Files
ubuntu-post-install/services/iopaint.sh
T
Claude bec9228c55 Back up existing files before every service overwrites them
Confirmed live: install_frigate()'s fresh-install path overwrote a
working, hand-crafted docker-compose.yml (Frigate + mosquitto +
frigate-notify) with zero backup, because that file's shape didn't match
what frigate.sh's own "existing install" detection knew how to recognize.
Every service's own detection is a judgment call about what counts as
"already installed" and can miss a real setup built outside this repo's
conventions.

lib/common.sh gains backup_if_exists(FILE) — copies FILE to
FILE.bak.<timestamp> if it exists, no-ops otherwise (including DRY_RUN).
Applied before every service's own `cat > docker-compose.yml`/`cat > .env`
write across all 60 services that do one (115 call sites), plus a matching
standalone-mode stub added to every service's own bootstrap block, same
convention already used for port_in_use/find_free_port. This doesn't
replace a service's own update/fresh-reinstall detection — it's the safety
net underneath it, so a wrong detection costs a .bak file to restore from
instead of the original silently disappearing.

Also fixes the actual gap that surfaced this: services/frigate.sh's
Authelia offer only checked for Authelia installed locally on Frigate's
own box, which is never true for a dedicated NVR box with no local Caddy
either (the common shape — Caddy lives elsewhere, snippet-generation mode
already handles that). Now offers Authelia protection unconditionally and,
when Authelia isn't local, asks whether it lives on the same machine as
Caddy (still "import authelia", since that's local to wherever Caddy ends
up) or on a genuinely separate third machine (the explicit
header-pinned forward_auth form, per CLAUDE.md's "forward_auth to a remote
Authelia" note, needed because a bare authelia:9091 shortcut only works
one hop).
2026-08-26 17:26:17 +00:00

523 lines
21 KiB
Bash

#!/bin/bash
# services/iopaint.sh — AI image editing: erase objects, fill regions, replace with text prompt.
# Part of the modular post-install system (sourced by setup.sh).
#
# Can also be run standalone on any machine:
# sudo bash iopaint.sh
# (Docker must already be installed when run standalone)
#
# Three use cases:
# Erase/remove — mask an object, AI fills the gap (LaMa, CPU-safe)
# Inpaint/fill — restore damaged areas, remove watermarks (multiple models)
# Replace — mask + text prompt → AI draws new content (PowerPaint, GPU required)
#
# IOPaint is local-only: it cannot call a remote GPU or InvokeAI on another machine.
# For text-guided replacement the GPU must be on this same machine.
# IOPaint has no built-in auth — protect with Authelia via Caddy.
# ── Standalone bootstrap ──────────────────────────────────────────────────────
if [[ "${BASH_SOURCE[0]}" == "${0}" ]]; then
[[ "$(id -u)" == "0" ]] || { echo "Run with sudo: sudo bash $0"; exit 1; }
_SELF_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
_COMMON="$_SELF_DIR/../lib/common.sh"
if [[ -f "$_COMMON" ]]; then
source "$_COMMON"
else
log_info() { echo -e "\033[0;34m[INFO]\033[0m $*"; }
log_success() { echo -e "\033[0;32m[OK]\033[0m $*"; }
log_warning() { echo -e "\033[1;33m[WARN]\033[0m $*"; }
log_error() { echo -e "\033[0;31m[ERROR]\033[0m $*" >&2; }
require_docker() {
command -v docker &>/dev/null || {
log_error "Docker not found. Install it first:"
log_error " curl -fsSL https://get.docker.com | sudo sh"
return 1
}
docker compose version &>/dev/null || {
log_error "Docker Compose plugin missing:"
log_error " sudo apt-get install -y docker-compose-plugin"
return 1
}
}
ensure_docker_dir_ownership() {
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$@" 2>/dev/null || true
}
port_in_use() {
local _port="$1" _proto="${2:-tcp}"
local _flag="-tlnH"
[ "$_proto" = "udp" ] && _flag="-ulnH"
ss "$_flag" "sport = :${_port}" 2>/dev/null | grep -q .
