Amc Run Rtsp Calibration
NVIDIAOfficialCreated by Shubham AgrawalDistributed by NVIDIA
- Skill
- Workflow
- Software development
- Apache-2.0
- Medium risk
- Has scripts
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured workflow to calibrate camera systems using live RTSP streams. It integrates with the VIOS service to record video clips, which are then ingested into the AutoMagicCalib (AMC) microservice for processing. The workflow covers project creation, stream capture, data ingestion, configuration management, and the execution of the calibration pipeline. It includes robust error handling, polling mechanisms for long-running tasks, and support for optional VGGT refinement.
What it does
- Connects to VIOS to record live RTSP camera streams for a specified duration.
- Ingests recorded clips into an AutoMagicCalib project.
- Supports uploading custom calibration settings, alignment data, and layout files.
- Executes the calibration pipeline using either resnet or transformer detectors.
- Provides polling mechanisms to track capture, ingestion, and calibration progress.
- Offers optional post-calibration VGGT refinement.
When to use it
- When you need to calibrate camera systems using live RTSP network streams.
- When you have a running AMC microservice and a reachable VIOS instance.
- When you want to automate the end-to-end process from stream capture to calibration results.
- When you have specific calibration assets (settings, alignment, layout) to apply to a new scene.
Advantages
- Automates the transition from live stream capture to calibrated output.
- Provides a consistent, repeatable workflow for multi-camera calibration.
- Integrates directly with existing AMC and VIOS infrastructure.
- Supports flexible configuration through both API uploads and UI-based tuning.
Usage examples
- “Calibrate my live cameras using RTSP URLs rtsp://cam0/stream and rtsp://cam1/stream.”
- The agent will initiate the project creation, trigger the VIOS recording session, ingest the resulting clips, and guide you through the calibration process.
- “Run AMC calibration on my RTSP streams for 180 seconds.”
- The agent will configure the capture session with the specified duration and proceed with the automated ingestion and calibration workflow.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/nvidia/amc-run-rtsp-calibration/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip amc-run-rtsp-calibration.zip -d .agents/skills
Documentation by Shubham Agrawal
Skill: Calibrate from RTSP Streams
When to Use This Skill
Activate this skill when the user wants to calibrate from live RTSP camera streams. Typical prompts:
"calibrate RTSP streams" / "calibrate from live cameras"
"run AMC on RTSP"
The user provides one or more
rtsp://...URLs
VIOS records fixed-duration clips from each stream, the AMC microservice ingests those clips into a project, then the workflow follows the same verification, calibration, polling, and results path as pre-recorded MP4 calibration.
Do not use this skill for local MP4 files already on disk; route those requests to skills/amc-run-video-calibration/SKILL.md. Do not use it for the bundled sample dataset; route that to skills/amc-run-sample-calibration/SKILL.md.
Never reuse files from the bundled sample dataset, extracted sample zip, assets/, or previous projects for RTSP calibration unless the user explicitly provides those paths for this RTSP scene. Similar camera names, stream counts, or cam_00/cam_01 ordering are not evidence that sample alignment, layout, GT, or detector settings apply.
Prerequisites
[ ] AMC microservice and UI running (follow
skills/amc-setup-calibration-stack/SKILL.mdif needed).[ ] VIOS is running and reachable from the AMC microservice.
[ ]
VIOS_BASE_URLis configured in the AMC microservice environment before capture starts.[ ] RTSP URLs are reachable from the VIOS host.
[ ] Camera streams have enough moving people/objects for calibration; record at least 2-3 minutes when possible.
[ ] Python 3 with
requestsinstalled when using the bundled script.
Data Privacy
RTSP URLs may contain usernames, passwords, hostnames, or network topology. Do not print full RTSP URLs if credentials are embedded. This skill does not handle bearer credentials; if the VIOS deployment requires authentication, stop and hand the user to a manual admin-managed workflow instead of collecting or relaying secrets in chat, scripts, or logs.
What to Ask the User
Required
RTSP URLs, one per camera.
Camera names, one per stream. Use
cam_00,cam_01, ... if the user does not provide names.Recording duration in seconds. Minimum is
60; prefer120-180or more when the scene has sparse motion.Microservice URL, for example
http://<HOST_IP>:8000orhttp://<HOST_IP>:8000/v1.Project name.
