Add ability to configure model input dtype (#14659)

* Add input type for dtype

* Add ability to manually enable TRT execution provider

* Formatting

frigate/detectors/detector_config.py

@@ -27,6 +27,11 @@ class InputTensorEnum(str, Enum):
     nhwc = "nhwc"
 
 
+class InputDTypeEnum(str, Enum):
+    float = "float"
+    int = "int"
+
+
 class ModelTypeEnum(str, Enum):
     ssd = "ssd"
     yolox = "yolox"
@@ -53,6 +58,9 @@ class ModelConfig(BaseModel):
     input_pixel_format: PixelFormatEnum = Field(
         default=PixelFormatEnum.rgb, title="Model Input Pixel Color Format"
     )
+    input_dtype: InputDTypeEnum = Field(
+        default=InputDTypeEnum.int, title="Model Input D Type"
+    )
     model_type: ModelTypeEnum = Field(
         default=ModelTypeEnum.ssd, title="Object Detection Model Type"
     )

frigate/detectors/plugins/onnx.py

@@ -54,7 +54,7 @@ class ONNXDetector(DetectionApi):
 
         logger.info(f"ONNX: {path} loaded")
 
-    def detect_raw(self, tensor_input):
+    def detect_raw(self, tensor_input: np.ndarray):
         model_input_name = self.model.get_inputs()[0].name
         tensor_output = self.model.run(None, {model_input_name: tensor_input})
 

frigate/object_detection.py

@@ -12,7 +12,11 @@ from setproctitle import setproctitle
 
 import frigate.util as util
 from frigate.detectors import create_detector
-from frigate.detectors.detector_config import BaseDetectorConfig, InputTensorEnum
+from frigate.detectors.detector_config import (
+    BaseDetectorConfig,
+    InputDTypeEnum,
+    InputTensorEnum,
+)
 from frigate.detectors.plugins.rocm import DETECTOR_KEY as ROCM_DETECTOR_KEY
 from frigate.util.builtin import EventsPerSecond, load_labels
 from frigate.util.image import SharedMemoryFrameManager
@@ -55,12 +59,15 @@ class LocalObjectDetector(ObjectDetector):
                 self.input_transform = tensor_transform(
                     detector_config.model.input_tensor
                 )
+
+            self.dtype = detector_config.model.input_dtype
         else:
             self.input_transform = None
+            self.dtype = InputDTypeEnum.int
 
         self.detect_api = create_detector(detector_config)
 
-    def detect(self, tensor_input, threshold=0.4):
+    def detect(self, tensor_input: np.ndarray, threshold=0.4):
         detections = []
 
         raw_detections = self.detect_raw(tensor_input)
@@ -77,9 +84,13 @@ class LocalObjectDetector(ObjectDetector):
         self.fps.update()
         return detections
 
-    def detect_raw(self, tensor_input):
+    def detect_raw(self, tensor_input: np.ndarray):
         if self.input_transform:
             tensor_input = np.transpose(tensor_input, self.input_transform)
+
+        if self.dtype == InputDTypeEnum.float:
+            tensor_input = tensor_input.astype(np.float32)
+
         return self.detect_api.detect_raw(tensor_input=tensor_input)
 
 

frigate/util/model.py

@@ -13,7 +13,7 @@ except ImportError:
 
 
 def get_ort_providers(
-    force_cpu: bool = False, openvino_device: str = "AUTO", requires_fp16: bool = False
+    force_cpu: bool = False, device: str = "AUTO", requires_fp16: bool = False
 ) -> tuple[list[str], list[dict[str, any]]]:
     if force_cpu:
         return (
@@ -38,7 +38,25 @@ def get_ort_providers(
             )
         elif provider == "TensorrtExecutionProvider":
             # TensorrtExecutionProvider uses too much memory without options to control it
-            pass
+            # so it is not enabled by default
+            if device == "Tensorrt":
+                os.makedirs(
+                    "/config/model_cache/tensorrt/ort/trt-engines", exist_ok=True
+                )
+                providers.append(provider)
+                options.append(
+                    {
+                        "arena_extend_strategy": "kSameAsRequested",
+                        "trt_fp16_enable": requires_fp16
+                        and os.environ.get("USE_FP_16", "True") != "False",
+                        "trt_timing_cache_enable": True,
+                        "trt_engine_cache_enable": True,
+                        "trt_timing_cache_path": "/config/model_cache/tensorrt/ort",
+                        "trt_engine_cache_path": "/config/model_cache/tensorrt/ort/trt-engines",
+                    }
+                )
+            else:
+                continue
         elif provider == "OpenVINOExecutionProvider":
             os.makedirs("/config/model_cache/openvino/ort", exist_ok=True)
             providers.append(provider)
@@ -46,7 +64,7 @@ def get_ort_providers(
                 {
                     "arena_extend_strategy": "kSameAsRequested",
                     "cache_dir": "/config/model_cache/openvino/ort",
-                    "device_type": openvino_device,
+                    "device_type": device,
                 }
             )
         elif provider == "CPUExecutionProvider":