import EXPECTED_HEIGHT, EXPECTED_WIDTH
 from resolver_athena_client.client.exceptions import AthenaError
 from resolver_athena_client.client.models import ImageData
-from tests.utils.image_generation import create_test_image
 from tests.utils.streaming_classify_utils import classify_images
 
 
@@ -39,12 +38,11 @@ async def test_classify_single_invalid_image(
             image_bytes = b"this is not a valid image file"
             image_data = ImageData(image_bytes)
 
-            with pytest.raises(UnidentifiedImageError) as e:
+            with pytest.raises(
+                ValueError, match="Failed to decode image data for resizing"
+            ) as e:
                 _ = await client.classify_single(image_data)
 
-            expected_msg = "cannot identify image file"
-            assert expected_msg in str(e.value)
-
         except Exception as e:
             msg = "Unexpected exception during invalid image test"
             raise AssertionError(msg) from e
diff --git a/tests/functional/test_invalid_static_token_auth.py b/tests/functional/test_invalid_static_token_auth.py
index 8cd83fb..b7db8f8 100644
--- a/tests/functional/test_invalid_static_token_auth.py
+++ b/tests/functional/test_invalid_static_token_auth.py
@@ -5,10 +5,10 @@
 from dotenv import load_dotenv
 from grpc.aio import Channel
 
+from common_utils.image_generation import create_test_image
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.models.input_model import ImageData
-from tests.utils.image_generation import create_test_image
 
 
 def create_channel(host: str, token: str) -> Channel:
diff --git a/tests/functional/test_list_deployments.py b/tests/functional/test_list_deployments.py
index 4681008..f99b7e6 100644
--- a/tests/functional/test_list_deployments.py
+++ b/tests/functional/test_list_deployments.py
@@ -1,5 +1,6 @@
 import pytest
 
+from common_utils.image_generation import iter_images
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
 from resolver_athena_client.client.channel import (
@@ -7,7 +8,6 @@
     create_channel_with_credentials,
 )
 from resolver_athena_client.client.deployment_selector import DeploymentSelector
-from tests.utils.image_generation import iter_images
 
 
 @pytest.mark.asyncio
diff --git a/tests/test_classify_single.py b/tests/test_classify_single.py
index 91e7e73..d517ca3 100644
--- a/tests/test_classify_single.py
+++ b/tests/test_classify_single.py
@@ -1,12 +1,12 @@
 """Tests for the classify_single method in AthenaClient."""
 
-import io
 import uuid
 from unittest.mock import AsyncMock, Mock
 
+import cv2 as cv
 import grpc.aio
+import numpy as np
 import pytest
-from PIL import Image
 
 from resolver_athena_client.client.athena_client import AthenaClient
 from resolver_athena_client.client.athena_options import AthenaOptions
@@ -196,10 +196,11 @@ async def test_classify_single_error_handling(
     # Create a simple valid image for testing
 
     # Create a simple 1x1 pixel image
-    img = Image.new("RGB", (1, 1), color="red")
-    img_bytes = io.BytesIO()
-    img.save(img_bytes, format="PNG")
-    valid_image_data = ImageData(img_bytes.getvalue())
+    img_arr = np.ndarray((1, 1, 3), dtype=np.uint8)
+    img_arr.fill(255)
+    success, img = cv.imencode(".png", img_arr, [])
+    assert success, "Failed to encode test image"
+    valid_image_data = ImageData(img.tobytes())
 
