docs: add wiki, .env.example, and fix stale if-curator references

- Add docs/setup.md, docs/troubleshooting.md, docs/faq.md as user-facing wiki
- Add .env.example with all env vars and inline comments
- Fix compose.override.yml: rename service if-curator → winnow, update volume paths
- Fix CHANGELOG.md: rename if-curator → winnow in release notes
- Link docs from README

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

docs/faq.md

@@ -0,0 +1,63 @@
+# FAQ
+
+## Does winnow modify my Immich library?
+
+No. winnow only reads from Immich (assets, people, face bounding boxes). It never writes back to Immich or deletes anything.
+
+---
+
+## How many images should I upload to Frigate?
+
+The `auto` strategy decides this for you — it keeps selecting until adding more images would be redundant. In practice this is usually 20–60 per person. You can cap it with `MAX_AUTO_IMAGES` (default 80).
+
+Quality and diversity matter far more than volume. 30 well-spread images outperform 200 from the same week.
+
+---
+
+## What's the difference between face mode and object mode?
+
+- **Face mode**: Extracts and aligns face crops, uploads them directly to Frigate's face training API. This is for teaching Frigate to recognize specific people.
+- **Object mode**: Runs YOLO detection on full images and saves crops of a target class (dog, cat, car, etc.) to disk. Frigate has no API for object training data, so you place them manually.
+
+---
+
+## Can I run it without Frigate?
+
+Yes — in object mode, `FRIGATE_URL` is not used and crops are saved to the output volume. In face mode you need Frigate to receive the uploads, but you can use `DRY_RUN=true` to preview selection without uploading.
+
+---
+
+## How does auto-diversity mode work?
+
+winnow computes a vector embedding for each candidate image (what the face/object actually looks like — angle, lighting, expression). It then clusters those embeddings and picks representatives that are maximally spread across the embedding space. It stops when the next-most-different image is already close to something already selected. See the README for the full pipeline.
+
+---
+
+## Does it support multiple people in one run?
+
+Yes. By default it processes every named person in your Immich library. Use `ONLY_PEOPLE` to whitelist specific names or `SKIP_PEOPLE` to exclude them.
+
+---
+
+## What GPU is needed?
+
+Any NVIDIA GPU with CUDA 12.x support. The models (InsightFace Buffalo_L + SigLIP) fit comfortably in 4 GB VRAM. CPU mode works but is significantly slower.
+
+ARM builds (linux/arm64) use CPU-only — CUDA is not available on ARM.
+
+---
+
+## Does it work on Unraid / Proxmox / bare Docker?
+
+Yes — the `compose.yml` uses standard Docker volume mounts. The TrueNAS paths in the example (`/mnt/<pool>/...`) are just an example; replace them with whatever paths suit your setup.
+
+---
+
+## How do I update winnow?
+
+```bash
+docker compose pull
+docker compose up -d
+```
+
+The `latest` tag on GHCR tracks the `main` branch. Pinning to a version tag (e.g. `ghcr.io/sudolulo/winnow:v0.2.0`) is recommended for stability.