refactor open_vocab into yolo_onnx and yoloworld_onnx engines

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.

dataflow.yml

@@ -1,13 +1,18 @@
 nodes:
   - id: zed-camera
     git: ssh://git@gitea.liria.cl:5001/liria/dora-zed.git
+    git_checkout: v0.1.0
     build: mkdir -p build && cd build && cmake .. && make install
     path: bin/dora_zed
     inputs:
       tick: dora/timer/millis/100
-      # update_vocabulary: vocabulary-node/labels  # optional: send new comma-separated labels at runtime
     outputs:
       - image_bgr
-      - point_cloud
-      - camera_info
       - objects
+
+  - id: plot
+    git: https://github.com/dora-rs/dora-hub.git
+    build: pip install ./node-hub/opencv-plot
+    path: opencv-plot
+    inputs:
+      image: zed-camera/image_bgr