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Add a black border around an image to avoid moving faces outside after alignment

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Sefik Ilkin Serengil 2024-06-02 20:33:51 +01:00
parent 188e15c177
commit 578f3e3dff
1 changed files with 17 additions and 0 deletions
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17
deepface/detectors/DetectorWrapper.py
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@ -1,5 +1,6 @@
from typing import Any, List, Tuple from typing import Any, List, Tuple
import numpy as np import numpy as np
import cv2
from deepface.modules import detection from deepface.modules import detection
from deepface.models.Detector import Detector, DetectedFace, FacialAreaRegion from deepface.models.Detector import Detector, DetectedFace, FacialAreaRegion
from deepface.detectors import ( from deepface.detectors import (
@ -84,6 +85,8 @@ def detect_faces(
- confidence (float): The confidence score associated with the detected face. - confidence (float): The confidence score associated with the detected face.
""" """
height, width, _ = img.shape
face_detector: Detector = build_model(detector_backend) face_detector: Detector = build_model(detector_backend)
# validate expand percentage score # validate expand percentage score
@ -94,6 +97,19 @@ def detect_faces(
) )
expand_percentage = 0 expand_percentage = 0
# If faces are close to the upper boundary, alignment move them outside
# Add a black border around an image to avoid this.
if align is True:
img = cv2.copyMakeBorder(
img,
int(0.5 * height),
int(0.5 * height),
int(0.5 * width),
int(0.5 * width),
cv2.BORDER_CONSTANT,
value=[0, 0, 0], # Color of the border (black)
)
# find facial areas of given image # find facial areas of given image
facial_areas = face_detector.detect_faces(img) facial_areas = face_detector.detect_faces(img)
@ -126,6 +142,7 @@ def detect_faces(
aligned_img, angle = detection.align_face( aligned_img, angle = detection.align_face(
img=img, left_eye=left_eye, right_eye=right_eye img=img, left_eye=left_eye, right_eye=right_eye
) )
rotated_x1, rotated_y1, rotated_x2, rotated_y2 = rotate_facial_area( rotated_x1, rotated_y1, rotated_x2, rotated_y2 = rotate_facial_area(
facial_area=(x, y, x + w, y + h), angle=angle, size=(img.shape[0], img.shape[1]) facial_area=(x, y, x + w, y + h), angle=angle, size=(img.shape[0], img.shape[1])
) )