Detect a simple face landmarks using Google's Mediapipe

image_test.py

import numpy
import math
import cv2
import mediapipe as mp

DESIRED_HEIGHT = 480
DESIRED_WIDTH = 480

localImages = [
	r'/home/guilherme/Projects/mediapipe/teste.png'
]

mp_face_mesh = mp.solutions.face_mesh
mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles

def resize_and_show(image):
	h, w = image.shape[:2]
	img = cv2.resize(
		image, 
		(DESIRED_WIDTH, math.floor(h/(w/DESIRED_WIDTH))) if h < w 
		else (math.floor(w/(h/DESIRED_HEIGHT)), DESIRED_HEIGHT)
	)
	cv2.imshow('Teste', img)
	cv2.waitKey(0)
	cv2.destroyAllWindows()

images = {name: cv2.imread(name) for name in localImages}

with mp_face_mesh.FaceMesh(
	static_image_mode=True,
	refine_landmarks=True,
	max_num_faces=2,
	min_detection_confidence=0.5
) as face_mesh:
	for name, image in images.items():
		results = face_mesh.process(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
		if not results.multi_face_landmarks:
			continue
		annot_image = image.copy()
		for face_landmarks in results.multi_face_landmarks:
			mp_drawing.draw_landmarks(
				image=annot_image,
				landmark_list=face_landmarks,
				connections=mp_face_mesh.FACEMESH_TESSELATION,
				landmark_drawing_spec=None,
				connection_drawing_spec=mp_drawing_styles.get_default_face_mesh_tesselation_style())
		resize_and_show(annot_image)