     # Enable resizing
     athena_client.options.resize_images = True
diff --git a/tests/utils/image_generation.py b/tests/utils/image_generation.py
deleted file mode 100644
index dd00f35..0000000
--- a/tests/utils/image_generation.py
+++ /dev/null
@@ -1,203 +0,0 @@
-"""Ultra-fast random image creation utilities for maximum throughput."""
-
-import asyncio
-import io
-import random
-import time
-from collections.abc import AsyncIterator
-
-from PIL import Image, ImageDraw
-
-from resolver_athena_client.client.models import ImageData
-
-
-def _rgb_to_bgr(raw_rgb: bytes) -> bytes:
-    data = bytearray(raw_rgb)
-    for i in range(0, len(data), 3):
-        data[i], data[i + 2] = data[i + 2], data[i]
-    return bytes(data)
-
-
-# Global cache for reusable objects and constants
-_image_cache: dict[
-    tuple[int, int], tuple[Image.Image, ImageDraw.ImageDraw]
-] = {}
-_rng = random.Random()  # noqa: S311 - Not used for cryptographic purposes
-
-
-def _get_cached_image(
-    width: int, height: int
-) -> tuple[Image.Image, ImageDraw.ImageDraw]:
-    """Get cached image and draw objects, creating if needed."""
-    key = (width, height)
-    if key not in _image_cache:
-        img = Image.new("RGB", (width, height), (0, 0, 0))
-        draw = ImageDraw.Draw(img)
-        _image_cache[key] = (img, draw)
-    return _image_cache[key]
-
-
-def create_random_image(
-    width: int = 160, height: int = 120, img_format: str = "PNG"
-) -> bytes:
-    """Create a minimal random image optimized for maximum speed.
-
-    Args:
-        width: Width of the test image in pixels (default: 160)
-        height: Height of the test image in pixels (default: 120)
-
-    Returns:
-        PNG image bytes
-
-    """
-    # Get cached image and draw objects
-    image, draw = _get_cached_image(width, height)
-
-    # Random background color
-    bg_r, bg_g, bg_b = (
-        _rng.randint(0, 255),
-        _rng.randint(0, 255),
-        _rng.randint(0, 255),
-    )
-
-    # Fill with background color
-    draw.rectangle([0, 0, width, height], fill=(bg_r, bg_g, bg_b))
-
-    # Add single accent rectangle for visual variation
-    accent_color = (255 - bg_r, 255 - bg_g, 255 - bg_b)
-    x1, y1 = width // 4, height // 4
-    x2, y2 = (width * 3) // 4, (height * 3) // 4
-    draw.rectangle([x1, y1, x2, y2], fill=accent_color)
-
-    if img_format.upper() in {"RAW_UINT8", "RAW_UINT8_BGR"}:
-        return _rgb_to_bgr(image.tobytes())
-
-    # Convert to PNG bytes
-    buffer = io.BytesIO()
-    image.save(buffer, format=img_format)
-    return buffer.getvalue()
-
-
-def create_batch_images(
-    count: int, width: int = 160, height: int = 120
-) -> list[bytes]:
-    """Create multiple images in a batch for maximum efficiency.
-
-    Args:
-        count: Number of images to generate
-        width: Width of the test images in pixels
-        height: Height of the test images in pixels
-
-    Returns:
-        List of PNG image bytes
-
-    """
-    images: list[bytes] = []
-    image, draw = _get_cached_image(width, height)
-
-    # Pre-calculate accent rectangle coordinates
-    x1, y1 = width // 4, height // 4
-    x2, y2 = (width * 3) // 4, (height * 3) // 4
-
-    for _ in range(count):
-        # Random background
-        bg_r, bg_g, bg_b = (
-            _rng.randint(0, 255),
-            _rng.randint(0, 255),
-            _rng.randint(0, 255),
-        )
-        draw.rectangle([0, 0, width, height], fill=(bg_r, bg_g, bg_b))
