feat(perception): sample OCR text foreground/background colors

PaddleOCR itself returns no color info, only text/bounds/confidence.
Add pixel-level post-processing in perception/ocr.py: crop the
screenshot to each OCR box, split pixels into two luminance clusters
via Otsu threshold, and treat the minority cluster as the text stroke
(foreground) and the majority as the background. New
SceneElement.foreground_color/background_color fields ("#rrggbb",
None when not OCR-sourced or sampling fails) round-trip through
to_dict/from_dict alongside the existing accessibility-state fields.
Planner system prompt documents the new fields as a secondary signal.

pillow is promoted from an implicit paddleocr transitive dependency to
an explicit direct dependency since perception/ocr.py now imports PIL
directly; uv.lock re-resolved with no version change (already locked
at 12.3.0).

runtime/planner_prompts.py

@@ -19,6 +19,14 @@ interacted with (do not tap it); `selected`/`checked`/`focused` describe its
 current toggle/focus state and are useful for deciding whether an action is
 already done or still needed.
 
+Text elements sourced from OCR may also carry `foreground_color` and
+`background_color` ("#rrggbb", sampled from the screenshot pixels under that
+text). These are omitted when the element is not OCR-sourced or sampling
+failed — omitted does NOT mean "no color", treat it as unknown. Use them only
+as a secondary signal (e.g. to tell an active/highlighted item apart from an
+inactive one with the same text) and prefer bounds/text/screenshot evidence
+when they disagree.
+
 Before calling a tool, output a short text block (1-2 sentences):
 1. If this is the first step, state what you intend to do and why.
 2. Otherwise, first assess whether the previous action achieved its intended