Calibration asset source for this RTSP scene:
a local directory to scan, such as
/data/my_rtsp_calib/;explicit paths to settings, alignment, layout, and optional GT files; or
confirmation that the user will upload/tune settings and alignment in the AMC UI.
If the user does not provide a local asset source, stop and ask whether they want to provide a path or use UI upload. Give the UI link as http://<HOST_IP>:<AUTO_MAGIC_CALIB_UI_PORT>; the default UI port is 5000.
Auto-Detected or Asked
RTSP clips are recorded by VIOS, so there is no local videos directory to anchor file discovery. Only scan a directory the user explicitly provided for this RTSP scene. If the user provides a settings file path, use that file's directory as the scan directory. If the user provides a calibration asset directory, scan only that directory. Otherwise ask this question before planning uploads or calibration:
Do you have a local calibration asset directory or settings file for these RTSP streams, or should you upload/tune settings and alignment in the AMC UI at
http://<HOST_IP>:<AUTO_MAGIC_CALIB_UI_PORT>?
| File | Candidate filenames | UI fallback |
|---|---|---|
| Calibration settings | Explicit user path, or settings.json, config.json, or calibration_config.json in the user-provided asset directory | UI Step 3: Parameters |
| Alignment JSON | Explicit user path, or alignment_data.json in the user-provided asset directory/settings directory | UI Step 4: Alignment |
| Layout PNG | Explicit user path, or layout.png in the user-provided asset directory/settings directory | UI Step 4: Alignment |
| Ground truth zip | Optional explicit user path, or GT.zip/gt.zip in the user-provided asset directory | Omit metrics |
Posting the settings file replaces UI Step 3 and may pin detector or detector_type. If it pins resnet or transformer, pass that same detector to /calibrate. If no settings file pins a detector, ask the user which detector to use; do not silently default to resnet.
Optional
sensor_idper stream if the cameras are already registered in VIOS. Leave unset for auto-registration.Ground truth zip (
GT.zip) for evaluation metrics.Focal lengths, one per camera.
Whether to run VGGT refinement after AMC completes, only when the project reports
vggt_state == "READY".
Instructions
The bundled script in scripts/run_rtsp_calibration.py implements this sequence end to end. Use the prose below for decisions, UI fallback, and troubleshooting.
Step 0 - Verify AMC and VIOS
Confirm the AMC microservice is reachable:
curl -sf http://<HOST_IP>:<MS_PORT>/v1/readyConfirm VIOS is reachable before starting capture. Probe in this order and stop at the first working URL:
: "${REPO_ROOT:?set REPO_ROOT to the auto-magic-calib checkout. Run amc-setup-calibration-stack Step 0b first.}"
grep -q "AutoMagicCalib" "$REPO_ROOT/README.md" 2>/dev/null && grep -q "auto-magic-calib-ms" "$REPO_ROOT/compose/ms/compose.yml" 2>/dev/null || { echo "ERROR: REPO_ROOT is not an auto-magic-calib checkout: $REPO_ROOT" >&2; exit 1; }
VIOS_BASE_URL=""
# Default local VIOS port.
if curl -sf http://localhost:30888/vst/api/v1/sensor/list >/dev/null 2>&1; then
VIOS_BASE_URL="http://localhost:30888"
echo "VIOS detected at $VIOS_BASE_URL"
fi
# Running AMC microservice container environment.
if [ -z "$VIOS_BASE_URL" ]; then
VIOS_BASE_URL=$(docker exec auto-magic-calib-ms-1 printenv VIOS_BASE_URL 2>/dev/null)
fi
if [ -n "$VIOS_BASE_URL" ]; then
curl -sf "${VIOS_BASE_URL}/vst/api/v1/sensor/list" >/dev/null \
&& echo "VIOS up at $VIOS_BASE_URL" \
|| { echo "VIOS_BASE_URL=$VIOS_BASE_URL is set but not responding"; VIOS_BASE_URL=""; }
fi
[ -n "$VIOS_BASE_URL" ] || {
echo "VIOS is not reachable. Export VIOS_BASE_URL=http://<VIOS_HOST>:30888 and relaunch the AMC microservice." >&2
exit 1
}If VIOS is not reachable, ask the user to deploy VIOS and provide the base URL. Do not start RTSP capture until ${VIOS_BASE_URL}/vst/api/v1/sensor/list returns 200.
