feat(red-eye-removal): SOTA red eye removal with MediaPipe Face Mesh + OpenCV LAB correction (#60)

Uses MediaPipe Face Mesh (refine_landmarks=True) for precise iris localization
and OpenCV LAB color space for accurate red-eye detection and luminance-preserving
correction. Zero new dependencies - leverages existing MediaPipe + OpenCV stack.

- Sensitivity slider (LAB 'a' channel threshold)
- Correction strength slider (pupil darkening factor)
- Output format selector (Original/PNG/JPEG/WebP)
- Before/after preview, progress stages, batch processing
- Pipeline support via Controls/Settings split

Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>

packages/shared/src/constants.ts

@@ -193,6 +193,14 @@ export const TOOLS: Tool[] = [
     icon: "Sparkles",
     route: "/noise-removal",
   },
+  {
+    id: "red-eye-removal",
+    name: "Red Eye Removal",
+    description: "AI-detect and fix red eye in flash photos",
+    category: "ai",
+    icon: "Eye",
+    route: "/red-eye-removal",
+  },
   // Watermark & Overlay
   {
     id: "watermark-text",
@@ -414,4 +422,5 @@ export const PYTHON_SIDECAR_TOOLS = [
   "ocr",
   "colorize",
   "noise-removal",
+  "red-eye-removal",
 ] as const;