Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
Set up the AutoMagicCalib microservice and UI from release containers: resolve an AMC checkout, authenticate to NGC, optionally download VGGT, configure Docker Compose, launch services, and verify readiness.
auto-magic-calib repo on disk. Step 0b resolves the current repo, DeepStream tools/auto-magic-calib, DEEPSTREAM_REPO_ROOT, or ~/auto-magic-calib; otherwise it asks before cloning https://github.com/NVIDIA-AI-IOT/auto-magic-calib.
NGC account with access to NVIDIA container registry
Docker runnable without sudo; verify with docker ps before continuing.
Instructions
Step 0: Verify Docker Runs Without sudo
docker ps
If it succeeds → continue.
If it fails with "permission denied" → the user is not in the docker group. Ask the user to run:
sudo usermod -aG docker $USER && newgrp docker
Then ask the user to confirm docker ps works before continuing.
Agent note: If docker ps cannot be run from within the agent sandbox, ask the user to confirm it works (e.g. "Can you confirm docker ps runs without sudo?") before proceeding.
Step 0b: Resolve Repo Checkout
The skill needs AMC repo assets (compose/, sample data, and models/). Resolve an existing checkout first; ask before cloning into ~/auto-magic-calib.
Agent note: never clone silently. Prefer initialized DeepStream tools/auto-magic-calib; do not clone over that submodule path. If it exists but is empty, ask the user to run git submodule update --init tools/auto-magic-calib. Honour an alternate AMC path if provided.
Step 0c: Install Python venv (New Systems Only)
On a fresh system, pip and python3-venv may not be available. Install them first:
Step 2: Download VGGT Model (If Not Already Present)
export REPO_ROOT=$(git rev-parse --show-toplevel)
cd"$REPO_ROOT"if [ -f "models/vggt/vggt_1B_commercial.pt" ]; thenecho"✓ VGGT model already present"elseecho"✗ VGGT model not found"echo"Options:"echo" 1. Continue without VGGT (AMC only - sufficient for most use cases)"echo" 2. Download VGGT model (~4.7GB, requires HuggingFace account)"fi
REPO_DIR="$(git rev-parse --show-toplevel 2>/dev/null || pwd)"cd"$REPO_DIR"# Find the HuggingFace CLI binary (named 'hf', not 'huggingface-cli')
HF_BIN="$(find "$REPO_DIR/venv" ~/venv/amc -name hf -type f 2>/dev/null | head -1)"
{ [ -z "$HF_BIN" ] || [ ! -x "$HF_BIN" ]; } && { echo"ERROR: hf binary not found or not executable; install the hf CLI (Step 0c) or set HF_BIN" >&2; exit 1; }
# Do NOT use --token on the command line (leaks via ps/argv). The HF CLI# reads HF_TOKEN from the environment automatically.
HF_TOKEN="<HF_TOKEN>""$HF_BIN" download facebook/VGGT-1B-Commercial \
--local-dir models/vggt/
# Verifyls -lh models/vggt/vggt_1B_commercial.pt
# Should show ~4.7GB file
Important: Download BEFORE setting chown 1000:1000 on the models directory — the current user needs write access during download. Set permissions in Step 4 after download completes.
Step 3: Configure Compose Environment Variables
The Compose environment file controls ports and paths. Update it before launching:
cd$REPO_ROOT/compose
# Find available backend port (8000-8009)for port in {8000..8009}; doif ! lsof -Pi :$port -sTCP:LISTEN -t >/dev/null 2>&1; then
MS_PORT=$portecho"Using backend port: $MS_PORT"breakfidone
[ -z "$MS_PORT" ] && { echo"ERROR: no free backend port in 8000-8009; free one or widen the range." >&2; exit 1; }
# Find available UI port (5000-5009)for port in {5000..5009}; doif ! lsof -Pi :$port -sTCP:LISTEN -t >/dev/null 2>&1; then
UI_PORT=$portecho"Using UI port: $UI_PORT"breakfidone
[ -z "$UI_PORT" ] && { echo"ERROR: no free UI port in 5000-5009; free one or widen the range." >&2; exit 1; }
# Get host IP
HOST_IP=$(hostname -I | awk '{print $1}')
echo"Host IP: $HOST_IP"# Preserve existing keys and restrict permissions on the Compose environment file.
