amc-run-video-calibration v1.0.0A

Immutable. This exact content is served forever at /api/v1/blob/f38fe3f2680c5ecb.

---
name: "amc-run-video-calibration"
description: "Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`."
owner: "NVIDIA CORPORATION"
service: "auto-magic-calib"
reviewed: "2026-04-28"
license: "Apache-2.0"
permissions: [env, file_read, network]
metadata:
  version: "1.0.0"
  author: "Shubham Agrawal <shuagrawal@nvidia.com>"
  tags: [amc, calibration, rest-api, camera, python]
---

# Skill: Calibrate from Video Files

## When to Use This Skill

Activate this skill when the user has pre-recorded MP4 files and wants to calibrate them via the AMC REST API. Typical prompts:

- "calibrate my videos" / "run AMC on these videos"
- "calibrate from video files"

Drives calibration through the REST API on user-supplied **pre-recorded MP4 files** — no CLI scripts or Docker bind-mounts required, just a running microservice and your files.

Do not use this skill for live RTSP streams or `rtsp://...` URLs; route those requests to `skills/amc-run-rtsp-calibration/SKILL.md`.

## Purpose

Guide the agent through project creation, sorted MP4 upload, local asset resolution, UI fallback only when necessary, project verification, calibration, polling, evaluation, and optional VGGT refinement for a user-provided multi-camera dataset.

## Prerequisites

- [ ] AMC microservice **and** UI running (follow `skills/amc-setup-calibration-stack/SKILL.md`)
- [ ] You know the microservice URL (use `https://<HOST_IP>:<MS_PORT>` for remote AMC, or `http://localhost:<MS_PORT>` on loopback) and UI URL
- [ ] Video files locally as contiguous `cam_00.mp4`, `cam_01.mp4`, … time-synchronized, ~1920×1080
- [ ] Python 3 with `requests`
- [ ] If AMC stores project outputs outside the default `projects/` directory, you know the host `PROJECTS_DIR`

## Interaction Model

- The "host's question mechanism" means the runtime's built-in prompt API for short user decisions, such as terminal stdin, an IDE ask tool, or an equivalent interactive dialog.
- If that mechanism is unavailable, ask in chat and wait before any guarded step that requires user confirmation or a missing-file decision.
- For unattended runs, the bundled script requires all non-UI inputs up front and exits before `/calibrate` unless `CONFIRM_CALIBRATION=true` is set. `RUN_VGGT=true` remains a separate opt-in for the optional VGGT step.

## Data Privacy

Video files uploaded via this skill are transmitted to the AutoMagicCalib backend (REST endpoint). Only use this skill when the backend is deployed on a trusted platform / network.

## Inputs

- Required inputs: `VIDEO_DIR`, `BASE_URL`, and `PROJECT_NAME`.
- Optional local inputs: `CONFIG_FILE`, `ALIGNMENT_JSON`, `LAYOUT_PNG`, `GT_ZIP`, `FOCAL_LENGTHS`, and `DETECTOR_TYPE`.
- Optional control inputs: `CONFIRM_CALIBRATION`, `RUN_VGGT`, `PROJECTS_DIR`, `CALIBRATION_TIMEOUT_SECONDS`, and `VGGT_TIMEOUT_SECONDS`.
- `BASE_URL` should use HTTPS for non-loopback hosts. Set `ALLOW_INSECURE_HTTP=true` only for trusted development setups that intentionally use remote plain HTTP.
- Resolution precedence for settings, alignment, and layout: explicit path, single local auto-detected match, then UI fallback.

