Python中的人脸对齐与DNN人脸检测器
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【中文标题】Python中的人脸对齐与DNN人脸检测器【英文标题】:Face alignment in Python with DNN face detector 【发布时间】:2020-12-15 08:34:36 【问题描述】:我正在尝试在 python 中进行人脸对齐代码。我正在关注此article,但在本文中使用了人脸检测 dlib。以下是原代码:
from imutils.face_utils import FaceAligner
from imutils.face_utils import rect_to_bb
import argparse
import imutils
import dlib
import cv2
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')
fa = FaceAligner(predictor, desiredFaceWidth=256)
image = cv2.imread('images\\1.jpg')
image = imutils.resize(image, width=300)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 2)
for rect in rects:
(x, y, w, h) = rect_to_bb(rect)
faceOrig = imutils.resize(image[y:y + h, x:x + w], width=256)
faceAligned = fa.align(image, gray, rect) # Here we get the aligned face
我有一些人脸图像没有被 dlib 人脸检测器检测到。所以我正在修改上面的代码并使用 DNN 人脸检测。以下是我的代码:
from imutils.face_utils import FaceAligner
from imutils.face_utils import rect_to_bb
import argparse
import imutils
import dlib
import cv2
protoPath = "deploy.prototxt"
modelPath = "res10_300x300_ssd_iter_140000.caffemodel"
detector = cv2.dnn.readNetFromCaffe(protoPath, modelPath)
fa = FaceAligner(predictor, desiredFaceWidth=256)
image = cv2.imread('images\\1.jpg')
image = imutils.resize(image, width=300)
(h, w) = image.shape[:2]
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
imageBlob = cv2.dnn.blobFromImage(cv2.resize(image, (300, 300)), 1.0, (300, 300), (104.0, 177.0, 123.0), swapRB=False, crop=False)
detector.setInput(imageBlob)
detections = detector.forward()
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
face = image[startY:endY, startX:endX]
gray = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
r = dlib.rectangle(int(startX), int(startY), int(endX), int(endY))
faceAligned = fa.align(face, gray, r)
但是在上面的代码中faceAligned
是全零,因此是一个空白图像。我不确定我做错了什么。谁能指出错误并帮助我解决问题。请帮忙。谢谢
【问题讨论】:
【参考方案1】:我建议您在 deepface 中执行此操作。它封装了opencv、ssd、dlib和mtcnn来检测和对齐人脸。
detectFace 函数分别在后台应用检测和对齐。
#!pip install deepface
from deepface import DeepFace
backends = ['opencv', 'ssd', 'dlib', 'mtcnn']
DeepFace.detectFace("img.jpg", detector_backend = backends[2])
此外,您可以手动应用检测和对齐。
from deepface.commons import functions
img = functions.load_image("img.jpg")
backends = ['opencv', 'ssd', 'dlib', 'mtcnn']
detected_face = functions.detect_face(img = img, detector_backend = backends[2])
plt.imshow(detected_face)
aligned_face = functions.align_face(img = img, detector_backend = backends[2])
plt.imshow(aligned_face)
processed_img = functions.detect_face(img = aligned_face, detector_backend = backends[2])
plt.imshow(processed_img)
如果您打算应用人脸识别,它也会在后台处理这些预处理步骤。
from deepface import DeepFace
DeepFace.verify("img1.jpg", "img2.jpg", detector_backend = 'dlib')
【讨论】:
【参考方案2】:您将人脸和灰色裁剪图像传递给 fa.align(face, gray, r),正如您在第一个代码中显示的那样,此参数必须是完整图像和矩形。这是完整的示例:
import numpy as np
import imutils
import dlib
import cv2
from imutils.face_utils import FaceAligner
protoPath = "path/to/deploy.prototxt.txt"
modelPath = "path/to/res10_300x300_ssd_iter_140000.caffemodel"
detector = cv2.dnn.readNetFromCaffe(protoPath, modelPath)
predictor = dlib.shape_predictor("path/to/shape_predictor_68_face_landmarks.dat")
fa = FaceAligner(predictor, desiredFaceWidth=256)
image = cv2.imread('path/to/image.jpg')
image = imutils.resize(image, width=300)
cv2.imshow("image", image)
(h, w) = image.shape[:2]
rgb = image.copy()
grey = cv2.cvtColor(rgb, cv2.COLOR_BGR2GRAY)
imageBlob = cv2.dnn.blobFromImage(rgb, 1.0, (300, 300), (104.0, 177.0, 123.0), swapRB=False, crop=False)
detector.setInput(imageBlob)
detections = detector.forward()
for i in range(0, detections.shape[2]):
confidence = detections[0, 0, i, 2]
if confidence > 0.5:
box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
(startX, startY, endX, endY) = box.astype("int")
face = image[startY:endY, startX:endX]
r = dlib.rectangle(int(startX), int(startY), int(endX), int(endY))
faceAligned = fa.align(rgb, grey, r)
cv2.imshow("FACE ALIGNED :d".format(i), faceAligned)
k = cv2.waitKey(0)
if k == 27:
cv2.destroyAllWindows()
祝你好运。
【讨论】:
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