Harden operator YOLO training runtime

scripts/train_operator_yolo_detector.sh

@@ -21,6 +21,7 @@ Environment variables:
   TRAIN_BATCH                  Batch size. Default: 2
   TRAIN_WORKERS                Data-loader workers. Default: 0
   TRAIN_DEVICE                 Device passed to Ultralytics. Default: cpu
+  PYTHON_BIN                   Python executable. Default: python3
 
 This helper is an operator/runtime smoke wrapper. It requires an existing local
 base model and an existing local dataset.yaml. It does not create app features.
@@ -42,6 +43,7 @@ TRAIN_IMGSZ="${TRAIN_IMGSZ:-512}"
 TRAIN_BATCH="${TRAIN_BATCH:-2}"
 TRAIN_WORKERS="${TRAIN_WORKERS:-0}"
 TRAIN_DEVICE="${TRAIN_DEVICE:-cpu}"
+PYTHON_BIN="${PYTHON_BIN:-python3}"
 
 DATASET_YAML="${OPERATOR_YOLO_DATASET_DIR%/}/dataset.yaml"
 SUMMARY_PATH="${TRAIN_OUTPUT_DIR%/}/${TRAIN_RUN_NAME}/training_summary.json"
@@ -55,6 +57,7 @@ export TRAIN_IMGSZ
 export TRAIN_BATCH
 export TRAIN_WORKERS
 export TRAIN_DEVICE
+export PYTHON_BIN
 export SUMMARY_PATH
 
 if [[ ! -f "${DATASET_YAML}" ]]; then
@@ -69,7 +72,7 @@ fi
 
 mkdir -p "${TRAIN_OUTPUT_DIR}" "$(dirname "${TRAIN_MODEL_OUTPUT_PATH}")"
 
-python - <<'PY'
+"${PYTHON_BIN}" - <<'PY'
 from __future__ import annotations
 
 import json