Question

我正在尝试使用DLIB的地标裁剪图像。

我尝试用numpy数组制作自己的形状
我尝试在stackexchange或其他github上使用其他示例，但没有成功
https://www.pyimagesearch.com/2017/04/03/facial-landmarks-dlib-opencv-python/没有成功

我已经对程序的大部分代码进行了编码，这些程序都可以正常工作，但是在过去的一周中，这部分一直很困难。我需要4个（x，y，）坐标。

https://i.stack.imgur.com/05uIT.jpg

我需要在坐标34、37和46上放置“参考框架”矩形；然后，我需要在每个轴上添加+ n的额外填充。

任何帮助将不胜感激！

# USAGE
# python facial_landmarks.py --shape-predictor shape_predictor_68_face_landmarks.dat --image images/example_01.jpg 

# import the necessary packages
from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
    help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
    help="path to input image")
args = vars(ap.parse_args())

# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

# load the input image, resize it, and convert it to grayscale
image = cv2.imread(args["image"])
image = imutils.resize(image, width=500)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# detect faces in the grayscale image
rects = detector(gray, 1)

# loop over the face detections
for (i, rect) in enumerate(rects):
    # determine the facial landmarks for the face region, then
    # convert the facial landmark (x, y)-coordinates to a NumPy
    # array
    shape = predictor(gray, rect)
    shape = face_utils.shape_to_np(shape)

    # convert dlib's rectangle to a OpenCV-style bounding box
    # [i.e., (x, y, w, h)], then draw the face bounding box
    (x, y, w, h) = face_utils.rect_to_bb(rect)
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

    # show the face number
    cv2.putText(image, "Face #{}".format(i + 1), (x - 10, y - 10),
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

    # loop over the (x, y)-coordinates for the facial landmarks
    # and draw them on the image
    for (x, y) in shape:
        cv2.circle(image, (x, y), 1, (0, 0, 255), -1)

# show the output image with the face detections + facial landmarks
cv2.imshow("Output", image)
cv2.waitKey(0)

Answer 1

面部界标存储在shape中。例如，shape[0][0]是第一个点的x坐标，shape[0][1]是第一个点的y坐标，依此类推。如果要在坐标34、37和46上绘制矩形：

cv2.rectangle(image,(shape[36][0], shape[36][1]), (shape[45][0],shape[33][1]), (255,0,0), 1)

Python Dlib使用面部地标进行裁剪

1 个答案: