Files

T

cesarandClaude Opus 5 15134dc12e add a depth output

Publish sl::MEASURE::DEPTH as float32 [H, W] millimetres on every frame that
carries image_bgr, with the intrinsics, frame_id and timestamps the other
outputs carry.

The map is copied out rather than published in place: sl::Mat rows can be
padded, so the buffer is not necessarily H * W floats. inf and nan are cleared
to 0 in the same pass, matching the reference driver — a hole is meaningful and
a consumer cannot back-project a non-finite value.

Consumers that need 3D can now back-project depth with the published
intrinsics instead of receiving a point cloud.

Also drops the stale objects entry from the dataflow outputs, missed when
detection was removed.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y7g2cBJ5e3r15ZbJ9WZn8c

2026-09-08 09:17:36 -03:00

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AGENTS.md

This file provides guidance to AI coding assistants when working with code in this repository.

What this is

A dora-rs C++ node that interfaces with ZED stereo cameras. On each tick it grabs a frame and publishes it over the dora dataflow: a BGR image, an XYZRGBA point cloud and camera intrinsics. Camera management lives in src/zed/ and the dora event loop in src/main.cc.

The node is a camera source only. It ran inference in-process through v0.1.0, under src/engines/; that was removed so the node has no inference dependency and builds on any platform the ZED SDK supports. The removed code remains reachable at tag v0.1.0.

Build

scripts/build.sh

The binary is installed to bin/dora_zed relative to the repo root. The script is also the dataflow's build: command: dora 1.0 executes build commands directly rather than through a shell, so cd, && and command substitution do not work there.

Requirements: dora 1.0+ (verified with dora-cli 1.0.1), CMake 3.21+, ZED SDK 5.x (at /usr/local/zed), CUDA Toolkit, Rust stable toolchain (for dora-rs C++ bindings).

The first build clones dora-rs from GitHub and compiles dora-node-api-cxx via Cargo. This takes a while. Subsequent builds are incremental. If DORA_ROOT_DIR is set to a local dora checkout, it builds against that instead.

For a build without installing the SDK stack on the host, see the Dockerfile (Ubuntu 24.04 — the newest release with a ZED SDK; there is no Stereolabs build for 26.04). Run the compile with --gpus all.

Run

dora up
dora start dataflow.yml

Camera behavior is configured entirely through environment variables (see README.md for the full list: ZED_RESOLUTION, ZED_FPS, ZED_DEPTH_MODE, etc.).

Architecture

src/util/env.h — Shared inline env-variable parsing helpers (get_env_int, get_env_str, get_env_bool, get_env_float).
src/zed/camera.h — zed::Config, zed::Calibration, and zed::Camera class. Camera wraps the ZED SDK lifecycle: open (with retry loop), warmup, grab (image + depth + point cloud), calibration, device timestamp, and close. Exposes handle() for engine access.
src/zed/camera.cc — Implementation. SDK enum parsers live in an anonymous namespace.
src/main.cc — Dora event loop. Parses ZED_PC_MODE (FULL/HALF) once before the loop. On any input event (intended to be driven by a tick timer; the id is not inspected): calls camera.grab(), then sends image_bgr, depth, point_cloud and camera_info. pack_depth copies the depth map into a tightly packed [H, W] float buffer (sl::Mat rows can be padded) and clears inf/nan to 0. set_intrinsics and set_frame_stamps stamp every output of a frame with the same intrinsics, frame_id and the two timestamps (device_timestamp_ns, host_timestamp_ns; both Unix-epoch nanoseconds). Point cloud output varies by mode: FULL sends the raw sl::Mat pointer (no copy); HALF downsamples by 2 in each dimension. Handles reconnection on grab failure.
DoraTargets.cmake — Handles building or fetching dora-rs and generating the CXX bridge files. Two paths: local (DORA_ROOT_DIR) or git clone. Produces dora_node_api_cxx library and the node_bridge.cc glue.
scripts/build.sh — Configure/compile/install in one shell-free-callable step. Referenced by dataflow.yml, the Dockerfile and the README.
dataflow.yml — Example dora dataflow definition using the git: source format, pinned with tag: — dora 1.0 pins a source with the mutually exclusive tag:, rev: or branch:.
Dockerfile — Ubuntu 24.04 x86-64 build environment (CUDA 12.8, ZED SDK 5.2, Rust). No ARM64/Jetson image; build natively there. No camera needed; run the compile with --gpus all. Sets NVIDIA_DRIVER_CAPABILITIES=compute,utility,video — the video capability is what makes the container runtime mount NVDEC/NVENC, which libsl_zed.so links against. Rust lives at /usr/local/{rustup,cargo} rather than /root so the build can run as the invoking user. docker build -t dora-zed-build . && docker run --rm --gpus all --user "$(id -u):$(id -g)" -v "$PWD:/src" -v dora-zed-cargo:/usr/local/cargo/registry dora-zed-build.

Key APIs

dora C++ API (<dora-node-api.h>): init_dora_node(), dora_node.events->next(), event_type(), send_output_with_metadata(), new_metadata().
ZED SDK (<sl/Camera.hpp>): sl::Camera, sl::InitParameters, sl::RuntimeParameters, sl::Mat.
Output data is sent as raw byte slices (rust::Slice<const uint8_t>) with typed metadata (shape, dtype, encoding).

Tools

Issue tracker: Gitea. Use the Gitea MCP tools (mcp__gitea__*) to read and manage issues, pull requests, and other repository operations.

Rules

Do not mention AI tools in commit messages or documentation.

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