## What to Ask the User

### Required
(Video-file naming and the microservice URL are specified under Prerequisites above — collect the inputs below.)
1. **Videos directory** — the folder the skill globs for `cam_*.mp4`, uploaded sorted alphabetically.
2. **Microservice URL**
3. **Project name** — short descriptive string

### Auto-Detected (ask only if not found)

The script searches the videos dir, its first-level subdirectories, and its parent. If exactly one match is found, it is used; otherwise the script prints the searched locations and continues to explicit path or UI fallback:

| File | Candidate filenames | UI fallback |
|---|---|---|
| Calibration settings | `settings.json`, `config.json`, `calibration_config.json` | UI Step 3: Parameters |
| Alignment JSON | `alignment_data.json` | UI Step 4: Alignment |
| Layout PNG | `layout.png` | UI Step 4: Alignment |

Posting the settings file replaces UI Step 3 and may pin the detector (`resnet`/`transformer`), which is passed to `/calibrate` separately — see Step 4.

### Optional
4. **Ground truth zip** — `GT.zip` with `_World_Cameras_Camera_XX/` folders (enables evaluation metrics)
5. **Focal lengths** — one per camera, e.g. `1269.0, 1099.5, 1099.5`
6. **Detector type** — `resnet` (default, fast) or `transformer` (slower, better under occlusion)
7. **Run VGGT refinement?** — if VGGT is ready after AMC completes, ask the user whether to run refinement (see setup skill)

See root `README.md` "Custom Dataset" section for input-video guidelines and ground-truth format.

---

## Available Scripts

| Script | Purpose | Key inputs |
|---|---|---|
| [run_video_calibration.py](scripts/run_video_calibration.py) | Executes create-project, upload, verify, calibrate, poll, evaluate, and optional VGGT refinement for a local MP4 dataset. | Required: `BASE_URL`, `PROJECT_NAME`, `VIDEO_DIR`. Optional: `CONFIG_FILE`, `ALIGNMENT_JSON`, `LAYOUT_PNG`, `GT_ZIP`, `FOCAL_LENGTHS`, `DETECTOR_TYPE`, `CONFIRM_CALIBRATION`, `RUN_VGGT`, `PROJECTS_DIR`, `CALIBRATION_TIMEOUT_SECONDS`, `VGGT_TIMEOUT_SECONDS`, `ALLOW_INSECURE_HTTP`. |

## Instructions

All endpoints below are implemented end-to-end in the [Complete Python Script](#complete-python-script) — the prose is the workflow plus the decisions the agent must make; the script is the authoritative runnable.

### Step 1 — Create Project

`POST /v1/create_project` (form field `project_name`) → save the returned `project_id`.

### Step 2 — Upload Videos (required)

`POST /v1/upload_video_files/<project_id>` (multipart `files`). **Upload sorted alphabetically** — the server assigns camera indices by upload order. The bundled script rejects non-contiguous or non-zero-based camera sequences up front; the directory must contain `cam_00.mp4`, `cam_01.mp4`, ... with no gaps.

### Step 3 — Resolve Local Files (Auto-Scan, Ask, or UI)

For each of calibration-settings, alignment, and layout, run this resolution:

**Auto-use rule:** if exactly one match is found, the script uses it automatically and prints the resolved path. No extra prompt occurs for that file.

1. **Auto-scan** `VIDEO_DIR`, one level of subdirectories under `VIDEO_DIR`, and `VIDEO_DIR.parent` for the candidate filenames (table above).
2. If **exactly one match**, use it and print what was found.
3. If **zero or multiple matches**, print the searched locations, then ask the user for an explicit path using the host's question mechanism; if none is available, ask in chat and wait. If they don't have the file, mark it for UI fallback.
4. **UI fallback**: tell the user to complete the corresponding UI step; wait for confirmation; then continue to Step 6 and treat `verify_project` as the source of truth for whether the UI-supplied alignment/layout data is complete.