COMPOSE_ENV_BASENAME="env"
ENV_FILE=".${COMPOSE_ENV_BASENAME}"if [ -f "$ENV_FILE" ]; then
BACKUP="${ENV_FILE}.bak.$(date +%s)"cp"$ENV_FILE""$BACKUP"chmod 600 "$BACKUP"fitouch"$ENV_FILE"chmod 600 "$ENV_FILE"set_env_key() {
local k="$1" v="$2"if grep -qE "^${k}=""$ENV_FILE"; then
sed -i "s|^${k}=.*|${k}=${v}|""$ENV_FILE"elseecho"${k}=${v}" >> "$ENV_FILE"fi
}
set_env_key AUTO_MAGIC_CALIB_MS_PORT "${MS_PORT}"
set_env_key AUTO_MAGIC_CALIB_UI_PORT "${UI_PORT}"
set_env_key PROJECT_DIR "../../projects"
set_env_key MODEL_DIR "../../models"
set_env_key HOST_IP "${HOST_IP}"# Keep timestamped Compose environment backups out of git.
GITIGNORE="$REPO_ROOT/.gitignore"touch"$GITIGNORE"
BACKUP_PATTERN="compose/${ENV_FILE}.bak.*"
grep -qxF "$BACKUP_PATTERN""$GITIGNORE" || echo"$BACKUP_PATTERN" >> "$GITIGNORE"echo"✓ Compose environment file updated"cat"$ENV_FILE"
Important: HOST_IP must be the machine's network IP (not localhost) so the UI container can reach the backend from a browser.
Optional: set VGGT_MODEL_PATH only if the VGGT model is mounted at a non-default container path; default is /tmp/vggt_model/vggt_1B_commercial.pt inside the MS container.
Optional for RTSP calibration: use skills/amc-run-rtsp-calibration/SKILL.md after launch. That skill verifies VIOS reachability and, when needed, relaunches the microservice with a temporary compose override that exports VIOS_BASE_URL without changing checked-in compose files.
Step 4: Set Directory Permissions
The containers run as UID/GID 1000. The projects and models directories must be owned by this UID for containers to read/write properly:
cd"$REPO_ROOT"# Create projects directory if it doesn't existmkdir -p projects
# Set ownership (required for containers to write calibration outputs).# Do this AFTER VGGT download is complete (current user needs write access during download).# Get explicit user confirmation before running sudo chown — it recursively changes# ownership of $REPO_ROOT/projects and $REPO_ROOT/models to UID/GID 1000.
[ -d projects ] && [ -d models ] || {
echo"ERROR: expected projects/ and models/ under $REPO_ROOT" >&2; exit 1;
}
echo"About to chown -R 1000:1000 on:"echo" $REPO_ROOT/projects"echo" $REPO_ROOT/models"echo"(required because containers run as UID 1000). Confirm before proceeding."sudochown 1000:1000 -R projects
sudochown 1000:1000 -R models
echo"✓ Permissions set"
Step 5: Launch Services
Before pulling, fail fast if the NGC key authenticated in Step 1 but cannot actually access a release image — otherwise docker compose up aborts partway with a 401/403 after some work is already done.
cd$REPO_ROOT/compose
# Fail-fast image-access check: confirm the NGC key can reach every release# image BEFORE pulling. `docker manifest inspect` checks registry access without# downloading layers, and the image list is read from the resolved compose so it# tracks the release tag automatically.
IMAGES=$(docker compose config --images | sort -u)
[ -z "$IMAGES" ] && { echo"ERROR: no images resolved from compose — check the Compose environment settings and chosen profile." >&2; exit 1; }
for img in$IMAGES; doecho"Checking access: $img"if ! docker manifest inspect "$img" >/dev/null 2>&1; thenecho"NGC login succeeded, but this key cannot access the required image:" >&2
echo" $img" >&2
echo"Provide an NGC key with access to this image's namespace, then re-run Step 1 (login) and retry." >&2
exit 1
fidone# Start all services (images pulled automatically on first run)
docker compose up -d
# Check containers are running
docker compose ps
The exact image tags change by release; read them from the active compose files instead of hardcoding a version.
