I modify your code to intake vid and process it.
How come the result is like this?

Face landmarks Detection

usage:

python facelandmarkdetect.py --shape-predictor shape_predictor_68_face_landmarks.dat --image images/face1.jpg

import the necessary packages

from imutils import face_utils
import numpy as np
import argparse
import os
import imutils
import dlib
import cv2
import matplotlib.pyplot as plt

construct the argument parser and parse the arguments

ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=False,
help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=False,
help="path to input image")
args = vars(ap.parse_args())

cwd = os.getcwd()
for filename in os.listdir('models'):
if filename == 'shape_predictor_68_face_landmarks.dat':
filepath = cwd + '\models\' + filename
else:
print("Oops...! File is not available.")
# cmd = "wget -c --progress=bar http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2"
# os.system(cmd)
exit(0)

initialize dlib's face detector (HOG-based) and then create

the facial landmark predictor

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(filepath)

load the input image, resize it, and convert it to grayscale

cap = cv2.VideoCapture(0)

while cap.isOpened():
ret, frame = cap.read()
if ret is True:
orig = frame
image = imutils.resize(frame, width=500)
gray = cv2.cvtColor(frame, 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('Landmark',image)

if cv2.waitKey(1) & 0xFF == ord('q'):
	cap.release()
	cv2.destroyAllWindows()
	break

thank you for your sharing.i want to know how to train the facial landmark