If VIOS is reachable but the AMC microservice is missing VIOS_BASE_URL, do not edit checked-in compose files. Export the variable and relaunch the microservice with a temporary compose override:
cd "$REPO_ROOT/compose"
export VIOS_BASE_URL="http://<VIOS_HOST>:30888"
OVERRIDE_FILE="${TMPDIR:-/tmp}/amc-vios.override.yml"
cat > "$OVERRIDE_FILE" <<'YAML'
services:
auto-magic-calib-ms:
environment:
- VIOS_BASE_URL=${VIOS_BASE_URL}
YAML
docker compose -f compose.yml -f "$OVERRIDE_FILE" up -d auto-magic-calib-ms
docker exec auto-magic-calib-ms-1 printenv VIOS_BASE_URLA host-shell export alone is not enough after the container is already running; the microservice process must be restarted with VIOS_BASE_URL in its environment.
Step 1 - Create Project
POST /v1/create_project with form field project_name. Save the returned project_id.
Step 2 - Start RTSP Capture
POST /v1/rtsp/capture/<project_id>
Content-Type: application/json
{
"streams": [
{"rtsp_url": "rtsp://...", "camera_name": "cam_00", "sensor_id": null},
{"rtsp_url": "rtsp://...", "camera_name": "cam_01", "sensor_id": null}
],
"duration_seconds": 180,
"ssl_verify": true
}The response can nest session fields under session:
{"code": 0, "message": "...", "session": {"session_id": "...", "status": "STARTING"}}Save session.session_id.
Step 3 - Poll Capture, Then Ingest
Poll every 10 seconds:
GET /v1/rtsp/capture/<project_id>/<session_id>Session lifecycle:
STARTING -> RECORDING -> COMPLETED -> INGESTING -> INGESTED
-> ERROR
RECORDING -> CANCELLEDWhen capture reaches COMPLETED, ingest the recorded clips into the AMC project:
POST /v1/rtsp/capture/<project_id>/<session_id>/ingestAfter ingest succeeds, the project has video files attached and the rest of the workflow matches the MP4 upload path.
Need to stop early: POST /v1/rtsp/capture/<project_id>/<session_id>/stop. A partial clip can still be ingested if VIOS produced one.
Other session endpoints:
GET /v1/rtsp/sessions/<project_id>- list sessions for a project.
Step 4 - Upload Settings, Alignment, Layout, and Optional Files
Resolve local files using the anchor-file pattern above. Upload resolved files:
| File | Endpoint | Notes |
|---|---|---|
| Calibration settings | POST /v1/config/<project_id> | JSON body posted as-is; replaces UI Step 3 |
| Alignment JSON | POST /v1/upload_alignment/<project_id> | Multipart alignment_file |
| Layout PNG | POST /v1/upload_layout/<project_id> | Multipart layout_file |
| Ground truth zip | POST /v1/upload_gt_file/<project_id> | Optional |
| Focal lengths | POST /v1/upload_focal_length/<project_id> | Optional repeated focal_length values |
Use only files from explicit user-provided paths or a user-provided calibration asset directory. Do not extract or scan sample data to find fallback settings, alignment, layout, or GT.
If settings are missing, direct the user to UI Step 3: Parameters at http://<HOST_IP>:<AUTO_MAGIC_CALIB_UI_PORT>, then ask which detector to use (resnet or transformer) before calibration. If alignment or layout is missing, direct the user to UI Step 4: Alignment for this project. For RTSP projects, videos are already ingested; do not re-upload videos in the UI fallback.
Before continuing after UI Step 4, verify:
PROJECT_ID=<project_id>
: "${REPO_ROOT:?set REPO_ROOT to the auto-magic-calib checkout. Run amc-setup-calibration-stack Step 0b first.}"
grep -q "AutoMagicCalib" "$REPO_ROOT/README.md" 2>/dev/null && grep -q "auto-magic-calib-ms" "$REPO_ROOT/compose/ms/compose.yml" 2>/dev/null || { echo "ERROR: REPO_ROOT is not an auto-magic-calib checkout: $REPO_ROOT" >&2; exit 1; }
HOST_PROJECTS="${PROJECTS_DIR:-$(cd "$REPO_ROOT" && realpath projects)}"
ls "$HOST_PROJECTS/project_${PROJECT_ID}/manual_adjustment/"
# Expected: alignment_data.json, layout.pngIf the AMC stack stores project outputs outside the default projects/ directory, set PROJECTS_DIR explicitly before running the check above. Do not read compose/.env for project paths during this workflow.