-
-        # Complement accent color
-        accent_color = (255 - bg_r, 255 - bg_g, 255 - bg_b)
-        draw.rectangle([x1, y1, x2, y2], fill=accent_color)
-
-        # Convert to PNG bytes
-        buffer = io.BytesIO()
-        image.save(buffer, format="PNG")
-        images.append(buffer.getvalue())
-
-    return images
-
-
-async def iter_images(
-    max_images: int | None = None,
-) -> AsyncIterator[ImageData]:
-    """Generate random test images with maximum throughput optimization.
-
-    Args:
-        max_images: Maximum number of images to generate. If None, generates
-            infinitely.
-        counter: Optional list with single integer to track number of images
-            sent.
-
-    Yields:
-        ImageData objects containing PNG image bytes with random content
-
-    """
-    count = 0
-    batch_size = 100  # Large batches for maximum efficiency
-
-    while max_images is None or count < max_images:
-        # Calculate batch size for this iteration
-        if max_images is not None:
-            remaining = max_images - count
-            current_batch_size = min(batch_size, remaining)
-        else:
-            current_batch_size = batch_size
-
-        # Generate batch of images
-        images = create_batch_images(current_batch_size, 160, 120)
-
-        # Yield each image
-        for img_bytes in images:
-            yield ImageData(img_bytes)
-            count += 1
-
-
-def create_test_image(
-    width: int = 160,
-    height: int = 120,
-    seed: int | None = None,
-    img_format: str = "PNG",
-) -> bytes:
-    """Create a test image with specified dimensions and optional seed.
-
-    Args:
-        width: Width of the test image in pixels (default: 160)
-        height: Height of the test image in pixels (default: 120)
-        seed: Optional seed for reproducible image generation
-        img_format: Image format (default: PNG). Other formats like JPEG are
-            also supported.
-
-    Returns:
-        image bytes in specified format (default: PNG)
-
-    """
-    if seed is not None:
-        _rng.seed(seed)
-
-    return create_random_image(width, height, img_format)
-
-
-async def rate_limited_image_iter(
-    min_interval_ms: int,
-    max_images: int | None = None,
-) -> AsyncIterator[ImageData]:
-    """Generate images with a minimum interval between yields."""
-    last_yield_time = time.time()
-    async for image in iter_images(max_images):
-        elapsed_ms = (time.time() - last_yield_time) * 1000
-        if elapsed_ms < min_interval_ms:
-            await asyncio.sleep((min_interval_ms - elapsed_ms) / 1000)
-        yield image
-        last_yield_time = time.time()
-
-
-def create_random_image_generator(
-    max_images: int, rate_limit_min_interval_ms: int | None = None
-) -> AsyncIterator[ImageData]:
-    if rate_limit_min_interval_ms is not None:
-        return rate_limited_image_iter(rate_limit_min_interval_ms, max_images)
-
-    return iter_images(max_images)
diff --git a/uv.lock b/uv.lock
index 41531a2..58c071e 100644
--- a/uv.lock
+++ b/uv.lock
@@ -986,6 +986,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/e3/6690b3f85a05506733c7e90b577e4762517404ea78bab2ca3a5cb1aeb78d/numpy-2.3.2-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:6936aff90dda378c09bea075af0d9c675fe3a977a9d2402f95a87f440f59f619", size = 12977811, upload-time = "2025-07-24T21:29:18.234Z" },
 ]
 
