Add containerized OCR pipeline for fuel receipts

Self-hosted, verifiable pipeline for extracting structured data (station,
date/time, price per litre, litres, discount, total) from German fuel
receipt photos: grayscale + mild bilateral filter + contrast stretch,
Tesseract OCR, then LLM structuring via a small local model (Qwen 2.5,
served by Ollama). Each step is independently runnable and inspectable
through numbered scripts against a shared tooling container.

Ollama runs as its own long-lived container (0_run_ollama.sh), separate
from the stateless per-receipt pipeline steps, so the model stays loaded
in memory between runs. Includes a containerized ground-truth batch test
(test_batch.sh) that reproduces the full pipeline over the test receipts
and reports per-field accuracy.

Targets eventual deployment on a Raspberry Pi 4 k3s cluster.

.gitignore

@@ -0,0 +1,19 @@
+# Test receipt images / ground-truth spreadsheets (not checked in)
+/testdata/
+
+# Local registry credentials (see registry.env.example)
+/registry.env
+
+# Local Claude Code settings
+/.claude/settings.local.json
+
+# Generated pipeline output (see test_batch.sh, 1_preprocess_image.sh,
+# 2_ocr_image.sh, 3_extract_data.sh) - intermediate/result dirs are
+# created as siblings of whatever -in directory was processed
+*-scratch/
+*-result/
+
+# Python bytecode cache (picked up if src/ is ever imported on the host
+# instead of run through the container)
+__pycache__/
+*.pyc