github/deepface
1
1
Fork 0
mirror of https://github.com/serengil/deepface.git synced 2025-06-07 20:15:21 +00:00
Code Issues Packages Projects Releases Wiki Activity

model building simplified, region calculation sorted

Browse Source
This commit is contained in:
Sefik Ilkin Serengil 2024-03-17 11:52:55 +00:00
parent a13f37c7c9
commit ee63d8b902
1 changed files with 15 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

34
deepface/detectors/FastMtCnn.py
View File

@ -32,12 +32,10 @@ class FastMtCnnClient(Detector):
and len(detections) > 0 and len(detections) > 0
and not any(detection is None for detection in detections) # issue 1043 and not any(detection is None for detection in detections) # issue 1043
): ):
for current_detection in zip(*detections): for regions, confidence, eyes in zip(*detections):
x, y, w, h = xyxy_to_xywh(current_detection[0]) x, y, w, h = xyxy_to_xywh(regions)
confidence = current_detection[1] left_eye = eyes[0]
right_eye = eyes[1]
left_eye = current_detection[2][0]
right_eye = current_detection[2][1]
left_eye = tuple(int(i) for i in left_eye) left_eye = tuple(int(i) for i in left_eye)
right_eye = tuple(int(i) for i in right_eye) right_eye = tuple(int(i) for i in right_eye)
@ -70,21 +68,19 @@ class FastMtCnnClient(Detector):
"Please install using 'pip install facenet-pytorch' " "Please install using 'pip install facenet-pytorch' "
) from e ) from e
face_detector = fast_mtcnn( face_detector = fast_mtcnn(device="cpu")
image_size=160,
thresholds=[0.6, 0.7, 0.7], # MTCNN thresholds
post_process=True,
device="cpu",
select_largest=False, # return result in descending order
)
return face_detector return face_detector
def xyxy_to_xywh(xyxy: Union[list, tuple]) -> list: def xyxy_to_xywh(regions: Union[list, tuple]) -> tuple:
""" """
Convert xyxy format to xywh format. Convert (x1, y1, x2, y2) format to (x, y, w, h) format.
Args:
regions (list or tuple): facial area coordinates as x, y, x+w, y+h
Returns:
regions (tuple): facial area coordinates as x, y, w, h
""" """
x, y = xyxy[0], xyxy[1] x, y, x_plus_w, y_plus_h = regions[0], regions[1], regions[2], regions[3]
w = xyxy[2] - x + 1 w = x_plus_w - x
h = xyxy[3] - y + 1 h = y_plus_h - y
return [x, y, w, h] return (x, y, w, h)