### Step 4 — Upload Resolved Files

Upload each file resolved locally:

| File | Endpoint | Notes |
|---|---|---|
| Calibration settings | `POST /v1/config/<project_id>` (JSON, posted as-is) | Replaces UI Step 3 (rectification, bundle-adjustment, evaluation, detector, …). Non-2xx is surfaced — never silently fall back. Skip on the UI-fallback path. |
| Alignment | `POST /v1/upload_alignment/<project_id>` (`alignment_data.json`) | |
| Layout | `POST /v1/upload_layout/<project_id>` (`layout.png`) | |
| Ground truth (optional) | `POST /v1/upload_gt_file/<project_id>` (`GT.zip`) | Enables evaluation metrics |
| Focal lengths (optional) | `POST /v1/upload_focal_length/<project_id>` (repeated `focal_length=`) | Overrides GeoCalib estimates |

Upload all resolved local files first, in any order. After the local uploads are complete, continue to Step 5 only for unresolved files, then run Step 6 exactly once to verify the assembled project.

After a successful settings POST, parse the file for `"detector"` / `"detector_type"` — if it's `"resnet"` or `"transformer"`, use that value for the `/calibrate` call in Step 7 (detector is a separate API parameter, not consumed by `/config`).

### Step 5 — UI Fallback (only for files the user doesn't have locally)

If any of settings / alignment / layout was not resolved in Step 3, direct the user to the appropriate UI step:

- **Settings missing** → "Open UI project `<project_id>`, go to **Step 3: Parameters**, tune via the settings dialog (or accept defaults), click Save." **Also**: before the `/calibrate` call, ask the user which detector to use (`resnet` or `transformer`) using the host's question mechanism; if none is available, ask in chat and wait. UI Step 3 does not cover detector choice.
- **Alignment or layout missing** → "Open UI project `<project_id>`, go to **Step 4: Alignment**, upload layout, mark correspondence points, click Save."

Wait for user confirmation. For non-interactive script runs, provide the needed files up front; the script exits with a clear message rather than waiting on input. Do not require local access to AMC's `projects/` storage for the UI fallback; Step 6 is the canonical server-side verification step.

### Step 6 — Verify Project

`POST /v1/verify_project/<project_id>` → must return `{"project_state": "READY"}` before calibrating.

### Step 7 — Start Calibration

**Confirm the plan before calibrating.** Whether the settings file and detector were auto-detected or asked, present a short summary and get explicit user confirmation before `POST /calibrate` using the host's question mechanism; if none is available, ask in chat and wait. The resolved values are the defaults, so confirming is one click, but the user can switch the detector or skip an auto-detected settings file. The standalone Python script prompts when stdin is interactive; in non-interactive runs it exits before `/calibrate` unless `CONFIRM_CALIBRATION=true` is set. Summarize:

- **Detector** — `resnet` or `transformer` (the value to be sent).
- **Calibration settings** — the file being applied (path), or "defaults" if none.
- **Optional overrides** — ground-truth zip and focal lengths, if any.

```
POST /v1/calibrate/<project_id>
Content-Type: application/json

{"detector_type": "resnet"}
```

### Step 8 — Poll for Completion

`GET /v1/get_project_info/<project_id>` every 10 s — `project_info.project_state` goes `RUNNING` → `COMPLETED` (or `ERROR`, pull the log). Typical time: **10–60 min** depending on video length and detector. The bundled script defaults to a `90` minute cap through `CALIBRATION_TIMEOUT_SECONDS=5400`; raise that env var for longer runs instead of silently killing the process.

### Step 9 — Get Results

`GET /v1/result/<project_id>/evaluation_statistics` (only if GT was uploaded; includes `Average L2 distance(m)` and `Average reprojection error 0(px)`), and `GET /v1/amc/calibrate/<project_id>/log` for the calibration log. If GT was uploaded and `evaluation_statistics` returns non-200, surface that HTTP error instead of treating it as a missing-GT case.

### Status Fields from `get_project_info`

`project_info.project_state` is the AMC calibration lifecycle for the project: `RUNNING` → `COMPLETED` (or `ERROR`).