Step 5 - Verify, Calibrate, Poll, and Fetch Results
Verify:
POST /v1/verify_project/<project_id>The project must return project_state == "READY".
Confirm the plan before calibrating. Summarize:
Stream count and recording duration.
Detector:
resnetortransformer.Settings source: explicit uploaded settings file, user-provided asset directory, or UI Step 3.
Alignment/layout source: explicit uploaded files, user-provided asset directory, or UI manual adjustment.
Optional GT and focal-length overrides.
Start calibration:
POST /v1/calibrate/<project_id>
Content-Type: application/json
{"detector_type": "<resnet-or-transformer>"}Poll:
GET /v1/get_project_info/<project_id>Stop on COMPLETED or ERROR. On error, fetch GET /v1/amc/calibrate/<project_id>/log.
Fetch results:
GET /v1/result/<project_id>/evaluation_statisticsOnly expect evaluation statistics when GT was uploaded.
Step 6 - Optional VGGT Refinement
After AMC calibration completes, read project_info.vggt_state from GET /v1/get_project_info/<project_id>.
If
vggt_state == "READY", ask whether to run VGGT refinement.If confirmed, call
POST /v1/vggt/calibrate/<project_id>, pollvggt_state, then fetchGET /v1/vggt_results/<project_id>/evaluation_statistics.If VGGT is not ready, skip it and explain that AMC calibration is complete.
Complete Python Script
Use the bundled script from the amc-run-rtsp-calibration skill package, not from the auto-magic-calib repo root. If the user points the agent at this skill folder directly instead of installing it, set AMC_RTSP_SKILL_DIR to the directory containing this SKILL.md, or run the command from that directory.
Common environment variables:
export BASE_URL=http://<HOST_IP>:8000
export PROJECT_NAME=rtsp_calibration_run
export RTSP_URLS='rtsp://user:pass@cam0/stream,rtsp://user:pass@cam1/stream'
export CAMERA_NAMES='cam_00,cam_01'
export DURATION_SECONDS=180
export VIOS_BASE_URL=http://<VIOS_HOST>:30888
export CALIB_ASSET_DIR=/path/to/rtsp-calibration-assets
# Or provide explicit CONFIG_FILE, ALIGNMENT_JSON, LAYOUT_PNG, and optional GT_ZIP.
export DETECTOR_TYPE=transformer # Required when settings do not set detector/detector_type.
export AMC_UI_URL=http://<HOST_IP>:5000
export RUN_VGGT=false
# Optional but recommended: REPO_ROOT points to the auto-magic-calib checkout.
# PROJECTS_DIR can be set explicitly when project outputs live elsewhere.
if [ -z "${DEEPSTREAM_REPO_ROOT:-}" ] && [ -n "${REPO_ROOT:-}" ] && [ -d "$REPO_ROOT/../../skills/amc-run-rtsp-calibration" ]; then
DEEPSTREAM_REPO_ROOT="$(cd "$REPO_ROOT/../.." && pwd)"
fi
SCRIPT_PATH=""
for candidate in \
"${AMC_RTSP_SKILL_DIR:+$AMC_RTSP_SKILL_DIR/scripts/run_rtsp_calibration.py}" \
"$PWD/scripts/run_rtsp_calibration.py" \
"${DEEPSTREAM_REPO_ROOT:+$DEEPSTREAM_REPO_ROOT/skills/amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py}" \
"$PWD/skills/amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py" \
"$HOME/.claude/skills/amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py" \
"$HOME/.codex/skills/amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py" \
"$HOME/.cursor/skills/amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py"; do
if [ -f "$candidate" ]; then
SCRIPT_PATH="$candidate"
break
fi
done
[ -n "$SCRIPT_PATH" ] || {
echo "ERROR: could not find amc-run-rtsp-calibration/scripts/run_rtsp_calibration.py" >&2
echo "Set AMC_RTSP_SKILL_DIR to the amc-run-rtsp-calibration skill directory, or run this block from that directory." >&2
exit 1
}
python3 "$SCRIPT_PATH"Alternative stream input:
export STREAMS_JSON='[
{"rtsp_url":"rtsp://cam0/stream","camera_name":"cam_00","sensor_id":null},
{"rtsp_url":"rtsp://cam1/stream","camera_name":"cam_01","sensor_id":null}
]'Optional env vars are CALIB_ASSET_DIR, CONFIG_FILE, ALIGNMENT_JSON, LAYOUT_PNG, GT_ZIP, FOCAL_LENGTHS, DETECTOR_TYPE, AMC_UI_URL, SSL_VERIFY, RUN_VGGT, REPO_ROOT, and PROJECTS_DIR. SSL_VERIFY defaults to true; only set SSL_VERIFY=false for loopback testing. If the VIOS deployment requires bearer authentication, stop and use a manual admin-managed capture flow instead of routing credentials through this skill.
