ruvnet/RuView · error · ValueError

Intrinsics file {path} missing key {key!r}

Error message

Intrinsics file {path} missing key {key!r}

What it means

load_intrinsics loads a precomputed camera-intrinsics JSON for the calibration flow. It accepts either a bare intrinsics dict or a full bundle containing a 'camera_intrinsics' object, then requires the keys camera_matrix, dist_coeffs, and image_size. The first missing key raises ValueError naming the file and the key.

Source

Thrown at scripts/calibration_lib.py:153

    )
    return {
        "image_size": [int(image_size[0]), int(image_size[1])],
        "camera_matrix": camera_matrix.tolist(),
        "dist_coeffs": dist_coeffs.ravel().tolist(),
        "reprojection_error_px": float(rms),
        "source": "computed",
    }


def load_intrinsics(path: Path) -> dict:
    """Load a pre-computed intrinsics JSON ({camera_matrix, dist_coeffs, image_size})."""
    with open(path, "r", encoding="utf-8") as f:
        data = json.load(f)
    # Accept either a bare intrinsics dict or a full calibration bundle.
    intr = data.get("camera_intrinsics", data)
    for key in ("camera_matrix", "dist_coeffs", "image_size"):
        if key not in intr:
            raise ValueError(f"Intrinsics file {path} missing key {key!r}")
    intr = dict(intr)
    intr["source"] = "file"
    return intr


# ---------------------------------------------------------------------------
# Extrinsics (camera -> room rigid transform)
# ---------------------------------------------------------------------------

def reprojection_rmse(
    room_points: np.ndarray,
    image_points: np.ndarray,
    rvec: np.ndarray,
    tvec: np.ndarray,
    camera_matrix: np.ndarray,
    dist_coeffs: np.ndarray,
) -> float:
    proj, _ = cv2.projectPoints(room_points, rvec, tvec, camera_matrix, dist_coeffs)

View on GitHub (pinned to 4685618388)

Solutions

1. Regenerate the intrinsics file with the calibration flow so all three keys are written
2. If importing from elsewhere, map fields explicitly: K → camera_matrix (3x3), D → dist_coeffs, [w, h] → image_size
3. Pre-validate: jq 'has("camera_matrix") and has("dist_coeffs") and has("image_size")' intrinsics.json

Example fix

// before
// intrinsics.json
{"camera_matrix": [[800,0,320],[0,810,240],[0,0,1]]}

// after
// intrinsics.json
{"camera_matrix": [[800,0,320],[0,810,240],[0,0,1]],
 "dist_coeffs": [0,0,0,0,0],
 "image_size": [640,480]}

import json

REQUIRED = ("camera_matrix", "dist_coeffs", "image_size")

def intrinsics_valid(path: str) -> bool:
    with open(path, encoding="utf-8") as f:
        data = json.load(f)
    intr = data.get("camera_intrinsics", data) if isinstance(data, dict) else {}
    return isinstance(intr, dict) and all(k in intr for k in REQUIRED)

if not intrinsics_valid("intrinsics.json"):
    raise SystemExit(f"intrinsics file must contain {REQUIRED}")

try:
    intr = load_intrinsics(path)
except ValueError as e:
    raise SystemExit(f"regenerate the intrinsics file: {e}") from e

When it happens

Trigger: Passing an intrinsics file that contains only camera_matrix (no dist_coeffs/image_size), a bundle whose nested object uses different key names, or a geometry file where intrinsics were expected.

Common situations: Reusing intrinsics exported from another OpenCV pipeline that omits D or image size; hand-edited files; resolution changed after calibration so image_size is missing.

Related errors

• {path}: expected {{'nodes': [...]}} or a top-level list
• {path}: each node needs 'id' and 'position_m' [x,y,z]
• Calibration bundle {path} missing key {key!r}
• Failed to load domain configuration: {e}
• Invalid axis token {token!r}; expected one of {sorted(_AXIS_

AI-assisted analysis of ruvnet/RuView@4685618388 (2026-08-16). Data as JSON: /api/errors/9ea5a3ce03af2ddd. Report an issue: GitHub.