Greeting, I have been trying to extract some regions from the face In this case (upper lip) using Dlib, the thing is after extracting the ROI (which look perfect) I realized that there is some noise around the ROI Can't figure out what I'm doing wrong, and how to resolve this issue. This is the used Python code:
import cv2
import numpy as np
import dlib
import os
from scipy import ndimage, misc
import time
def extract_index_nparray(nparray):
index = None
for num in nparray[0]:
index = num
break
return index
img = cv2.imread( 'input_facial_image.jpg')
img=cv2.resize(img,(512,512))
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
mask = np.zeros_like(img_gray)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("/facial-landmarks-recognition/shape_predictor_68_face_landmarks.dat")
# Face 1
faces = detector(img_gray)
for face in faces:
landmarks = predictor(img_gray, face)
landmarks_points = []
for n in [48,49,50,51,52,53,54,64,63,62,61,60]:
x = landmarks.part(n).x
y = landmarks.part(n).y
landmarks_points.append((x, y))
points = np.array(landmarks_points, np.int32)
convexhull = cv2.convexHull(points)
# cv2.polylines(img, [convexhull], True, (255, 0, 0), 3)
cv2.fillConvexPoly(mask, convexhull, 255)
face_image_1 = cv2.bitwise_or(img, img, mask=mask)
cv2.imwrite('extracted_lips.jpg', face_image_1 )
The extracted image looks like this : upper lips extracted image But in further steps in my work, I realized a noise around the upper lip, so I examined and I found unclean_upperlip Is there any way to get rid of the noise during the ROI extracting or any image processing technique to bypass this issue? Thanks in advance
For anyone who faced the same issue as me, it's simple. Just change the output format to png. The JPG compressing is the issue here.
I hope that this helps
