docs: clarify ONNX Runtime dependency and input handling
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.
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@@ -36,7 +36,7 @@ Camera and detection behavior is configured entirely through environment variabl
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- **`src/engines/zed_native.h/cc`** — `engines::ZedNative`: wraps ZED SDK's TensorRT-optimized object detection module.
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- **`src/engines/yolo_helpers.h`** — Header-only shared helpers used by the ONNX engine: `RawDetection`, `nms()`, `letterbox()`, `fuse_bbox()`, `backproject()`. Lives in `engines::detail` namespace.
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- **`src/engines/yolo_onnx.h/cc`** — `engines::YoloOnnx` / `YoloOnnxConfig`: closed-vocabulary detection for any single-input YOLO ONNX model (YOLOv8, YOLOv11, YOLOv5, etc.). Auto-detects output layout (`NC_FIRST` / `NC_LAST` / `NC_LAST_OBJ`) from tensor shape; override with `ZED_ONNX_OUTPUT_FORMAT`. Labels loaded from `ZED_ONNX_LABELS` or `ZED_ONNX_LABELS_FILE`.
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- **`src/main.cc`** — Dora event loop. Selects engine via `ZED_ENGINE` env var (`yolo_onnx`/`onnx` or `native`), holds a `std::unique_ptr<engines::Engine>`. Parses `ZED_PC_MODE` (`FULL`/`HALF`/`ROI`) once before the loop. On `tick` input: calls `camera.grab()` and `detector->detect()`, then sends `image_bgr`, `point_cloud`, `camera_info`, and `objects` outputs. Point cloud output varies by mode: `FULL` sends the raw `sl::Mat` pointer (no copy); `HALF` downsamples by 2 in each dimension; `ROI` emits only valid points within detected bounding boxes as a flat `[N, 4]` array. Handles reconnection on grab failure.
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- **`src/main.cc`** — Dora event loop. Selects engine via `ZED_ENGINE` env var (`yolo_onnx`/`onnx` or `native`), holds a `std::unique_ptr<engines::Engine>`. Parses `ZED_PC_MODE` (`FULL`/`HALF`/`ROI`) once before the loop. On any input event (intended to be driven by a tick timer; the id is not inspected): calls `camera.grab()` and `detector->detect()`, then sends `image_bgr`, `point_cloud`, `camera_info`, and `objects` outputs. Point cloud output varies by mode: `FULL` sends the raw `sl::Mat` pointer (no copy); `HALF` downsamples by 2 in each dimension; `ROI` emits only valid points within detected bounding boxes as a flat `[N, 4]` array. Handles reconnection on grab failure.
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- **`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.
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- **`dataflow.yml`** — Example dora dataflow definition using the `git:` source format.
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- **`scripts/export_yolo.py`** — PEP 723 uv script. Exports a standard YOLOv11 model to ONNX for closed-vocabulary detection. Run: `uv run scripts/export_yolo.py --model n --output-dir models/`.
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