Success Criteria
VIOS health probe returns 200.
Capture session reaches
COMPLETED.Ingest returns success and project info shows the expected video files.
verify_projectreturnsREADY.AMC calibration reaches
project_state == "COMPLETED".If GT was uploaded, evaluation statistics are returned.
No RTSP credentials, bearer tokens, NGC keys, or HuggingFace tokens are printed or persisted by the agent.
Key Output Files
Results persist on the AMC server under:
projects/project_<project_id>/
|-- manual_adjustment/
| |-- alignment_data.json
| `-- layout.png
|-- output/
| |-- single_view_results/cam_XX/
| | |-- camInfo_hyper_XX.yaml
| | `-- trajDump_Stream_0_3d.txt
| `-- multi_view_results/BA_output/results_ba/
| |-- initial/camInfo_XX.yaml
| `-- refined/camInfo_XX.yaml
`-- calibration.logTroubleshooting
| Issue | Fix |
|---|---|
VIOS /vst/api/v1/sensor/list returns connection refused | VIOS is not running or not reachable from this host. Ask the user to deploy VIOS or provide the reachable base URL. |
| Capture endpoint returns 503 or "VIOS not configured" | Export VIOS_BASE_URL, relaunch the microservice with the temporary compose override from Step 0, then retry capture. |
Session stuck in STARTING | VIOS accepted the request but sensors may not be online. Check ${VIOS_BASE_URL}/vst/api/v1/sensor/list and wait 20-30 seconds after sensor restarts. |
Session stuck in RECORDING past duration_seconds | Call POST /v1/rtsp/capture/<project_id>/<session_id>/stop, then ingest the partial clip if available. |
| Ingest fails with "No clip available" | The recording window may not overlap the VIOS timeline. Wait for sensors to become online, then start a new capture. |
| 400 "empty streams" | Pass at least one stream object with rtsp_url and camera_name. |
| 400 "duration too short" | Use duration_seconds >= 60. |
404 on /v1/rtsp/capture/<project_id> | Create the project first with /v1/create_project. |
verify_project is not READY after ingest | Check project info and confirm expected videos, alignment, and layout are attached. |
Calibration reaches ERROR | Fetch GET /v1/amc/calibrate/<project_id>/log; common causes are insufficient tracklets, static scenes, or incorrect alignment. |
Related Skills
skills/amc-setup-calibration-stack/SKILL.md- start AMC microservice and UI first.skills/amc-run-video-calibration/SKILL.md- calibrate from local pre-recorded MP4 files.skills/amc-run-sample-calibration/SKILL.md- verify the stack with the bundled sample dataset.
<!-- signing marker -->
Files
- ATTRIBUTION.mdAdded by AutoGineer939 B
- BENCHMARK.md4.5 KiB
- LICENSELicence file added by AutoGineer11.2 KiB
- SKILL.md17.8 KiB
- evals/evals.json6.8 KiB
- scripts/run_rtsp_calibration.pyScript22.0 KiB
- skill-card.md4.1 KiB
- skill.oms.sig4.7 KiB
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Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs network access, Needs a command-line tool, Needs Python
Security
What our scanner noticed· Medium risk
- Large base64-encoded blobs
- Instructions that use the network
- Scripts that your agent may run
This skill includes scripts that your agent may run. Read them before you use it.
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Shubham Agrawal
- Publisher
- NVIDIA (Official)
- Distributed by
- NVIDIA
- Source
- NVIDIA/skills · skills/amc-run-rtsp-calibration · commit fce3cca
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE-APACHE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Shubham Agrawal or NVIDIA.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download amc-run-rtsp-calibration.zip