`project_info.vggt_state` is also **per-project**, a project-scoped VGGT refinement lifecycle rather than a direct global service or model-load status. A newly created project can report `vggt_state: "INIT"` even when the VGGT model is present and mounted. The expected VGGT lifecycle is `INIT` → `READY` after AMC calibration completes → `RUNNING` while VGGT refinement runs → `COMPLETED` (or `ERROR`).

Use `vggt_state == "READY"` only as the gate for optional VGGT refinement in Step 10. Interpret `INIT` on a new or uncalibrated project as normal project state. If AMC calibration is complete and the project remains in a non-ready VGGT state, confirm VGGT setup and model availability with the setup skill checks and service logs.

### Step 10 — (Optional) VGGT Refinement

After AMC calibration completes, read `vggt_state` from `GET /v1/get_project_info/<project_id>`.

- If the project reports `vggt_state == "READY"`, ask the user whether to run VGGT refinement using the host's question mechanism; if none is available, ask in chat and wait.
- If the user confirms, `POST /v1/vggt/calibrate/<project_id>`, poll `vggt_state` via `get_project_info`, then `GET /v1/vggt_results/<project_id>/evaluation_statistics`.
- If VGGT is not ready, skip refinement and explain that the user can set up VGGT with `amc-setup-calibration-stack` and rerun this optional step later.

The standalone Python script prompts only when stdin is interactive. In non-interactive runs, set `RUN_VGGT = True` to opt in; otherwise the script prints that VGGT is ready and continues without blocking.

---

## Complete Python Script

Use the bundled script from the `amc-run-video-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_VIDEO_SKILL_DIR` to the directory containing this `SKILL.md`, or run the command from that directory. Set `BASE_URL`, `PROJECT_NAME`, and `VIDEO_DIR`; optional env vars are `CONFIG_FILE`, `ALIGNMENT_JSON`, `LAYOUT_PNG`, `GT_ZIP`, `FOCAL_LENGTHS`, `DETECTOR_TYPE`, `RUN_VGGT`, `REPO_ROOT`, `PROJECTS_DIR`, `CONFIRM_CALIBRATION`, `CALIBRATION_TIMEOUT_SECONDS`, `VGGT_TIMEOUT_SECONDS`, and `ALLOW_INSECURE_HTTP`. The script implements AMC readiness checks, UI fallback, explicit confirmation gating, bounded polling, and refined statistics retrieval.

```bash
# 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 "$REPO_ROOT/../../skills/amc-run-video-calibration" ]; then
  DEEPSTREAM_REPO_ROOT="$(cd "$REPO_ROOT/../.." && pwd)"
fi

SCRIPT_PATH=""
for candidate in \
  "${AMC_VIDEO_SKILL_DIR:+$AMC_VIDEO_SKILL_DIR/scripts/run_video_calibration.py}" \
  "$PWD/scripts/run_video_calibration.py" \
  "${DEEPSTREAM_REPO_ROOT:+$DEEPSTREAM_REPO_ROOT/skills/amc-run-video-calibration/scripts/run_video_calibration.py}" \
  "$PWD/skills/amc-run-video-calibration/scripts/run_video_calibration.py" \
  "$HOME/.claude/skills/amc-run-video-calibration/scripts/run_video_calibration.py" \
  "$HOME/.codex/skills/amc-run-video-calibration/scripts/run_video_calibration.py" \
  "$HOME/.cursor/skills/amc-run-video-calibration/scripts/run_video_calibration.py"; do
  if [ -f "$candidate" ]; then
    SCRIPT_PATH="$candidate"
    break
  fi
done

[ -n "$SCRIPT_PATH" ] || {
  echo "ERROR: could not find amc-run-video-calibration/scripts/run_video_calibration.py" >&2
  echo "Set AMC_VIDEO_SKILL_DIR to the amc-run-video-calibration skill directory, or run this block from that directory." >&2
  exit 1
}

python3 "$SCRIPT_PATH"
```