}
find_free_port() {
local _varname="$1" _port="$2" _proto="${3:-tcp}"
while port_in_use "$_port" "$_proto"; do
_port=$((_port + 1))
done
eval "$_varname='$_port'"
}
prompt_text() {
local _q="$1" _def="$2" _var="$3" _r
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
read -r -p " $_q " _r
eval "$_var='${_r:-$_def}'"
}
prompt_yn() {
local _q="$1" _def="$2" _var="$3" _r
[[ "${UNATTENDED:-false}" == "true" ]] && { eval "$_var='$_def'"; return; }
read -r -p " $_q " _r
eval "$_var='${_r:-$_def}'"
}
configure_caddy_for_service() {
local _name="$1" _upstream="$2" _subdomain="$3" _extra="${4:-}"
local _caddy_dir="$DOCKER_DIR/caddy"
local _caddyfile="$_caddy_dir/Caddyfile"
local _display_port="${_upstream##*:}"
local _mode="none"
[[ -d "$_caddy_dir" ]] && _mode="local"
[[ -n "${CADDY_REMOTE_HOST:-}" ]] && [[ "$_mode" != "local" ]] && _mode="remote"
[[ "$_mode" == "none" ]] && {
log_info "Access $_name directly on port $_display_port."
return 0
}
echo ""
local _do_caddy=""
if [[ "$_mode" == "remote" ]]; then
log_info "Remote Caddy configured (${CADDY_REMOTE_HOST})."
log_info "A snippet file will be saved to ~/docker/caddy-snippets/."
fi
read -r -p " Configure Caddy reverse proxy for $_name? [y/N]: " _do_caddy
[[ "${_do_caddy,,}" == "y" ]] || {
log_info "Skipping — access at: http://localhost:$_display_port"
return 0
}
local _default_domain=""
if [[ -n "${SITE_DOMAIN:-}" ]] && [[ "$SITE_DOMAIN" != "example.com" ]]; then
_default_domain="${_subdomain}.${SITE_DOMAIN}"
log_info "Default: $_default_domain"
fi
local _domain=""
read -r -p " Domain [${_default_domain:-required}]: " _domain
_domain="${_domain:-$_default_domain}"
[[ -n "$_domain" ]] || { log_warning "No domain entered — skipping Caddy."; return 0; }
local _block_upstream="$_upstream"
if [[ "$_mode" == "remote" ]]; then
_block_upstream="${CADDY_REMOTE_HOST}:${_display_port}"
fi
local _site_block
_site_block="$(cat << CBLOCK
# $_name
${_domain} {
reverse_proxy ${_block_upstream}
header {
Strict-Transport-Security "max-age=31536000; includeSubDomains; preload"
X-Content-Type-Options "nosniff"
X-Frame-Options "SAMEORIGIN"
Referrer-Policy "strict-origin-when-cross-origin"
}
log {
output file /var/log/caddy/${_domain}.log
format json
}
${_extra}
}
CBLOCK
)"
if [[ "$_mode" == "local" ]]; then
if [[ -f "$_caddyfile" ]]; then
local _bk="$_caddy_dir/Caddyfile.backup.$(date +%Y%m%d-%H%M%S)"
cp "$_caddyfile" "$_bk"
log_info "Backed up Caddyfile to $(basename "$_bk")"
else
touch "$_caddyfile"
fi
if grep -q "^${_domain}" "$_caddyfile" 2>/dev/null; then
log_warning "$_domain already in Caddyfile"
local _ow=""
read -r -p " Overwrite? [y/N]: " _ow
[[ "${_ow,,}" == "y" ]] || { log_info "Keeping existing entry."; return 0; }
sed -i "/^${_domain}/,/^}/d" "$_caddyfile"
fi
printf '%s\n' "$_site_block" >> "$_caddyfile"
log_success "Added $_domain to Caddyfile"
docker exec caddy caddy fmt --overwrite /etc/caddy/Caddyfile 2>/dev/null || true
