mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
0d16bd0144
* add false positive submission * switch timeline events to x,y,w,h * update docs * fix type checks * convert to upsert * fix config test
104 lines
3.0 KiB
Python
104 lines
3.0 KiB
Python
import hashlib
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import logging
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from enum import Enum
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from typing import Dict, List, Optional, Tuple, Union, Literal
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import matplotlib.pyplot as plt
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from pydantic import BaseModel, Extra, Field, validator
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from pydantic.fields import PrivateAttr
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from frigate.util import load_labels
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logger = logging.getLogger(__name__)
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class PixelFormatEnum(str, Enum):
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rgb = "rgb"
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bgr = "bgr"
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yuv = "yuv"
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class InputTensorEnum(str, Enum):
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nchw = "nchw"
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nhwc = "nhwc"
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class ModelTypeEnum(str, Enum):
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ssd = "ssd"
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yolox = "yolox"
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yolov5 = "yolov5"
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yolov8 = "yolov8"
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class ModelConfig(BaseModel):
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path: Optional[str] = Field(title="Custom Object detection model path.")
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labelmap_path: Optional[str] = Field(title="Label map for custom object detector.")
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width: int = Field(default=320, title="Object detection model input width.")
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height: int = Field(default=320, title="Object detection model input height.")
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labelmap: Dict[int, str] = Field(
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default_factory=dict, title="Labelmap customization."
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)
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input_tensor: InputTensorEnum = Field(
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default=InputTensorEnum.nhwc, title="Model Input Tensor Shape"
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)
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input_pixel_format: PixelFormatEnum = Field(
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default=PixelFormatEnum.rgb, title="Model Input Pixel Color Format"
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)
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model_type: ModelTypeEnum = Field(
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default=ModelTypeEnum.ssd, title="Object Detection Model Type"
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)
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_merged_labelmap: Optional[Dict[int, str]] = PrivateAttr()
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_colormap: Dict[int, Tuple[int, int, int]] = PrivateAttr()
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_model_hash: str = PrivateAttr()
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@property
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def merged_labelmap(self) -> Dict[int, str]:
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return self._merged_labelmap
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@property
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def colormap(self) -> Dict[int, Tuple[int, int, int]]:
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return self._colormap
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@property
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def model_hash(self) -> str:
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return self._model_hash
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def __init__(self, **config):
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super().__init__(**config)
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self._merged_labelmap = {
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**load_labels(config.get("labelmap_path", "/labelmap.txt")),
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**config.get("labelmap", {}),
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}
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self._colormap = {}
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def compute_model_hash(self) -> None:
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with open(self.path, "rb") as f:
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file_hash = hashlib.md5()
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while chunk := f.read(8192):
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file_hash.update(chunk)
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self._model_hash = file_hash.hexdigest()
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def create_colormap(self, enabled_labels: set[str]) -> None:
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"""Get a list of colors for enabled labels."""
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cmap = plt.cm.get_cmap("tab10", len(enabled_labels))
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for key, val in enumerate(enabled_labels):
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self._colormap[val] = tuple(int(round(255 * c)) for c in cmap(key)[:3])
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class Config:
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extra = Extra.forbid
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class BaseDetectorConfig(BaseModel):
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# the type field must be defined in all subclasses
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type: str = Field(default="cpu", title="Detector Type")
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model: ModelConfig = Field(
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default=None, title="Detector specific model configuration."
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)
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class Config:
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extra = Extra.allow
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arbitrary_types_allowed = True
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