+[[package]]
+name = "opencv-python-headless"
+version = "4.13.0.92"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" },
+    { name = "numpy", version = "2.3.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
+]
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/79/42/2310883be3b8826ac58c3f2787b9358a2d46923d61f88fedf930bc59c60c/opencv_python_headless-4.13.0.92-cp37-abi3-macosx_13_0_arm64.whl", hash = "sha256:1a7d040ac656c11b8c38677cc8cccdc149f98535089dbe5b081e80a4e5903209", size = 46247192, upload-time = "2026-02-05T07:01:35.187Z" },
+    { url = "https://files.pythonhosted.org/packages/2d/1e/6f9e38005a6f7f22af785df42a43139d0e20f169eb5787ce8be37ee7fcc9/opencv_python_headless-4.13.0.92-cp37-abi3-macosx_14_0_x86_64.whl", hash = "sha256:3e0a6f0a37994ec6ce5f59e936be21d5d6384a4556f2d2da9c2f9c5dc948394c", size = 32568914, upload-time = "2026-02-05T07:01:51.989Z" },
+    { url = "https://files.pythonhosted.org/packages/21/76/9417a6aef9def70e467a5bf560579f816148a4c658b7d525581b356eda9e/opencv_python_headless-4.13.0.92-cp37-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5c8cfc8e87ed452b5cecb9419473ee5560a989859fe1d10d1ce11ae87b09a2cb", size = 33703709, upload-time = "2026-02-05T10:24:46.469Z" },
+    { url = "https://files.pythonhosted.org/packages/92/ce/bd17ff5772938267fd49716e94ca24f616ff4cb1ff4c6be13085108037be/opencv_python_headless-4.13.0.92-cp37-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:0525a3d2c0b46c611e2130b5fdebc94cf404845d8fa64d2f3a3b679572a5bd22", size = 56016764, upload-time = "2026-02-05T10:26:48.904Z" },
+    { url = "https://files.pythonhosted.org/packages/8f/b4/b7bcbf7c874665825a8c8e1097e93ea25d1f1d210a3e20d4451d01da30aa/opencv_python_headless-4.13.0.92-cp37-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:eb60e36b237b1ebd40a912da5384b348df8ed534f6f644d8e0b4f103e272ba7d", size = 35010236, upload-time = "2026-02-05T10:28:11.031Z" },
+    { url = "https://files.pythonhosted.org/packages/4b/33/b5db29a6c00eb8f50708110d8d453747ca125c8b805bc437b289dbdcc057/opencv_python_headless-4.13.0.92-cp37-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:0bd48544f77c68b2941392fcdf9bcd2b9cdf00e98cb8c29b2455d194763cf99e", size = 60391106, upload-time = "2026-02-05T10:30:14.236Z" },
+    { url = "https://files.pythonhosted.org/packages/fb/c3/52cfea47cd33e53e8c0fbd6e7c800b457245c1fda7d61660b4ffe9596a7f/opencv_python_headless-4.13.0.92-cp37-abi3-win32.whl", hash = "sha256:a7cf08e5b191f4ebb530791acc0825a7986e0d0dee2a3c491184bd8599848a4b", size = 30812232, upload-time = "2026-02-05T07:02:29.594Z" },
+    { url = "https://files.pythonhosted.org/packages/4a/90/b338326131ccb2aaa3c2c85d00f41822c0050139a4bfe723cfd95455bd2d/opencv_python_headless-4.13.0.92-cp37-abi3-win_amd64.whl", hash = "sha256:77a82fe35ddcec0f62c15f2ba8a12ecc2ed4207c17b0902c7a3151ae29f37fb6", size = 40070414, upload-time = "2026-02-05T07:02:26.448Z" },
+]
+
 [[package]]
 name = "packaging"
 version = "25.0"
@@ -995,104 +1014,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/20/12/38679034af332785aac8774540895e234f4d07f7545804097de4b666afd8/packaging-25.0-py3-none-any.whl", hash = "sha256:29572ef2b1f17581046b3a2227d5c611fb25ec70ca1ba8554b24b0e69331a484", size = 66469, upload-time = "2025-04-19T11:48:57.875Z" },
 ]
 
-[[package]]
-name = "pillow"
-version = "12.0.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/5a/b0/cace85a1b0c9775a9f8f5d5423c8261c858760e2466c79b2dd184638b056/pillow-12.0.0.tar.gz", hash = "sha256:87d4f8125c9988bfbed67af47dd7a953e2fc7b0cc1e7800ec6d2080d490bb353", size = 47008828, upload-time = "2025-10-15T18:24:14.008Z" }
-wheels = [
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 name = "platformdirs"
 version = "4.5.0"
@@ -1296,7 +1217,7 @@ dependencies = [
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-    { name = "pillow" },
+    { name = "opencv-python-headless" },
 ]
 
 [package.dev-dependencies]
@@ -1330,7 +1251,7 @@ requires-dist = [
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     { name = "httpx", specifier = ">=0.25.0" },
     { name = "numpy", specifier = ">=2.2.6" },
-    { name = "pillow", specifier = ">=11.3.0" },
+    { name = "opencv-python-headless", specifier = ">=4.13.0.92" },
 ]
 
 [package.metadata.requires-dev]