if docker exec caddy caddy reload --config /etc/caddy/Caddyfile 2>/dev/null; then
log_success "$_name accessible at: https://$_domain"
else
log_warning "Reload failed — check: docker logs caddy"
log_info "Manual reload: docker exec caddy caddy reload --config /etc/caddy/Caddyfile"
fi
else
local _snippet_dir="$DOCKER_DIR/caddy-snippets"
local _snippet_file="$_snippet_dir/${_subdomain}.caddy"
mkdir -p "$_snippet_dir"
printf '%s\n' "$_site_block" > "$_snippet_file"
chown "$ACTUAL_USER:$ACTUAL_USER" "$_snippet_file" 2>/dev/null || true
log_success "Snippet saved: $_snippet_file"
log_info "Copy to Caddy machine:"
log_info " scp $_snippet_file caddy-host:~/caddy-snippets/"
log_info " rsync -av $_snippet_dir/ caddy-host:~/caddy-snippets/ (all at once)"
fi
}
write_readme() {
local _dir="$1"
mkdir -p "$_dir"
[[ "${DRY_RUN:-false}" == "true" ]] && return 0
cat > "$_dir/README.md"
}
backup_if_exists() {
local _file="$1"
[ -f "$_file" ] || return 0
cp -p "$_file" "${_file}.bak.$(date +%Y%m%d-%H%M%S)" 2>/dev/null
}
fi
ACTUAL_USER="${ACTUAL_USER:-${SUDO_USER:-$USER}}"
ACTUAL_HOME="$(getent passwd "$ACTUAL_USER" 2>/dev/null | cut -d: -f6 || echo "${HOME:-/root}")"
DOCKER_DIR="${DOCKER_DIR:-$ACTUAL_HOME/docker}"
DRY_RUN="${DRY_RUN:-false}"
UNATTENDED="${UNATTENDED:-false}"
SITE_TZ="${SITE_TZ:-$(cat /etc/timezone 2>/dev/null || echo UTC)}"
SITE_DOMAIN="${SITE_DOMAIN:-example.com}"
SITE_CADDY_NET="${SITE_CADDY_NET:-caddy_net}"
CADDY_REMOTE_HOST="${CADDY_REMOTE_HOST:-}"
register_service() { :; }
_RUN_STANDALONE=1
fi
# ─────────────────────────────────────────────────────────────────────────────
register_service iopaint utilities "AI image inpainting — erase objects, fill, restore (IOPaint)" 8100
install_iopaint() {
require_docker || return 1
log_info "Installing IOPaint..."
local IOPAINT_DIR="$DOCKER_DIR/iopaint"
local WEB_PORT="8100"
if [ "$DRY_RUN" = true ]; then
echo "[DRY-RUN] Would create $IOPAINT_DIR"
echo "[DRY-RUN] Would prompt for model and GPU (CUDA) support"
echo "[DRY-RUN] Would write docker-compose.yml and .env"
echo "[DRY-RUN] Would auto-scan for a free host port"
echo "[DRY-RUN] Would offer Authelia SSO"
return 0
fi
# Scan for a free host port — a plain install shouldn't silently claim a
# port another already-running service holds. See CLAUDE.md's "Port
# collision avoidance" section.
find_free_port WEB_PORT "$WEB_PORT"
mkdir -p "$IOPAINT_DIR"
ensure_docker_dir_ownership "$IOPAINT_DIR"
cd "$IOPAINT_DIR" || return 1
# ── GPU ──────────────────────────────────────────────────────────────────
log_info "IOPaint can:"
log_info " • Erase / remove — mask an object, AI fills the gap (works CPU-only)"
log_info " • Inpaint / fill — restore damaged areas, remove watermarks"
log_info " • Replace — mask + type what goes there → AI draws it (needs GPU)"
log_info " Note: inference is always local — IOPaint cannot use a GPU on another machine."
