github/deepface
1
1
Fork 0
mirror of https://github.com/serengil/deepface.git synced 2025-06-07 12:05:22 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #1326 from serengil/feat-task-3108-casting-confidence-to-float

Browse Source 
cast confidence to float
This commit is contained in:
Sefik Ilkin Serengil 2024-08-31 16:35:49 +01:00 committed by GitHub
commit a3088ac903
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 18 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

32
deepface/modules/detection.py
View File

@ -158,7 +158,7 @@ def extract_faces(
"left_eye": current_region.left_eye, "left_eye": current_region.left_eye,
"right_eye": current_region.right_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: if anti_spoofing is True:
@ -179,9 +179,11 @@ def extract_faces(
def detect_faces( def detect_faces(
detector_backend: str, img: np.ndarray, detector_backend: str,
align: bool = True, expand_percentage: int = 0, img: np.ndarray,
max_faces: Optional[int] = None align: bool = True,
expand_percentage: int = 0,
max_faces: Optional[int] = None,
) -> List[DetectedFace]: ) -> List[DetectedFace]:
""" """
Detect face(s) from a given image 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): if max_faces is not None and max_faces < len(facial_areas):
facial_areas = nlargest( facial_areas = nlargest(
max_faces, max_faces, facial_areas, key=lambda facial_area: facial_area.w * facial_area.h
facial_areas,
key=lambda facial_area: facial_area.w * facial_area.h
) )
return [ return [
@ -251,15 +251,20 @@ def detect_faces(
align=align, align=align,
expand_percentage=expand_percentage, expand_percentage=expand_percentage,
width_border=width_border, width_border=width_border,
height_border=height_border height_border=height_border,
) )
for facial_area in facial_areas for facial_area in facial_areas
] ]
def expand_and_align_face( def expand_and_align_face(
facial_area: FacialAreaRegion, img: np.ndarray, facial_area: FacialAreaRegion,
align: bool, expand_percentage: int, width_border: int, img: np.ndarray,
height_border: int) -> DetectedFace: align: bool,
expand_percentage: int,
width_border: int,
height_border: int,
) -> DetectedFace:
x = facial_area.x x = facial_area.x
y = facial_area.y y = facial_area.y
w = facial_area.w w = facial_area.w
@ -309,6 +314,7 @@ def expand_and_align_face(
confidence=confidence, confidence=confidence,
) )
def align_img_wrt_eyes( def align_img_wrt_eyes(
img: np.ndarray, img: np.ndarray,
left_eye: Union[list, tuple], left_eye: Union[list, tuple],
@ -337,9 +343,7 @@ def align_img_wrt_eyes(
center = (w // 2, h // 2) center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, angle, 1.0) M = cv2.getRotationMatrix2D(center, angle, 1.0)
img = cv2.warpAffine( img = cv2.warpAffine(
img, M, (w, h), img, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT, borderValue=(0, 0, 0)
flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_CONSTANT,
borderValue=(0,0,0)
) )
return img, angle return img, angle