photo-enhance: adaptive pipeline with conditional ESRGAN and blended scene grading

Addresses all five priority improvements from photo-enhance-review.md:

1. Conditional ESRGAN (ConditionalESRGANBlend node): portrait and night
   scenes skip Real-ESRGAN entirely; indoor/golden_hour use a reduced
   blend (0.25–0.60); landscape/beach keep full strength. Confidence-
   weighted ratios from CLIP scores soften hard scene-boundary transitions.

2. Blended CLIP scene profiles: CLIPSceneDetect now outputs top-3 scene
   scores as a normalised JSON string. AdaptivePhotoGrade blends the
   matching grading profiles weighted by confidence instead of hard-
   switching on the argmax label — a 55/35/10 landscape/golden_hour/overcast
   split produces a weighted average of those three profiles.

3. Conservative depth defaults: DepthSelectiveSharpen background_blur
   changed from 0.50 to 0.0 (disabled by default). Foreground sharpening
   is kept; background blur can be re-enabled explicitly per shot.

4. EXIF/ICC preservation: copy_exif() in photo-enhance.rb uses exiftool
   to restore capture time, camera/lens info, GPS, and ICC profile from
   the source file onto the enhanced JPEG after ComfyUI strips metadata.
   Embedded thumbnail/preview are excluded to avoid showing the old image.

5. Provenance logging: prompt_id is now passed into the metadata markdown
   report. WritePhotoMetadata emits scene_scores and esrgan_mode into the
   JSON sidecar. The markdown report now shows top-3 scene confidences,
   ESRGAN mode, and ComfyUI prompt ID for reproducibility.

Workflow restructured: CLIPSceneDetect now runs on the original image
(before ESRGAN) so scene scores are available to gate the upscaler.
ConditionalESRGANBlend (node 16) inserted between ESRGAN downscale and
CodeFormer. All downstream nodes receive scene_scores via node 11 outputs.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

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