echo ""
local USE_GPU=""
prompt_yn "Enable CUDA GPU support? Requires nvidia-container-toolkit (y/n):" "n" USE_GPU
# ── Model selection ───────────────────────────────────────────────────────
echo ""
log_info "Select default model (you can switch models in the UI without restarting):"
echo ""
log_info " ── CPU-safe — work on any machine ─────────────────────────────────────────"
log_info " 1) lama Erase / removal. Intelligent gap fill. ~200 MB ← Recommended"
log_info " 2) cv2 OpenCV fill. No download, instant. Rough quality."
log_info " 3) zits Portrait & face restoration. ~200 MB."
log_info " 4) manga Comic/manga text bubble removal. ~100 MB."
echo ""
if [[ "$USE_GPU" =~ ^[Yy]$ ]]; then
log_info " ── GPU-accelerated fill ───────────────────────────────────────────────────"
log_info " 5) migan MiGAN: fast GPU inpainting. ~50 MB."
log_info " 6) fcf FcF: high-quality contextual fill. ~600 MB."
log_info " 7) mat MAT: large missing region fill. ~300 MB."
log_info " 8) ldm LDM: latent diffusion texture fill. ~1.2 GB."
echo ""
log_info " ── Text-guided REPLACEMENT (GPU + Stable Diffusion) ───────────────────────"
log_info " 9) Sanster/PowerPaint-V2-filling"
log_info " Mask + type 'a red barn' → AI draws it. ~4 GB."
log_info " Modes: text-guided, shape-guided, erase, outpaint."
log_info " 10) runwayml/stable-diffusion-inpainting"
log_info " Classic SD 1.5 inpaint. Huge LoRA/style library. ~4 GB."
echo ""
fi
local MODEL_NUM=""
prompt_text "Model choice [1=lama]:" "1" MODEL_NUM
local IOPAINT_MODEL="lama"
case "$MODEL_NUM" in
2) IOPAINT_MODEL="cv2" ;;
3) IOPAINT_MODEL="zits" ;;
4) IOPAINT_MODEL="manga" ;;
5) IOPAINT_MODEL="migan" ;;
6) IOPAINT_MODEL="fcf" ;;
7) IOPAINT_MODEL="mat" ;;
8) IOPAINT_MODEL="ldm" ;;
9) IOPAINT_MODEL="Sanster/PowerPaint-V2-filling" ;;
10) IOPAINT_MODEL="runwayml/stable-diffusion-inpainting" ;;
*) IOPAINT_MODEL="lama" ;;
esac
local DEVICE_VAL="cpu"
[[ "$USE_GPU" =~ ^[Yy]$ ]] && DEVICE_VAL="cuda"
