make device configurable in OpenVINO inference

anomalib/deploy/inferencers/openvino_inferencer.py

@@ -37,6 +37,7 @@ def __init__(
         config: Union[str, Path, DictConfig, ListConfig],
         path: Union[str, Path, Tuple[bytes, bytes]],
         meta_data_path: Union[str, Path] = None,
+        device: Optional[str] = "CPU",
     ):
         # Check and load the configuration
         if isinstance(config, (str, Path)):
@@ -46,6 +47,7 @@ def __init__(
         else:
             raise ValueError(f"Unknown config type {type(config)}")
 
+        self.device = device
         self.input_blob, self.output_blob, self.network = self.load_model(path)
         self.meta_data = super()._load_meta_data(meta_data_path)
 
@@ -80,7 +82,7 @@ def load_model(self, path: Union[str, Path, Tuple[bytes, bytes]]):
 
         input_blob = next(iter(network.input_info))
         output_blob = next(iter(network.outputs))
-        executable_network = ie_core.load_network(network=network, device_name="CPU")
+        executable_network = ie_core.load_network(network=network, device_name=self.device)
 
         return input_blob, output_blob, executable_network
 

docs/source/tutorials/inference.rst

@@ -51,6 +51,8 @@ To run OpenVINO inference, first make sure that your model has been exported to
 | meta_data | True     | Path to the JSON file containing the model's meta data (e.g. normalization           |
 |           |          | parameters and anomaly score threshold).                                             |
 +-----------+----------+--------------------------------------------------------------------------------------+
+| device    | False    | Device on which OpenVINO will perform the computations (``CPU``, ``GPU`` or ``VPU``) |
++-----------+----------+--------------------------------------------------------------------------------------+
 
 For correct inference results, the ``meta_data`` argument should be specified and point to the ``meta_data.json`` file that was generated when exporting the OpenVINO IR model. The file is stored in the same folder as the ``.xml`` and ``.bin`` files of the model.
 

tools/inference/openvino_inference.py

@@ -40,6 +40,14 @@ def get_args() -> Namespace:
         default="classification",
         choices=["classification", "segmentation"],
     )
+    parser.add_argument(
+        "--device",
+        type=str,
+        required=False,
+        help="Hardware device on which the model will be deployed",
+        default="CPU",
+        choices=["CPU", "GPU", "VPU"],
+    )
     parser.add_argument(
         "--visualization_mode",
         type=str,
@@ -71,7 +79,9 @@ def infer() -> None:
     args = get_args()
 
     # Get the inferencer.
-    inferencer = OpenVINOInferencer(config=args.config, path=args.weights, meta_data_path=args.meta_data)
+    inferencer = OpenVINOInferencer(
+        config=args.config, path=args.weights, meta_data_path=args.meta_data, device=args.device
+    )
     visualizer = Visualizer(mode=args.visualization_mode, task=args.task)
 
     filenames = get_image_filenames(path=args.input)
@@ -86,7 +96,7 @@ def infer() -> None:
             )
 
         if args.output:
-            file_path = generate_output_image_filename(input_path=args.input, output_path=args.output)
+            file_path = generate_output_image_filename(input_path=filename, output_path=args.output)
             visualizer.save(file_path=file_path, image=output)
 
         # Show the image in case the flag is set by the user.