Could not build wheels for dlib, which is required to install pyproject.toml-based projects

[githubUser01946]

When I follow your readme to install the imlib I receive the error in the title. I have pasted it on pastebin as it's huge.

https://pastebin.com/PDJVzYM2

[SyedKasina]

Before installing dlib . You need to install some c++ library tools.

CMake: This is because dlib was developed in C based programming language, so it needs this program to use it. It can be found in the link https://cmake.org/download/. To make sure matching with your operating system, in our case is Windows 10 64-bit version.

Visual studio: As I mentioned before, dlib is C based programming language. Another thing that really need is compiler. The Visual studio can be downloaded in the link https://visualstudio.microsoft.com/visual-cpp-build-tools/. After finishing the installation, you need to install additional packages for C, C++ programming, which is Packages CMake tools for Windows.

[nmww]

# import the necessary packages
import numpy as np
from imutils import face_utils
import dlib
import cv2
 
# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
# pip install numpy opencv-python dlib imutils
p = "shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(p)

cap = cv2.VideoCapture(0)
 
while True:
    # load the input image and convert it to grayscale
    _, image = cap.read()
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        
    # detect faces in the grayscale image
    rects = detector(gray, 0)
    image = np.zeros((500, 500, 3), dtype="uint8")  # 尺寸可以根据需要调整

    # 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)
    
        # 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), 3, (0, 255, 0), -1)
    
    # show the output image with the face detections + facial landmarks
    cv2.imshow("Output", image)
    k = cv2.waitKey(5) & 0xFF
    if k == 27:
        break

cv2.destroyAllWindows()
cap.release()

`