GPU-accelerated phash + fix discovery/takeout hang

GPU:
- Switch Dockerfile base to pytorch/pytorch:2.3.1-cuda12.1-cudnn8-runtime
- Add gpu_hasher.py: batched 2D DCT on GPU via PyTorch matrix multiply,
  256 images/batch, produces imagehash-compatible 64-bit hex hashes,
  auto-falls back to CPU when CUDA unavailable
- Replace per-image phash loop in scanner.py with phasher.hash_files()
- docker-compose.yml: add nvidia GPU device reservation

Hang fix:
- takeout.is_takeout_folder() now caps at 50 directories (was walking
  entire tree — blocked for minutes on 65k+ file libraries)
- Add "Not a Takeout folder" status message so takeout phase is never silent

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

Dockerfile

@@ -1,7 +1,9 @@
-FROM python:3.12-slim
+# PyTorch + CUDA 12.1 base — matches Ubuntu 22.04 with NVIDIA driver 525+
+FROM pytorch/pytorch:2.3.1-cuda12.1-cudnn8-runtime
 
 RUN apt-get update && apt-get install -y \
-    libheif-dev libjpeg-dev libpng-dev libtiff-dev libwebp-dev exiftool \
+    libheif-dev libjpeg-dev libpng-dev libtiff-dev libwebp-dev \
+    libgl1 libglib2.0-0 exiftool ffmpeg \
     && rm -rf /var/lib/apt/lists/*
 
 WORKDIR /app