feat(detectors): add Qualcomm Hexagon NPU support (community board)

Add a community-supported board build for Qualcomm SoCs with a Hexagon
NPU, accelerating TFLite object detection through the QNN TFLite delegate
on the Hexagon Tensor Processor (HTP).

Supported boards:
- IQ9100 (IQ-9075 EVK)
- QCS6490 (RB3 Gen 2 Vision Kit / Rubik Pi 3)

- detector: new `qualcomm_tfl` plugin loading libQnnTFLiteDelegate.so on
  the HTP backend, reusing the shared TFLite delegate helpers
- docker: `docker/qualcomm` board build (Dockerfile, qualcomm.hcl,
  qualcomm.mk) producing the arm64 `-qualcomm` image
- cdi: per-board Container Device Interface descriptors and an install
  helper exposing the NPU device nodes and QNN libraries to the container
- ci/codeowners: register the qualcomm build target and code owner
- docs: installation, hardware, and object detector documentation, using
  the shared model config dropdown component
- i18n: add the Qualcomm detector label and description to the generated
  en config locale

Signed-off-by: Rami Mouro <rmouro@qti.qualcomm.com>

docs/data/object_detectors_models.json

@@ -265,6 +265,19 @@
       }
     ]
   },
+  "qualcomm": {
+    "title": "Qualcomm",
+    "models": [
+      {
+        "key": "ssd_mobiledet",
+        "label": "SSD MobileDet",
+        "recommended": true,
+        "download": "The default SSD MobileDet TFLite model (`/cpu_model.tflite`) bundled with the Frigate container is used automatically. This model is INT8 quantized and compatible with the QNN HTP backend.\n\nOnly `.tflite` models are supported with this detector. A custom model must be INT8 quantized for the Hexagon NPU.",
+        "ui": "Navigate to **Settings > System > Detectors and model** and select **Qualcomm** from the detector type dropdown and click **Add**. The bundled SSD MobileDet model is used automatically.\n\nTo use a custom model, configure in the **Custom Model** tab:\n\n| Field                                    | Value                              |\n| ---------------------------------------- | ---------------------------------- |\n| **Custom object detector model path**    | `/config/your_custom_model.tflite` |\n| **Object detection model input width**   | `320`                              |\n| **Object detection model input height**  | `320`                              |\n| **Label map for custom object detector** | `/labelmap/coco-80.txt`            |",
+        "yaml": "detectors:\n  qualcomm_npu:\n    type: qualcomm_tfl"
+      }
+    ]
+  },
   "rknn": {
     "title": "RKNN",
     "models": [