python dlib-读取图像而不是网络摄像头

似乎你在要求 在OpenCV中读取图像 .

假设你正在运行 脚本语言 从同一文件夹 文件段 存储,只需键入:

img = cv2.imread("image.jpg")

当然,因为你只读了一次图像,就不需要再做一个while循环了。

以下是完整的工作代码:

from imutils import face_utils
import dlib
import cv2

p = "shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(p)

image = cv2.imread("image.jpg")    
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)    
rects = detector(gray, 0)

for (i, rect) in enumerate(rects):
    shape = predictor(gray, rect)
    shape = face_utils.shape_to_np(shape)
    for (x, y) in shape:
        cv2.circle(image, (x, y), 2, (0, 255, 0), -1)

cv2.imshow("Output", image)
cv2.waitKey(0)

cv2.destroyAllWindows()

视频基本上是一组图像流,它们的移动速度比我们的眼睛所能检测到的要快。因此,对于您的查询,除了while循环部分,代码几乎保持不变。

from imutils import face_utils
import dlib
import cv2

# Vamos inicializar um detector de faces (HOG) para então
# let's go code an faces detector(HOG) and after detect the 
# landmarks on this detected face

# p = our pre-treined model directory, on my case, it's on the same script's diretory.
p = "shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(p)

cap = cv2.VideoCapture(0)

#while True:
# Getting out image by webcam 
image = #load your image here
# Converting the image to gray scale
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# Get faces into webcam's image
rects = detector(gray, 0)

# For each detected face, find the landmark.
for (i, rect) in enumerate(rects):
# Make the prediction and transfom it to numpy array
    shape = predictor(gray, rect)
    shape = face_utils.shape_to_np(shape)

    # Draw on our image, all the finded cordinate points (x,y) 
    for (x, y) in shape:
        cv2.circle(image, (x, y), 2, (0, 255, 0), -1)

# Show the image
cv2.imshow("Output", image)

k = cv2.waitKey(5) & 0xFF
if k == 27:
    break

#cv2.destroyAllWindows()
#cap.release()