text: import cv2
  import numpy as np
  import dlib
  import time
  
  
  def extract_index_nparray(nparray):
      index = None
      for num in nparray[0]:
          index = num
          break
      return index
  
  
  img = cv2.imread("../images/aditya.jpg")
  img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  mask = np.zeros_like(img_gray)
  img2 = cv2.imread("../images/bradley_cooper.jpg")
  img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
  
  
  detector = dlib.get_frontal_face_detector()
  predictor = dlib.shape_predictor("../shape_predictor_68_face_landmarks.dat")
  height, width, channels = img2.shape
  img2_new_face = np.zeros((height, width, channels), np.uint8)
  
  
  
  
  # Face 1
  faces = detector(img_gray)
  for face in faces:
      landmarks = predictor(img_gray, face)
      landmarks_points = []
      for n in range(0, 68):
          x = landmarks.part(n).x
          y = landmarks.part(n).y
          landmarks_points.append((x, y))
  
  
      points = np.array(landmarks_points, np.int32)
      print(points)
      convexhull = cv2.convexHull(points)
      # cv2.polylines(img, [convexhull], True, (255, 0, 0), 3)
      cv2.fillConvexPoly(mask, convexhull, 255)
  
      face_image_1 = cv2.bitwise_and(img, img, mask=mask)
  
  # Delaunay triangulation
  rect = cv2.boundingRect(convexhull)
  subdiv = cv2.Subdiv2D(rect)
  subdiv.insert(landmarks_points)
  triangles = subdiv.getTriangleList()
  triangles = np.array(triangles, dtype=np.int32)
  
  indexes_triangles = []
  for t in triangles:
      pt1 = (t[0], t[1])
      pt2 = (t[2], t[3])
      pt3 = (t[4], t[5])
  
  
      index_pt1 = np.where((points == pt1).all(axis=1))
      index_pt1 = extract_index_nparray(index_pt1)
  
      index_pt2 = np.where((points == pt2).all(axis=1))
      index_pt2 = extract_index_nparray(index_pt2)
  
      index_pt3 = np.where((points == pt3).all(axis=1))
      index_pt3 = extract_index_nparray(index_pt3)
  
      if index_pt1 is not None and index_pt2 is not None and index_pt3 is not None:
          triangle = [index_pt1, index_pt2, index_pt3]
          indexes_triangles.append(triangle)
  
  
  
  # Face 2
  faces2 = detector(img2_gray)
  for face in faces2:
      landmarks = predictor(img2_gray, face)
      landmarks_points2 = []
      for n in range(0, 68):
          x = landmarks.part(n).x
          y = landmarks.part(n).y
          landmarks_points2.append((x, y))
  
  
      points2 = np.array(landmarks_points2, np.int32)
      convexhull2 = cv2.convexHull(points2)
  
  lines_space_mask = np.zeros_like(img_gray)
  lines_space_new_face = np.zeros_like(img2)
  # Triangulation of both faces
  for triangle_index in indexes_triangles:
      # Triangulation of the first face
      tr1_pt1 = landmarks_points[triangle_index[0]]
      tr1_pt2 = landmarks_points[triangle_index[1]]
      tr1_pt3 = landmarks_points[triangle_index[2]]
      triangle1 = np.array([tr1_pt1, tr1_pt2, tr1_pt3], np.int32)
  
  
      rect1 = cv2.boundingRect(triangle1)
      (x, y, w, h) = rect1
      cropped_triangle = img[y: y + h, x: x + w]
      cropped_tr1_mask = np.zeros((h, w), np.uint8)
  
  
      points = np.array([[tr1_pt1[0] - x, tr1_pt1[1] - y],
                         [tr1_pt2[0] - x, tr1_pt2[1] - y],
                         [tr1_pt3[0] - x, tr1_pt3[1] - y]], np.int32)
  
      cv2.fillConvexPoly(cropped_tr1_mask, points, 255)
  
      # Lines space
      cv2.line(lines_space_mask, tr1_pt1, tr1_pt2, 255)
      cv2.line(lines_space_mask, tr1_pt2, tr1_pt3, 255)
      cv2.line(lines_space_mask, tr1_pt1, tr1_pt3, 255)
      lines_space = cv2.bitwise_and(img, img, mask=lines_space_mask)
  
      # Triangulation of second face
      tr2_pt1 = landmarks_points2[triangle_index[0]]
      tr2_pt2 = landmarks_points2[triangle_index[1]]
      tr2_pt3 = landmarks_points2[triangle_index[2]]
      triangle2 = np.array([tr2_pt1, tr2_pt2, tr2_pt3], np.int32)
  
      rect2 = cv2.boundingRect(triangle2)
      (x, y, w, h) = rect2
  
      cropped_tr2_mask = np.zeros((h, w), np.uint8)
  
      points2 = np.array([[tr2_pt1[0] - x, tr2_pt1[1] - y],
                          [tr2_pt2[0] - x, tr2_pt2[1] - y],
                          [tr2_pt3[0] - x, tr2_pt3[1] - y]], np.int32)
  
      cv2.fillConvexPoly(cropped_tr2_mask, points2, 255)
  
      # Warp triangles
      points = np.float32(points)
      points2 = np.float32(points2)
      M = cv2.getAffineTransform(points, points2)
      warped_triangle = cv2.warpAffine(cropped_triangle, M, (w, h))
      warped_triangle = cv2.bitwise_and(warped_triangle, warped_triangle, mask=cropped_tr2_mask)
  
      # Reconstructing destination face
      img2_new_face_rect_area = img2_new_face[y: y + h, x: x + w]
      img2_new_face_rect_area_gray = cv2.cvtColor(img2_new_face_rect_area, cv2.COLOR_BGR2GRAY)
      _, mask_triangles_designed = cv2.threshold(img2_new_face_rect_area_gray, 1, 255, cv2.THRESH_BINARY_INV)
      warped_triangle = cv2.bitwise_and(warped_triangle, warped_triangle, mask=mask_triangles_designed)
  
      img2_new_face_rect_area = cv2.add(img2_new_face_rect_area, warped_triangle)
      img2_new_face[y: y + h, x: x + w] = img2_new_face_rect_area
  
  
  
  # Face swapped (putting 1st face into 2nd face)
  img2_face_mask = np.zeros_like(img2_gray)
  img2_head_mask = cv2.fillConvexPoly(img2_face_mask, convexhull2, 255)
  img2_face_mask = cv2.bitwise_not(img2_head_mask)
  
  
  img2_head_noface = cv2.bitwise_and(img2, img2, mask=img2_face_mask)
  result = cv2.add(img2_head_noface, img2_new_face)
  
  (x, y, w, h) = cv2.boundingRect(convexhull2)
  center_face2 = (int((x + x + w) / 2), int((y + y + h) / 2))
  
  seamlessclone = cv2.seamlessClone(result, img2, img2_head_mask, center_face2, cv2.NORMAL_CLONE)
  
  cv2.imshow("seamlessclone", seamlessclone)
  cv2.waitKey(0)
  
  
  
  cv2.destroyAllWindows()