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cast confidence to float

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This commit is contained in:
Sefik Ilkin Serengil 2024-08-31 14:17:10 +01:00
parent f3d0923fc4
commit a52d4f3869
1 changed files with 18 additions and 14 deletions
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32
deepface/modules/detection.py
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@ -158,7 +158,7 @@ def extract_faces(
"left_eye": current_region.left_eye,
"right_eye": current_region.right_eye,
},
"confidence": round(current_region.confidence, 2),
"confidence": round(float(current_region.confidence or 0), 2),
}
if anti_spoofing is True:
@ -179,9 +179,11 @@ def extract_faces(
def detect_faces(
detector_backend: str, img: np.ndarray,
align: bool = True, expand_percentage: int = 0,
max_faces: Optional[int] = None
detector_backend: str,
img: np.ndarray,
align: bool = True,
expand_percentage: int = 0,
max_faces: Optional[int] = None,
) -> List[DetectedFace]:
"""
Detect face(s) from a given image
@ -239,9 +241,7 @@ def detect_faces(
if max_faces is not None and max_faces < len(facial_areas):
facial_areas = nlargest(
max_faces,
facial_areas,
key=lambda facial_area: facial_area.w * facial_area.h
max_faces, facial_areas, key=lambda facial_area: facial_area.w * facial_area.h
)
return [
@ -251,15 +251,20 @@ def detect_faces(
align=align,
expand_percentage=expand_percentage,
width_border=width_border,
height_border=height_border
height_border=height_border,
)
for facial_area in facial_areas
]
def expand_and_align_face(
facial_area: FacialAreaRegion, img: np.ndarray,
align: bool, expand_percentage: int, width_border: int,
height_border: int) -> DetectedFace:
facial_area: FacialAreaRegion,
img: np.ndarray,
align: bool,
expand_percentage: int,
width_border: int,
height_border: int,
) -> DetectedFace:
x = facial_area.x
y = facial_area.y
w = facial_area.w
@ -309,6 +314,7 @@ def expand_and_align_face(
confidence=confidence,
)
def align_img_wrt_eyes(
img: np.ndarray,
left_eye: Union[list, tuple],
@ -337,9 +343,7 @@ def align_img_wrt_eyes(
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, angle, 1.0)
img = cv2.warpAffine(
img, M, (w, h),
flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT,
borderValue=(0,0,0)
img, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT, borderValue=(0, 0, 0)
)
return img, angle