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90 lines
2.8 KiB
Python
90 lines
2.8 KiB
Python
from typing import List, Tuple, Optional
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from abc import ABC, abstractmethod
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import numpy as np
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# Notice that all facial detector models must be inherited from this class
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# pylint: disable=unnecessary-pass, too-few-public-methods
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class Detector(ABC):
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@abstractmethod
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def detect_faces(self, img: np.ndarray) -> List["FacialAreaRegion"]:
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"""
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Interface for detect and align face
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Args:
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img (np.ndarray): pre-loaded image as numpy array
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Returns:
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results (List[FacialAreaRegion]): A list of FacialAreaRegion objects
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where each object contains:
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- facial_area (FacialAreaRegion): The facial area region represented
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as x, y, w, h, left_eye and right_eye. left eye and right eye are
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eyes on the left and right respectively with respect to the person
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instead of observer.
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"""
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pass
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class FacialAreaRegion:
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x: int
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y: int
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w: int
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h: int
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left_eye: Tuple[int, int]
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right_eye: Tuple[int, int]
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confidence: float
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def __init__(
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self,
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x: int,
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y: int,
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w: int,
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h: int,
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left_eye: Optional[Tuple[int, int]] = None,
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right_eye: Optional[Tuple[int, int]] = None,
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confidence: Optional[float] = None,
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):
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"""
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Initialize a Face object.
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Args:
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x (int): The x-coordinate of the top-left corner of the bounding box.
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y (int): The y-coordinate of the top-left corner of the bounding box.
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w (int): The width of the bounding box.
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h (int): The height of the bounding box.
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left_eye (tuple): The coordinates (x, y) of the left eye with respect to
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the person instead of observer. Default is None.
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right_eye (tuple): The coordinates (x, y) of the right eye with respect to
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the person instead of observer. Default is None.
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confidence (float, optional): Confidence score associated with the face detection.
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Default is None.
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"""
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self.x = x
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self.y = y
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self.w = w
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self.h = h
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self.left_eye = left_eye
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self.right_eye = right_eye
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self.confidence = confidence
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class DetectedFace:
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img: np.ndarray
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facial_area: FacialAreaRegion
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confidence: float
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def __init__(self, img: np.ndarray, facial_area: FacialAreaRegion, confidence: float):
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"""
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Initialize detected face object.
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Args:
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img (np.ndarray): detected face image as numpy array
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facial_area (FacialAreaRegion): detected face's metadata (e.g. bounding box)
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confidence (float): confidence score for face detection
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"""
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self.img = img
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self.facial_area = facial_area
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self.confidence = confidence
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