isaac-camera

Camera (Isaac Sim 6 / Kit 110)

Two layers stack:

1. UsdGeomCamera — the USD camera prim (focal length, apertures, clipping, transform).
2. isaacsim.sensors.experimental.rtx — the runtime sensor wrapper (authoring class + runtime sensor class). Use this for any new code that captures frames, attaches annotators, or applies lens distortion.

The legacy isaacsim.sensors.camera.Camera class still works but the extension itself is a stub (no Python). The implementation moved to isaacsim.sensors.experimental.rtx; new code should use that.

Migration: see the Migration from isaacsim.sensors.camera.Camera table below, plus the official camera migration guide for the full API change set.

When to use

• Create or configure camera prims in USD stages.
• Attach RGB / depth / segmentation / bbox annotators for capture.
• Apply lens distortion (OpenCV pinhole, OpenCV fisheye, LUT).
• Convert real-world calibration (OpenCV / ROS) to Omniverse units.
• Build stereo, multi-sensor, or tiled multi-camera rigs.
• Animate cameras (keyframes, motion paths, orbit, fly-through).
• Generate synthetic data with Replicator randomization.
• Set up Metropolis cameras for MEGA scenarios.

Fundamentals

Unit system

OpenUSD expresses optical properties in tenths of a scene unit.

Meter stage: a 25 mm focal length is 0.025.

Coordinate system

Camera looks down -Z; +Y is up, +X is right. Same regardless of stage up-axis.

Path A — RtxCamera + CameraSensor (recommended)

RtxCamera wraps a UsdGeom.Camera prim with OmniSensorAPI applied; CameraSensor builds a Replicator render product on top and exposes annotators. Both extend the isaacsim.core.experimental.prims.XformPrim family, so the standard pose / transform methods apply.

from isaacsim.sensors.experimental.rtx import RtxCamera, CameraSensor
import isaacsim.core.experimental.utils.app as app_utils

cam = RtxCamera(
    "/World/cam",
    tick_rate=30.0,                       # 0 = autotrigger
    aux_output_level="NONE",              # RtxCamera supports NONE only
)
cam.camera.set_focal_lengths(24.0)
cam.camera.set_clipping_ranges(0.01, 1000.0)

sensor = CameraSensor(
    cam,
    resolution=(480, 640),                # (height, width)
    annotators=["rgb", "distance_to_image_plane"],
)
app_utils.play(commit=True)
data = sensor.get_data("rgb")

TiledCameraSensor batches many cameras into one render call; useful for multi-view RL data collection. SingleViewDepthCameraSensor simulates stereo depth via OmniSensorDepthSensorSingleViewAPI.

Lens distortion (OpenCV fisheye / pinhole)

Set via API schemas + USD attributes at authoring time. The schema and attribute names are stable; use them through RtxCamera's schemas and attributes constructor args, or Apply them on the camera prim directly.

from isaacsim.sensors.experimental.rtx import RtxCamera
from pxr import Gf

cam = RtxCamera(
    "/World/fisheye",
    schemas=["OmniLensDistortionOpenCvFisheyeAPI"],
    attributes={
        "omni:lensdistortion:opencvFisheye:fx": 500.0,
        "omni:lensdistortion:opencvFisheye:fy": 500.0,
        "omni:lensdistortion:opencvFisheye:cx": 640.0,
        "omni:lensdistortion:opencvFisheye:cy": 360.0,
        "omni:lensdistortion:opencvFisheye:k1": 0.05,
        "omni:lensdistortion:opencvFisheye:imageSize": Gf.Vec2i(1280, 720),
    },
)

Equivalent OpenCV-pinhole schema: OmniLensDistortionOpenCvPinholeAPI (attributes omni:lensdistortion:opencvPinhole:{fx,fy,cx,cy,k1,k2,p1,p2,...}). LUT-based distortion uses OmniLensDistortionLutAPI.

Path B — UsdGeomCamera + omni.replicator.core (no RTX wrapper)

When you don't need RTX sensor features (lens distortion, ISP, tick-rate control), straight USD + Replicator works:

from pxr import UsdGeom, Gf
import omni.replicator.core as rep

cam = UsdGeom.Camera.Define(stage, "/World/Cam")
cam.GetFocalLengthAttr().Set(24.0)
cam.GetHorizontalApertureAttr().Set(36.0)            # full-frame 35 mm equiv
cam.GetVerticalApertureAttr().Set(20.25)
cam.GetClippingRangeAttr().Set(Gf.Vec2f(0.01, 1000.0))

rp = rep.create.render_product(cam.GetPath(), (1920, 1080))
rgb     = rep.AnnotatorRegistry.get_annotator("rgb")
depth   = rep.AnnotatorRegistry.get_annotator("distance_to_camera")
semseg  = rep.AnnotatorRegistry.get_annotator("semantic_segmentation",
                                              init_params={"colorize": True})
normals = rep.AnnotatorRegistry.get_annotator("normals")
for ann in (rgb, depth, semseg, normals):
    ann.attach([rp])

For pose authoring use isaacsim.core.experimental.objects.Camera (wraps UsdGeom.Camera with the standard pose / scale API), or the look-at helper:

from isaacsim.core.experimental.objects import Camera

cam = Camera(paths="/World/Cam", positions=[2.0, 2.0, 2.0])
cam.set_world_poses(positions=[[2.0, 2.0, 2.0]],
                    orientations=[[1.0, 0.0, 0.0, 0.0]])

OpenCV intrinsics -> USD

from pxr import UsdGeom

def opencv_to_usd_camera(stage, path, fx, fy, cx, cy, image_w, image_h,
                         sensor_w_m=0.036):
    """OpenCV intrinsics -> USD camera on a meter-stage."""
    focal_length_m = fx * sensor_w_m / image_w
    h_aperture     = sensor_w_m
    v_aperture     = fy * sensor_w_m / fx   # preserve aspect
    cam = UsdGeom.Camera.Define(stage, path)
    cam.GetFocalLengthAttr().Set(focal_length_m)
    cam.GetHorizontalApertureAttr().Set(h_aperture)
    cam.GetVerticalApertureAttr().Set(v_aperture)
    # Principal-point offset:
    cam.GetHorizontalApertureOffsetAttr().Set((cx - image_w / 2) * sensor_w_m / image_w)
    cam.GetVerticalApertureOffsetAttr().Set((cy - image_h / 2) * sensor_w_m / image_w)
    return cam

Animation

from pxr import Usd, Gf

for frame, pos in enumerate(camera_positions):
    cam.GetPrim().GetAttribute("xformOp:translate").Set(
        Gf.Vec3d(*pos), Usd.TimeCode(frame)
    )

Replicator randomization

import omni.replicator.core as rep

with rep.new_layer():
    cameras = rep.get.prims(path_pattern="/World/Camera.*")
    with rep.trigger.on_frame(num_frames=200):
        with cameras:
            rep.modify.pose(
                position=rep.distribution.uniform((-5, -5, 2), (5, 5, 8)),
                look_at="/World/Target",
            )

Sensor checker / supported configs

For asset-driven lidar / camera configs and validation helpers, see isaacsim.sensors.experimental.rtx.SUPPORTED_LIDAR_CONFIGS and the sensor_checker module bundled with the extension. The Replicator AOV annotator names match the standard registry: rgb, distance_to_image_plane, distance_to_camera, normals, semantic_segmentation, instance_segmentation, bounding_box_2d_tight, bounding_box_2d_loose, bounding_box_3d, camera_params, pointcloud, occlusion.

Migration from isaacsim.sensors.camera.Camera

Full guide: isaacsim.sensors.camera → isaacsim.sensors.experimental.rtx.