feat: reduce build size — replace Pillow with cv2, refactor build scripts

- Create utils/image_codec.py with cv2-based image helpers
- Replace PIL usage across all routes, filters, and engines with cv2
- Move Pillow from core deps to [tray] optional in pyproject.toml
- Extract shared build logic into build-common.sh (detect_version, cleanup, etc.)
- Strip unused NumPy/PIL/zeroconf/debug files in build scripts

server/src/wled_controller/utils/image_codec.py

@@ -0,0 +1,91 @@
+"""Image encoding/decoding/resizing utilities using OpenCV.
+
+Replaces PIL/Pillow for JPEG encoding, image loading, and resizing operations.
+All functions work with numpy RGB arrays (H, W, 3) uint8.
+"""
+
+import base64
+from pathlib import Path
+from typing import Tuple, Union
+
+import cv2
+import numpy as np
+
+
+def encode_jpeg(image: np.ndarray, quality: int = 85) -> bytes:
+    """Encode an RGB numpy array as JPEG bytes."""
+    bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    ok, buf = cv2.imencode(".jpg", bgr, [cv2.IMWRITE_JPEG_QUALITY, quality])
+    if not ok:
+        raise RuntimeError("JPEG encoding failed")
+    return buf.tobytes()
+
+
+def encode_jpeg_data_uri(image: np.ndarray, quality: int = 85) -> str:
+    """Encode an RGB numpy array as a JPEG base64 data URI."""
+    raw = encode_jpeg(image, quality)
+    b64 = base64.b64encode(raw).decode("utf-8")
+    return f"data:image/jpeg;base64,{b64}"
+
+
+def resize_image(image: np.ndarray, width: int, height: int) -> np.ndarray:
+    """Resize an image to exact dimensions.
+
+    Uses INTER_AREA for downscaling (better quality, faster) and
+    INTER_LANCZOS4 for upscaling.
+    """
+    h, w = image.shape[:2]
+    shrinking = (width * height) < (w * h)
+    interp = cv2.INTER_AREA if shrinking else cv2.INTER_LANCZOS4
+    return cv2.resize(image, (width, height), interpolation=interp)
+
+
+def thumbnail(image: np.ndarray, max_width: int) -> np.ndarray:
+    """Create a thumbnail that fits within max_width, preserving aspect ratio.
+
+    Uses INTER_AREA (optimal for downscaling).
+    """
+    h, w = image.shape[:2]
+    if w <= max_width:
+        return image.copy()
+    scale = max_width / w
+    new_w = max_width
+    new_h = max(1, int(h * scale))
+    return cv2.resize(image, (new_w, new_h), interpolation=cv2.INTER_AREA)
+
+
+def resize_down(image: np.ndarray, max_width: int) -> np.ndarray:
+    """Downscale if wider than max_width; return as-is otherwise.
+
+    Uses INTER_AREA (optimal for downscaling).
+    """
+    h, w = image.shape[:2]
+    if w <= max_width:
+        return image
+    scale = max_width / w
+    new_w = max_width
+    new_h = max(1, int(h * scale))
+    return cv2.resize(image, (new_w, new_h), interpolation=cv2.INTER_AREA)
+
+
+def load_image_file(path: Union[str, Path]) -> np.ndarray:
+    """Load an image file and return as RGB numpy array."""
+    path = str(path)
+    bgr = cv2.imread(path, cv2.IMREAD_COLOR)
+    if bgr is None:
+        raise FileNotFoundError(f"Cannot load image: {path}")
+    return cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
+
+
+def load_image_bytes(data: bytes) -> np.ndarray:
+    """Decode image bytes (JPEG, PNG, etc.) and return as RGB numpy array."""
+    arr = np.frombuffer(data, dtype=np.uint8)
+    bgr = cv2.imdecode(arr, cv2.IMREAD_COLOR)
+    if bgr is None:
+        raise ValueError("Cannot decode image data")
+    return cv2.cvtColor(bgr, cv2.COLOR_BGR2RGB)
+
+
+def image_size(image: np.ndarray) -> Tuple[int, int]:
+    """Return (width, height) of an image array."""
+    return image.shape[1], image.shape[0]