dora-zed publishes camera data only. The two engines under src/engines/, the
objects output, the ZED_ENGINE/ZED_DETECTION_*/ZED_ONNX_* variables and the
ZED_PC_MODE=ROI crop are gone, along with the standalone engine test and the
model export script.
This drops the unconditional ONNX Runtime requirement from CMakeLists, the
Dockerfile and the install scripts, so the node now configures on a machine
with no ONNX Runtime — which is what blocked the Jetson build, since there is
no official ARM64 GPU binary.
zed_native is dropped rather than kept: it is bound to the live camera handle
and cannot run in a node that receives images over a dataflow. The removed
code remains reachable at tag v0.1.0.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y7g2cBJ5e3r15ZbJ9WZn8c
dora 1.0 runs a node's build command directly rather than through a shell, so
the mkdir/cd/&& sequence in dataflow.yml could not work. Move it to
scripts/build.sh and invoke that instead.
Default CMAKE_BUILD_TYPE to Release so DoraTargets.cmake picks the release
cargo profile and the binary does not link debug dora bindings.
Pin the dataflow source with tag: — 1.0 replaced git_checkout with the
mutually exclusive tag/rev/branch.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y7g2cBJ5e3r15ZbJ9WZn8c
The release tarball ships its CMake package files under lib/, but
onnxruntimeTargets.cmake resolves the library as <prefix>/lib64. Ubuntu
is multiarch, so CMake does not search lib64 for packages and ld.so does
not search /usr/local/lib64 at all, leaving find_package(onnxruntime)
failing on a stock install. Keep the libraries in lib64, move only the
package files to lib/cmake, and add lib64 to the linker path.
ONNX Runtime is a configure-time dependency for every build, not only
for the yolo_onnx engine. The event loop no longer inspects the input
id, so it grabs on any input rather than specifically on tick.
Deletes the yoloworld_onnx engine, the CLIP BPE tokenizer, the standalone
test binary and both export scripts. Drops the update_vocabulary input and
the yoloworld_onnx/open_vocab dispatch from main.cc, along with the now
unused Engine::set_labels. Documentation follows.
Split the monolithic open_vocab engine into two focused engines:
yolo_onnx (closed-vocabulary, any single-input YOLO ONNX) and
yoloworld_onnx (open-vocabulary YOLO-World with CLIP encoder).
Shared NMS/letterbox/fuse helpers extracted to yolo_helpers.h.
Add export_yolo.py script and separate test binaries for each engine.
- Add OpenVocab engine: YOLO-World ONNX detection with runtime
vocabulary via CLIP text embeddings (two-input model support)
- Add header-only C++ CLIP BPE tokenizer (no external deps)
- Add detect(cv::Mat) overload to OpenVocab for camera-free testing
- Add standalone test binary (test_open_vocab) using test/assets images
- Add export scripts for YOLO-World and CLIP text encoder (uv/PEP 723)
- Add installation scripts for Linux x64, ARM (Jetson), and Windows
- Update CMakeLists to use find_package(onnxruntime) instead of FetchContent
- Update README and AGENTS with env vars, setup workflow, and test usage
cristhian