## Examples

Interactive run with auto-detection for local settings/alignment/layout:

```bash
BASE_URL="http://localhost:8000/v1" \
PROJECT_NAME="warehouse-calibration" \
VIDEO_DIR="/data/warehouse_session" \
python3 "$SCRIPT_PATH"
```

Non-interactive run with all required local files supplied up front:

```bash
BASE_URL="http://localhost:8000/v1" \
PROJECT_NAME="warehouse-batch" \
VIDEO_DIR="/data/warehouse_session" \
CONFIG_FILE="/data/warehouse_session/settings.json" \
ALIGNMENT_JSON="/data/warehouse_session/alignment_data.json" \
LAYOUT_PNG="/data/warehouse_session/layout.png" \
CONFIRM_CALIBRATION=true \
RUN_VGGT=true \
python3 "$SCRIPT_PATH"
```

## Success Criteria

- `project_state == "COMPLETED"` after polling.
- `verify_project` returned `READY` before calibration (including manual alignment/UI fallback paths).
- If GT was uploaded: evaluation returns typical thresholds:
  - `Average L2 distance(m)` < 1.5
  - `Average reprojection error 0(px)` < 5
- No `ERROR` state.

## Key Output Files (on server)

```
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          # ← final calibration
└── calibration.log
```

## Limitations

- This skill only applies to local pre-recorded `cam_*.mp4` datasets. Live RTSP streams and the bundled sample dataset are out of scope.
- Unattended runs cannot rely on UI fallback; provide the required local files up front and set `CONFIRM_CALIBRATION=true`.
- Reported server-side output paths depend on the correct host `PROJECTS_DIR` when AMC writes project outputs outside the default `projects/` directory.

## Troubleshooting

| Issue | Fix |
|---|---|
| `verify_project` state not `READY` | Confirm videos uploaded and alignment + layout are present (either via API or via UI manual alignment) |
| Manual alignment still not accepted after UI step | User likely did not click Save or the UI data is incomplete; rerun `verify_project` and repeat UI Step 4 |
| Calibration stuck `RUNNING` > 90 min | `GET /v1/amc/calibrate/<id>/log` — usually insufficient tracklets (scene too static). See "Custom Dataset" guidelines in root README. |
| Immediate `ERROR` state | Check video naming: must be `cam_00.mp4`, `cam_01.mp4`, … contiguous |
| Low L2 but high reprojection | Provide explicit `focal_length` override via Step 3 |
| VGGT stays non-ready after AMC completes | `INIT` is expected for a new project. After AMC calibration reaches `COMPLETED`, the project should transition to `READY` before optional VGGT refinement when VGGT is configured. If refinement is required and the state remains `INIT` or otherwise non-ready, confirm VGGT setup and model availability with setup skill Step 2 and MS logs. |
| Upload timeout | Large videos — bump `timeout=300` to e.g. `600` in the script |

## For Downstream Skills — MV3DT Export

A downstream Multi-View 3D Tracking skill fetches the MV3DT-format calibration directly from the microservice (this skill does **not** download it; it returns the `project_id`). After this skill reports `COMPLETED`:

- `GET /v1/result/{project_id}/mv3dt_result?result_type=amc` → `mv3dt_output.zip` (contains `transforms.yml`).
- If VGGT ran to `COMPLETED` (Step 10): `?result_type=vggt` → `vggt_mv3dt_output.zip`.

## Related Skills

- `skills/amc-setup-calibration-stack/SKILL.md` — start MS + UI first.
- `skills/amc-run-sample-calibration/SKILL.md` — verify the stack with the bundled sample before trying your own.
- `skills/amc-run-rtsp-calibration/SKILL.md` — same calibration tail, but sourcing footage from live RTSP streams through VIOS.

Root `README.md` "Custom Dataset" and "Calibration Workflow (UI)" sections document input-video guidelines and the UI-driven alternative to this API flow.

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