Step 6: Verify Services Are Running
# Read ports from the Compose environment file.
COMPOSE_ENV_BASENAME="env"
COMPOSE_ENV_FILE="$REPO_ROOT/compose/.${COMPOSE_ENV_BASENAME}"
MS_PORT=$(grep AUTO_MAGIC_CALIB_MS_PORT "$COMPOSE_ENV_FILE" | cut -d= -f2)
UI_PORT=$(grep AUTO_MAGIC_CALIB_UI_PORT "$COMPOSE_ENV_FILE" | cut -d= -f2)
HOST_IP=$(grep HOST_IP "$COMPOSE_ENV_FILE" | cut -d= -f2)
# Wait for microservice readiness. Cold image pulls or first startup can need# extra time after `docker compose up -d` returns.
READY_URL="http://localhost:${MS_PORT}/v1/ready"echo"Waiting for microservice readiness at ${READY_URL} ..."
ready_response=""for attempt in $(seq 1 24); doif ready_response=$(curl -fsS --max-time 5 "${READY_URL}" 2>/dev/null) && \
echo"${ready_response}" | grep -q '"code"[[:space:]]*:[[:space:]]*0'; thenecho"Microservice ready: ${ready_response}"breakfiif [ "${attempt}" -lt 24 ]; thenprintf" [%02d/24] Microservice not ready yet; retrying in 5s...\n""${attempt}"sleep 5
fidoneif ! echo"${ready_response}" | grep -q '"code"[[:space:]]*:[[:space:]]*0'; thenecho"ERROR: microservice did not report ready within 120 seconds: ${READY_URL}" >&2
echo"Check status and logs:" >&2
echo" cd ${REPO_ROOT}/compose && docker compose ps" >&2
echo" cd ${REPO_ROOT}/compose && docker compose logs auto-magic-calib-ms" >&2
exit 1
fi# Check UI is serving
UI_STATUS=$(curl -s -o /dev/null -w "%{http_code}" --max-time 5 "http://localhost:${UI_PORT}")
if [ "${UI_STATUS}" != "200" ]; thenecho"ERROR: Web UI returned HTTP ${UI_STATUS}; check docker compose ps and UI logs." >&2
exit 1
fiecho"Web UI ready: HTTP ${UI_STATUS}"echo"Microservice: http://${HOST_IP}:${MS_PORT}"echo"Web UI: http://${HOST_IP}:${UI_PORT}"
Success Criteria
docker compose ps shows MS and UI containers Up; MS should be healthy.
/v1/ready returns code:0 and Step 6 prints the microservice and UI URLs.
Browser access to http://<HOST_IP>:<AUTO_MAGIC_CALIB_UI_PORT> works.
Projects persist under $REPO_ROOT/projects/.
Troubleshooting
Issue
Fix
Docker permission denied
Ask the user to run sudo usermod -aG docker $USER && newgrp docker, then retry docker ps.
docker login rejected
Ask for a current NGC key and log in again.
Required image inaccessible
The key lacks image namespace access; ask for a key with access, then retry Step 1 and Step 5.
python3 -m venv, pip, or hf missing
Install python3-venv/python3-pip; the HF binary is named hf.
VGGT permission error
Download VGGT before chown 1000:1000; to recover, restore user ownership of models/ and re-download.
Port in use
Pick a free MS port in 8000-8009 and UI port in 5000-5009, then update the Compose environment file.
Readiness timeout or exited container
Run cd $REPO_ROOT/compose && docker compose ps and inspect docker compose logs auto-magic-calib-ms.
Project/model permission denied
Re-run Step 4 for projects/ or models/ only.
UI cannot reach backend
Verify HOST_IP in the Compose environment file is the machine network IP, not localhost.
GPU unavailable
Verify NVIDIA runtime with docker run --rm --runtime=nvidia --gpus all ubuntu:20.04 nvidia-smi.
Common Fixes:
cd$REPO_ROOT/compose
# View logs
docker compose logs -f
# View logs for specific service
docker compose logs -f auto-magic-calib-ms
# Restart all services
docker compose restart
# Stop and remove containers
docker compose down
# Update Compose environment settings and relaunch
docker compose up -d
Stopping the Services
cd$REPO_ROOT/compose
# Stop all services (containers removed, data persisted)
docker compose down
# Stop and remove volumes
docker compose down -v
Related Skills
skills/amc-run-sample-calibration/SKILL.md - Sanity-check the running stack with the bundled sample dataset
skills/amc-run-video-calibration/SKILL.md - Calibrate from your own pre-recorded MP4s via REST API
skills/amc-run-rtsp-calibration/SKILL.md - Calibrate from live RTSP streams through VIOS capture
