/amc-run-rtsp-calibration

name: "amc-run-rtsp-calibration"
description: "Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration."
owner: "NVIDIA CORPORATION"
service: "auto-magic-calib"
version: "1.0.0"
reviewed: "2026-06-15"
license: "Apache-2.0"
permissions: [env, file_read, network]
metadata:
  author: "Shubham Agrawal <shuagrawal@nvidia.com>"
  tags: [amc, calibration, rtsp, vios, rest-api, camera, python]

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.md` if needed).
• [ ] VIOS is running and reachable from the AMC microservice.
• [ ] `VIOS_BASE_URL` is 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 `requests` installed 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

1. RTSP URLs, one per camera. 2. Camera names, one per stream. Use `cam_00`, `cam_01`, ... if the user does not provide names. 3. Recording duration in seconds. Minimum is `60`; prefer `120`-`180` or more when the scene has sparse motion. 4. Microservice URL, for example `http://<HOST_IP>:8000` or `http://<HOST_IP>:8000/v1`. 5. Project name. 6. 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

6. `sensor_id` per stream if the cameras are already registered in VIOS. Leave unset for auto-registration. 7. Ground truth zip (`GT.zip`) for evaluation metrics. 8. Focal lengths, one per camera. 10. 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](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/ready

Confirm 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/compo