diff --git a/FAQ.md b/FAQ.md
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+# 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. Replace the example paths with whatever absolute 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.
diff --git a/Home.md b/Home.md
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--- a/Home.md
+++ b/Home.md
@@ -1 +1,18 @@
-Welcome to the winnow wiki!
+# winnow
+
+winnow pulls photos from [Immich](https://immich.app), selects diverse high-quality subsets using AI embeddings, and uploads them as face recognition training data to [Frigate](https://frigate.video).
+
+It runs fully headless in Docker, is configured entirely through environment variables, and can run on a schedule.
+
+## Pages
+
+- [[Setup]] — installation, Docker Compose configuration, GPU passthrough, environment variables
+- [[Troubleshooting]] — common failures and fixes
+- [[FAQ]] — frequently asked questions
+
+## Quick Links
+
+- [GitHub Repository](https://github.com/sudolulo/winnow)
+- [CHANGELOG](https://github.com/sudolulo/winnow/blob/main/CHANGELOG.md)
+- [compose.yml](https://github.com/sudolulo/winnow/blob/main/compose.yml)
+- [.env.example](https://github.com/sudolulo/winnow/blob/main/.env.example)
diff --git a/Setup.md b/Setup.md
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+# Setup Guide
+
+## Prerequisites
+
+- [Immich](https://immich.app) v1.106+ with face recognition enabled and people tagged
+- [Frigate](https://frigate.video) v0.16+ (face mode only)
+- Docker with the NVIDIA container toolkit (optional but strongly recommended)
+
+---
+
+## 1. Get your Immich API key
+
+1. Open Immich → **Account Settings** → **API Keys**
+2. Click **New API Key**, give it a name (e.g. `winnow`), copy the key
+
+---
+
+## 2. Get your Frigate URL
+
+This is the base URL of your Frigate instance, e.g. `http://192.168.1.10:5000`. Only needed for face mode — omit it entirely if you're using object mode.
+
+---
+
+## 3. Deploy with Docker Compose
+
+Copy [`compose.yml`](../compose.yml) and [`.env.example`](../.env.example) to a directory on your host:
+
+```bash
+mkdir winnow && cd winnow
+curl -O https://raw.githubusercontent.com/sudolulo/winnow/main/compose.yml
+curl -O https://raw.githubusercontent.com/sudolulo/winnow/main/.env.example
+cp .env.example .env
+```
+
+Edit `.env` with your values:
+
+```bash
+IMMICH_URL=http://192.168.1.10:2283
+API_KEY=your-immich-api-key
+FRIGATE_URL=http://192.168.1.10:5000
+```
+
+Edit the volume paths in `compose.yml` to point to directories on your host where models, cache, and output crops should be stored:
+
+```yaml
+volumes:
+  - /your/path/to/models:/models
+  - /your/path/to/cache:/app/.if_cache
+  - /your/path/to/output:/app/frigate_train
+```
+
+These directories will be created automatically by Docker if they don't exist.
+
+Start it:
+
+```bash
+docker compose up -d
+```
+
+Logs:
+
+```bash
+docker compose logs -f winnow
+```
+
+---
+
+## 4. First run
+
+On the first run, winnow downloads the embedding models (~1–2 GB) from HuggingFace and InsightFace. This happens once — subsequent runs use the cached models from your mounted volume and start immediately.
+
+---
+
+## 5. Scheduling
+
+Set `CRON_SCHEDULE` in your `.env` to keep winnow running on a schedule:
+
+```
+CRON_SCHEDULE=0 3 * * 0   # Every Sunday at 3 AM
+```
+
+Without `CRON_SCHEDULE`, the container runs once and exits.
+
+---
+
+## GPU passthrough
+
+To enable GPU acceleration, include the `deploy` block in `compose.yml` (already present in the example) and ensure the NVIDIA container toolkit is installed on your host:
+
+```bash
+# Verify GPU is accessible to Docker
+docker run --rm --gpus all nvidia/cuda:12.9.2-base-ubuntu22.04 nvidia-smi
+```
+
+CPU mode works without any GPU setup — set `FORCE_CPU=true` to disable GPU explicitly.
diff --git a/Troubleshooting.md b/Troubleshooting.md
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+# Troubleshooting
+
+## Container exits immediately
+
+Check logs:
+```bash
+docker compose logs winnow
+```
+
+Common causes:
+- **Missing required env var** — `IMMICH_URL` or `API_KEY` not set
+- **Cannot reach Immich** — check the URL and that Immich is running; use `http://` not `https://` unless you have TLS set up
+
+---
+
+## "No people found" / nothing processed
+
+- Make sure Immich has completed face recognition and you have named people in your library
+- `YEARS_FILTER` defaults to 10 years — increase it if your tagged photos are older
+- `MIN_FACE_COUNT` skips people with few photos — lower or remove it
+
+---
+
+## Frigate upload fails
+
+- Confirm `FRIGATE_URL` is reachable from inside the container: `docker exec winnow curl $FRIGATE_URL/api/stats`
+- Check Frigate v0.16+ — older versions don't have the face training API
+- Set `DRY_RUN=true` to verify selection without uploading
+
+---
+
+## Models fail to download
+
+winnow downloads InsightFace and HuggingFace (SigLIP) models on first run.
+
+- Ensure the container has internet access
+- Confirm the model volume is mounted and writable
+- If behind a proxy, set `HTTP_PROXY` / `HTTPS_PROXY` env vars
+
+---
+
+## Running on CPU (no GPU)
+
+Set `FORCE_CPU=true`. Everything works but embedding computation is slower — expect several minutes per person instead of seconds.
+
+If you have a GPU but it's not being used:
+- Confirm the NVIDIA container toolkit is installed: `docker run --rm --gpus all nvidia/cuda:12.9.2-base-ubuntu22.04 nvidia-smi`
+- Confirm the `deploy.resources.reservations.devices` block is present in `compose.yml`
+
+---
+
+## Same images uploaded every run
+
+The upload tracker is stored in `CACHE_DIR` (`/app/.if_cache` by default). If this volume isn't persisted between runs, the tracker resets and images are re-uploaded.
+
+Make sure `/app/.if_cache` is mounted to a persistent host path.
+
+---
+
+## Re-uploading a specific person
+
+To clear the upload history for one person and start fresh:
+
+```env
+RESET_PERSON=John
+```
+
+Remove this after one run — it clears the history and then processes normally.
+
+---
+
+## Image quality issues
+
+- **Too blurry**: Lower `BLUR_THRESHOLD` (default 100) — e.g. `50` accepts more blur
+- **Face too small**: Lower `MIN_FACE_WIDTH` (default 50px)
+- **Low confidence detections included**: Raise `MIN_CONFIDENCE` (default 0.7)
+- **Rejected images being re-tried**: Set `RETRY_REJECTED=true` for one run