# ── docker-compose.yml ────────────────────────────────────────────────────
# MODEL and DEVICE come from .env — change them there and restart to switch.
# Volume ./models:/root/.cache persists ALL model caches:
# /root/.cache/torch/hub/checkpoints/ (LaMa, CV2, ZITS, etc.)
# /root/.cache/huggingface/ (SD, PowerPaint, LDM, etc.)
# Mirrors configure_caddy_for_service's own mode resolution (lib/common.sh):
# explicit CADDY_MODE from the site config wins, then a local ~/docker/caddy,
# then the legacy CADDY_REMOTE_HOST var. Only "local" joins caddy_net — a
# remote Caddy box can't resolve container names on this host's bridge
# network anyway; it reaches this service via the host's published port.
local _CADDY_MODE="${CADDY_MODE:-none}"
[ "$_CADDY_MODE" = "none" ] && [ -d "$DOCKER_DIR/caddy" ] && _CADDY_MODE="local"
[ "$_CADDY_MODE" = "none" ] && [ -n "${CADDY_REMOTE_HOST:-}" ] && _CADDY_MODE="remote"
local _CADDY_NET_BLOCK=""
local _CADDY_NET_SECTION=""
if [ "$_CADDY_MODE" = "local" ]; then
_CADDY_NET_BLOCK=" networks:
- caddy_net
"
_CADDY_NET_SECTION="
networks:
caddy_net:
external: true
name: ${SITE_CADDY_NET:-caddy_net}
"
fi
if [[ "$USE_GPU" =~ ^[Yy]$ ]]; then
backup_if_exists docker-compose.yml
cat > docker-compose.yml << IOPAINT_GPU
name: iopaint
services:
iopaint:
image: cwq1913/iopaint:latest
container_name: iopaint
hostname: iopaint
restart: unless-stopped
command: >-
iopaint start
--model=\${MODEL:-lama}
--device=\${DEVICE:-cuda}
--port=8080
--host=0.0.0.0
ports:
- "${WEB_PORT}:8080"
env_file: .env
volumes:
- ./models:/root/.cache
- ./input:/app/input
- ./output:/app/output
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
${_CADDY_NET_BLOCK}${_CADDY_NET_SECTION}
IOPAINT_GPU
else
backup_if_exists docker-compose.yml
cat > docker-compose.yml << IOPAINT_CPU
name: iopaint
services:
iopaint:
image: cwq1913/iopaint:latest
container_name: iopaint
hostname: iopaint
restart: unless-stopped
command: >-
iopaint start
--model=\${MODEL:-lama}
--device=\${DEVICE:-cpu}
--port=8080
--host=0.0.0.0
ports:
- "${WEB_PORT}:8080"
env_file: .env
volumes:
- ./models:/root/.cache
- ./input:/app/input
- ./output:/app/output
${_CADDY_NET_BLOCK}${_CADDY_NET_SECTION}
IOPAINT_CPU
fi
# ── .env ─────────────────────────────────────────────────────────────────
backup_if_exists .env
cat > .env << IOPAINT_ENV
# IOPaint — change MODEL and restart to switch (no need to edit docker-compose.yml)
# Current model (set during install — see README for full model list)
MODEL=${IOPAINT_MODEL}
# Device: cpu or cuda
# For GPU: also requires the deploy: block in docker-compose.yml
DEVICE=${DEVICE_VAL}
# Caddy network
CADDY_NET=${SITE_CADDY_NET}
IOPAINT_ENV
chmod 600 .env
mkdir -p models input output
chown -R "$ACTUAL_USER:$ACTUAL_USER" "$IOPAINT_DIR"
echo ""
log_success "IOPaint configured — model: $IOPAINT_MODEL | device: $DEVICE_VAL"
if [[ "$IOPAINT_MODEL" == *"PowerPaint"* ]] || [[ "$IOPAINT_MODEL" == *"stable-diffusion"* ]]; then
log_info "SD-based model selected (~4 GB). It downloads from HuggingFace on first start."
log_info "If the download fails, try: HF_TOKEN=your_token docker compose up -d"
else
log_info "Model downloads automatically on first start (LaMa ~200 MB)."
fi
log_info "Switch models any time by editing MODEL= in .env and restarting."
# No built-in auth — offer Authelia SSO protection
local EXTRA_BLOCK=""
if [ -d "$DOCKER_DIR/authelia" ]; then
local _use_auth=""
prompt_yn "Protect IOPaint with Authelia SSO? (y/n):" "y" _use_auth
[[ "$_use_auth" =~ ^[Yy]$ ]] && EXTRA_BLOCK=" import authelia"
fi
configure_caddy_for_service "IOPaint" "iopaint:8080" "inpaint" "$EXTRA_BLOCK"
write_readme "$IOPAINT_DIR" << 'MD'
# IOPaint
AI-powered image editing:
- **Erase / remove** — mask an object, AI fills the background (LaMa, works CPU-only)
- **Inpaint / restore** — fix damaged areas, remove watermarks
- **Replace with AI** — mask something + type what goes there → AI draws it (PowerPaint, GPU)
Note: IOPaint is **local only** — all inference runs on this machine.
