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set left and right eye locations with respect to the person instead of observer

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This commit is contained in:
Sefik Ilkin Serengil 2024-03-24 16:34:28 +00:00
parent 2b5c139670
commit 745b4b8835
8 changed files with 26 additions and 21 deletions
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4
deepface/detectors/Dlib.py
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@ -88,11 +88,11 @@ class DlibClient(Detector):
shape = self.model["sp"](img, detection)
left_eye = (
right_eye = (
int((shape.part(2).x + shape.part(3).x) // 2),
int((shape.part(2).y + shape.part(3).y) // 2),
)
right_eye = (
left_eye = (
int((shape.part(0).x + shape.part(1).x) // 2),
int((shape.part(0).y + shape.part(1).y) // 2),
)

4
deepface/detectors/FastMtCnn.py
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@ -34,8 +34,8 @@ class FastMtCnnClient(Detector):
):
for regions, confidence, eyes in zip(*detections):
x, y, w, h = xyxy_to_xywh(regions)
left_eye = eyes[0]
right_eye = eyes[1]
right_eye = eyes[0]
left_eye = eyes[1]
left_eye = tuple(int(i) for i in left_eye)
right_eye = tuple(int(i) for i in right_eye)

4
deepface/detectors/MediaPipe.py
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@ -61,8 +61,8 @@ class MediaPipeClient(Detector):
y = int(bounding_box.ymin * img_height)
h = int(bounding_box.height * img_height)
left_eye = (int(landmarks[0].x * img_width), int(landmarks[0].y * img_height))
right_eye = (int(landmarks[1].x * img_width), int(landmarks[1].y * img_height))
right_eye = (int(landmarks[0].x * img_width), int(landmarks[0].y * img_height))
left_eye = (int(landmarks[1].x * img_width), int(landmarks[1].y * img_height))
# nose = (int(landmarks[2].x * img_width), int(landmarks[2].y * img_height))
# mouth = (int(landmarks[3].x * img_width), int(landmarks[3].y * img_height))
# right_ear = (int(landmarks[4].x * img_width), int(landmarks[4].y * img_height))

6
deepface/detectors/MtCnn.py
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@ -35,8 +35,10 @@ class MtCnnClient(Detector):
for current_detection in detections:
x, y, w, h = current_detection["box"]
confidence = current_detection["confidence"]
left_eye = current_detection["keypoints"]["left_eye"]
right_eye = current_detection["keypoints"]["right_eye"]
# mtcnn detector assigns left eye with respect to the observer
# but we are setting it with respect to the person itself
left_eye = current_detection["keypoints"]["right_eye"]
right_eye = current_detection["keypoints"]["left_eye"]
facial_area = FacialAreaRegion(
x=x,

13
deepface/detectors/OpenCv.py
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@ -112,15 +112,18 @@ class OpenCvClient(Detector):
eye_2 = eyes[1]
if eye_1[0] < eye_2[0]:
left_eye = eye_1
right_eye = eye_2
else:
left_eye = eye_2
right_eye = eye_1
left_eye = eye_2
else:
right_eye = eye_2
left_eye = eye_1
# -----------------------
# find center of eyes
left_eye = (int(left_eye[0] + (left_eye[2] / 2)), int(left_eye[1] + (left_eye[3] / 2)))
left_eye = (
int(left_eye[0] + (left_eye[2] / 2)),
int(left_eye[1] + (left_eye[3] / 2)),
)
right_eye = (
int(right_eye[0] + (right_eye[2] / 2)),
int(right_eye[1] + (right_eye[3] / 2)),

6
deepface/detectors/RetinaFace.py
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@ -34,9 +34,9 @@ class RetinaFaceClient(Detector):
x = detection[0]
w = detection[2] - x
# notice that these must be inverse for retinaface
left_eye = identity["landmarks"]["right_eye"]
right_eye = identity["landmarks"]["left_eye"]
# retinaface sets left and right eyes with respect to the person
left_eye = identity["landmarks"]["left_eye"]
right_eye = identity["landmarks"]["right_eye"]
# eyes are list of float, need to cast them tuple of int
left_eye = tuple(int(i) for i in left_eye)

8
deepface/detectors/Yolo.py
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@ -81,10 +81,10 @@ class YoloClient(Detector):
x, y, w, h = result.boxes.xywh.tolist()[0]
confidence = result.boxes.conf.tolist()[0]
# left_eye_conf = result.keypoints.conf[0][0]
# right_eye_conf = result.keypoints.conf[0][1]
left_eye = result.keypoints.xy[0][0].tolist()
right_eye = result.keypoints.xy[0][1].tolist()
# right_eye_conf = result.keypoints.conf[0][0]
# left_eye_conf = result.keypoints.conf[0][1]
right_eye = result.keypoints.xy[0][0].tolist()
left_eye = result.keypoints.xy[0][1].tolist()
# eyes are list of float, need to cast them tuple of int
left_eye = tuple(int(i) for i in left_eye)

2
deepface/detectors/YuNet.py
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@ -99,7 +99,7 @@ class YuNetClient(Detector):
{x, y}_{re, le, nt, rcm, lcm} stands for the coordinates of right eye,
left eye, nose tip, the right corner and left corner of the mouth respectively.
"""
(x, y, w, h, x_re, y_re, x_le, y_le) = list(map(int, face[:8]))
(x, y, w, h, x_le, y_le, x_re, y_re) = list(map(int, face[:8]))
# YuNet returns negative coordinates if it thinks part of the detected face
# is outside the frame.