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.

tooling-container/Dockerfile

@@ -0,0 +1,20 @@
+FROM python:3.12-slim
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        tesseract-ocr \
+        tesseract-ocr-deu \
+    && rm -rf /var/lib/apt/lists/*
+
+RUN pip install --no-cache-dir \
+        opencv-python-headless==4.10.0.84 \
+        numpy==2.1.3 \
+        pillow==11.0.0 \
+        pytesseract==0.3.13 \
+        requests==2.32.3 \
+        odfpy==1.4.1
+
+COPY src/ /opt/app/src/
+RUN chmod -R a+rX /opt/app/src
+
+WORKDIR /data
+ENTRYPOINT []