mirror of
https://github.com/blakeblackshear/frigate.git
synced 2024-11-21 19:07:46 +01:00
0592c8b0e2
* Initial commit that adds YOLOv5 and YOLOv8 support for OpenVINO detector * Fixed double inference bug with YOLOv5 and YOLOv8 * Modified documentation to mention YOLOv5 and YOLOv8 * Changes to pass lint checks * Change minimum threshold to improve model performance * Fix link * Clean up YOLO post-processing --------- Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
91 lines
2.6 KiB
Python
91 lines
2.6 KiB
Python
import logging
|
|
from enum import Enum
|
|
from typing import Dict, List, Optional, Tuple, Union, Literal
|
|
|
|
import matplotlib.pyplot as plt
|
|
from pydantic import BaseModel, Extra, Field, validator
|
|
from pydantic.fields import PrivateAttr
|
|
|
|
from frigate.util import load_labels
|
|
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class PixelFormatEnum(str, Enum):
|
|
rgb = "rgb"
|
|
bgr = "bgr"
|
|
yuv = "yuv"
|
|
|
|
|
|
class InputTensorEnum(str, Enum):
|
|
nchw = "nchw"
|
|
nhwc = "nhwc"
|
|
|
|
|
|
class ModelTypeEnum(str, Enum):
|
|
ssd = "ssd"
|
|
yolox = "yolox"
|
|
yolov5 = "yolov5"
|
|
yolov8 = "yolov8"
|
|
|
|
|
|
class ModelConfig(BaseModel):
|
|
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"
|
|
)
|
|
model_type: ModelTypeEnum = Field(
|
|
default=ModelTypeEnum.ssd, title="Object Detection Model Type"
|
|
)
|
|
_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", {}),
|
|
}
|
|
self._colormap = {}
|
|
|
|
def create_colormap(self, enabled_labels: set[str]) -> None:
|
|
"""Get a list of colors for enabled labels."""
|
|
cmap = plt.cm.get_cmap("tab10", len(enabled_labels))
|
|
|
|
for key, val in enumerate(enabled_labels):
|
|
self._colormap[val] = tuple(int(round(255 * c)) for c in cmap(key)[:3])
|
|
|
|
class Config:
|
|
extra = Extra.forbid
|
|
|
|
|
|
class BaseDetectorConfig(BaseModel):
|
|
# the type field must be defined in all subclasses
|
|
type: str = Field(default="cpu", title="Detector Type")
|
|
model: ModelConfig = Field(
|
|
default=None, title="Detector specific model configuration."
|
|
)
|
|
|
|
class Config:
|
|
extra = Extra.allow
|
|
arbitrary_types_allowed = True
|