Convert detectors to factory pattern, ability to set different model for each detector (#4635)

* refactor detectors

* move create_detector and DetectorTypeEnum

* fixed code formatting

* add detector model config models

* fix detector unit tests

* adjust SharedMemory size to largest detector model shape

* fix detector model config defaults

* enable auto-discovery of detectors

* simplify config

* simplify config changes further

* update detectors docs; detect detector configs dynamic

* add suggested changes

* remove custom detector doc

* fix grammar, adjust device defaults

frigate/config.py

@@ -9,7 +9,7 @@ from typing import Dict, List, Optional, Tuple, Union
 import matplotlib.pyplot as plt
 import numpy as np
 import yaml
-from pydantic import BaseModel, Extra, Field, validator
+from pydantic import BaseModel, Extra, Field, validator, parse_obj_as
 from pydantic.fields import PrivateAttr
 
 from frigate.const import (
@@ -32,8 +32,15 @@ from frigate.ffmpeg_presets import (
     parse_preset_output_record,
     parse_preset_output_rtmp,
 )
+from frigate.detectors import (
+    PixelFormatEnum,
+    InputTensorEnum,
+    ModelConfig,
+    DetectorConfig,
+)
 from frigate.version import VERSION
 
+
 logger = logging.getLogger(__name__)
 
 # TODO: Identify what the default format to display timestamps is
@@ -52,18 +59,6 @@ class FrigateBaseModel(BaseModel):
         extra = Extra.forbid
 
 
-class DetectorTypeEnum(str, Enum):
-    edgetpu = "edgetpu"
-    openvino = "openvino"
-    cpu = "cpu"
-
-
-class DetectorConfig(FrigateBaseModel):
-    type: DetectorTypeEnum = Field(default=DetectorTypeEnum.cpu, title="Detector Type")
-    device: str = Field(default="usb", title="Device Type")
-    num_threads: int = Field(default=3, title="Number of detection threads")
-
-
 class UIConfig(FrigateBaseModel):
     use_experimental: bool = Field(default=False, title="Experimental UI")
 
@@ -725,57 +720,6 @@ class DatabaseConfig(FrigateBaseModel):
     )
 
 
-class PixelFormatEnum(str, Enum):
-    rgb = "rgb"
-    bgr = "bgr"
-    yuv = "yuv"
-
-
-class InputTensorEnum(str, Enum):
-    nchw = "nchw"
-    nhwc = "nhwc"
-
-
-class ModelConfig(FrigateBaseModel):
-    path: Optional[str] = Field(title="Custom Object detection model path.")
-    labelmap_path: Optional[str] = Field(title="Label map for custom object detector.")
-    width: int = Field(default=320, title="Object detection model input width.")
-    height: int = Field(default=320, title="Object detection model input height.")
-    labelmap: Dict[int, str] = Field(
-        default_factory=dict, title="Labelmap customization."
-    )
-    input_tensor: InputTensorEnum = Field(
-        default=InputTensorEnum.nhwc, title="Model Input Tensor Shape"
-    )
-    input_pixel_format: PixelFormatEnum = Field(
-        default=PixelFormatEnum.rgb, title="Model Input Pixel Color Format"
-    )
-    _merged_labelmap: Optional[Dict[int, str]] = PrivateAttr()
-    _colormap: Dict[int, Tuple[int, int, int]] = PrivateAttr()
-
-    @property
-    def merged_labelmap(self) -> Dict[int, str]:
-        return self._merged_labelmap
-
-    @property
-    def colormap(self) -> Dict[int, Tuple[int, int, int]]:
-        return self._colormap
-
-    def __init__(self, **config):
-        super().__init__(**config)
-
-        self._merged_labelmap = {
-            **load_labels(config.get("labelmap_path", "/labelmap.txt")),
-            **config.get("labelmap", {}),
-        }
-
-        cmap = plt.cm.get_cmap("tab10", len(self._merged_labelmap.keys()))
-
-        self._colormap = {}
-        for key, val in self._merged_labelmap.items():
-            self._colormap[val] = tuple(int(round(255 * c)) for c in cmap(key)[:3])
-
-
 class LogLevelEnum(str, Enum):
     debug = "debug"
     info = "info"
@@ -890,7 +834,7 @@ class FrigateConfig(FrigateBaseModel):
         default_factory=ModelConfig, title="Detection model configuration."
     )
     detectors: Dict[str, DetectorConfig] = Field(
-        default={name: DetectorConfig(**d) for name, d in DEFAULT_DETECTORS.items()},
+        default=DEFAULT_DETECTORS,
         title="Detector hardware configuration.",
     )
     logger: LoggerConfig = Field(
@@ -1032,6 +976,33 @@ class FrigateConfig(FrigateBaseModel):
             # generate the ffmpeg commands
             camera_config.create_ffmpeg_cmds()
             config.cameras[name] = camera_config
+
+        for key, detector in config.detectors.items():
+            detector_config: DetectorConfig = parse_obj_as(DetectorConfig, detector)
+            if detector_config.model is None:
+                detector_config.model = config.model
+            else:
+                model = detector_config.model
+                schema = ModelConfig.schema()["properties"]
+                if (
+                    model.width != schema["width"]["default"]
+                    or model.height != schema["height"]["default"]
+                    or model.labelmap_path is not None
+                    or model.labelmap is not {}
+                    or model.input_tensor != schema["input_tensor"]["default"]
+                    or model.input_pixel_format
+                    != schema["input_pixel_format"]["default"]
+                ):
+                    logger.warning(
+                        "Customizing more than a detector model path is unsupported."
+                    )
+            merged_model = deep_merge(
+                detector_config.model.dict(exclude_unset=True),
+                config.model.dict(exclude_unset=True),
+            )
+            detector_config.model = ModelConfig.parse_obj(merged_model)
+            config.detectors[key] = detector_config
+
         return config
 
     @validator("cameras")