For text-guided replacement a CUDA GPU on this machine is required.
## Access
- URL: http://localhost:8100
- No built-in login — protect via Authelia SSO if exposed
## Switching models
Edit `MODEL=` in `.env` and restart — no need to touch `docker-compose.yml`:
```bash
cd ~/docker/iopaint
nano .env # change MODEL= line
docker compose restart
```
## Model reference
| # | Model | Type | Size | Best for |
|---|-------|------|------|---------|
| 1 | `lama` | CPU-safe | ~200 MB | **Object erase/removal** (default) |
| 2 | `cv2` | CPU-safe | built-in | Basic fill, no download |
| 3 | `zits` | CPU-safe | ~200 MB | Portrait & face restoration |
| 4 | `manga` | CPU-safe | ~100 MB | Comic/manga text bubble removal |
| 5 | `migan` | GPU | ~50 MB | Fast GPU inpainting |
| 6 | `fcf` | GPU | ~600 MB | High-quality contextual fill |
| 7 | `mat` | GPU | ~300 MB | Large missing region fill |
| 8 | `ldm` | GPU | ~1.2 GB | Latent diffusion texture fill |
| 9 | `Sanster/PowerPaint-V2-filling` | GPU+SD | ~4 GB | **Text-guided replacement** |
| 10 | `runwayml/stable-diffusion-inpainting` | GPU+SD | ~4 GB | SD 1.5 inpaint, large LoRA library |
SD-based models (9, 10) download from HuggingFace on first start.
If a gated model needs a token: add `HF_TOKEN=xxx` to `.env`.
## How to use
1. Open http://localhost:8100
2. Upload an image (or drag & drop)
3. Paint a mask over the area to change
4. For erase models: click Run → gap fills automatically
5. For SD models (PowerPaint): type a text prompt → AI draws it into the masked area
## GPU acceleration
Requires `nvidia-container-toolkit`. The GPU compose adds a `deploy:` block.
Re-run the installer with GPU=y to regenerate docker-compose.yml, or manually add:
```yaml
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
```
Then change `DEVICE=cuda` in `.env` and restart.
## Manage
```bash
cd ~/docker/iopaint
docker compose up -d
docker compose down
docker compose logs -f
docker compose pull && docker compose down && docker compose up -d
```
## Files
- docker-compose.yml — stack (MODEL and DEVICE come from .env)
- .env — model and device config
- models/ — all cached model weights (torch + HuggingFace)
- input/, output/ — optional file staging
MD
# The README above is a quoted (non-interpolating) heredoc — dense with
# literal backticks for inline code spans, too risky to convert to an
# interpolating heredoc without escaping every one of them. Patch the
# port in afterward instead when it was scanned away from the default.
[ "$WEB_PORT" != "8100" ] && sed -i "s/localhost:8100/localhost:${WEB_PORT}/g" "$IOPAINT_DIR/README.md"
local START_IO=""
prompt_yn "Start IOPaint now? (y/n):" "y" START_IO
if [ "$START_IO" = "y" ] || [ "$START_IO" = "Y" ]; then
docker compose up -d \
&& log_success "IOPaint started — model downloads on first use" \
|| log_warning "Start failed — check: docker compose logs"
fi
echo ""
echo " URL: http://localhost:${WEB_PORT}"
echo " Model: $IOPAINT_MODEL"
echo " Device: $DEVICE_VAL"
echo " Switch: edit MODEL= in $IOPAINT_DIR/.env and restart"
echo ""
}
[[ "${_RUN_STANDALONE:-0}" == 1 ]] && install_iopaint