diff --git a/frigate/detectors/openvino.py b/frigate/detectors/openvino.py
index e038048eb..a63dae317 100644
--- a/frigate/detectors/openvino.py
+++ b/frigate/detectors/openvino.py
@@ -9,49 +9,38 @@ logger = logging.getLogger(__name__)
 
 
 class OvDetector(DetectionApi):
-    def __init__(self, det_device=None, model_path=None, num_threads=1):
+    def __init__(self, det_device=None, model_config=None, num_threads=1):
         self.ov_core = ov.Core()
-        self.ov_model = self.ov_core.read_model(model_path)
+        self.ov_model = self.ov_core.read_model(model_config.path)
+
         self.interpreter = self.ov_core.compile_model(
             model=self.ov_model, device_name=det_device
         )
-        logger.info(f"Model Input Shape: {self.interpreter.input().shape}")
-        logger.info(f"Model Output Shape: {self.interpreter.output().shape}")
+        logger.info(f"Model Input Shape: {self.interpreter.input(0).shape}")
+        logger.info(f"Model Output Shape: {self.interpreter.output(0).shape}")
 
     def detect_raw(self, tensor_input):
-        tensor_transpose = np.reshape(tensor_input, self.interpreter.input().shape)
 
         infer_request = self.interpreter.create_infer_request()
-        results = infer_request.infer([tensor_transpose])
+        infer_request.infer([tensor_input])
 
-        # class_ids = self.interpreter.tensor(self.tensor_output_details[1]["index"])()[0]
-        # scores = self.interpreter.tensor(self.tensor_output_details[2]["index"])()[0]
-        # count = int(
-        #     self.interpreter.tensor(self.tensor_output_details[3]["index"])()[0]
-        # # )
-
-        # class_ids = results[0, 0, :, 1]
-        # # class_ids = [0, 0, 1, 1]
-        # print(class_ids)
-
-        # scores = results
-        # print(scores)
+        results = infer_request.get_output_tensor()
 
         detections = np.zeros((20, 6), np.float32)
-        # i = 0
-        # for object_detected in results["detection_out"][0, 0, :]:
-        #     if object_detected[2] < 0.1 or i == 20:
-        #         break
-        #     detections.append(
-        #         [
-        #             object_detected[1],
-        #             float(object_detected[2]),
-        #             object_detected[3],
-        #             object_detected[4],
-        #             object_detected[5],
-        #             object_detected[6],
-        #         ]
-        #     )
-        #     i += 1
+        i = 0
+        for object_detected in results.data[0, 0, :]:
+            if object_detected[0] != -1:
+                logger.debug(object_detected)
+            if object_detected[2] < 0.1 or i == 20:
+                break
+            detections[i] = [
+                object_detected[1],  # Label ID
+                float(object_detected[2]),  # Confidence
+                object_detected[4],  # y_min
+                object_detected[3],  # x_min
+                object_detected[6],  # y_max
+                object_detected[5],  # x_max
+            ]
+            i += 1
 
         return detections