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sample_facemesh.py
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sample_facemesh.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import copy
import argparse
import cv2 as cv
import numpy as np
import mediapipe as mp
from utils import CvFpsCalc
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--device", type=int, default=0)
parser.add_argument("--width", help='cap width', type=int, default=960)
parser.add_argument("--height", help='cap height', type=int, default=540)
parser.add_argument("--max_num_faces", type=int, default=1)
parser.add_argument('--refine_landmarks', action='store_true')
parser.add_argument("--min_detection_confidence",
help='min_detection_confidence',
type=float,
default=0.7)
parser.add_argument("--min_tracking_confidence",
help='min_tracking_confidence',
type=int,
default=0.5)
parser.add_argument('--use_brect', action='store_true')
args = parser.parse_args()
return args
def main():
# 引数解析 #################################################################
args = get_args()
cap_device = args.device
cap_width = args.width
cap_height = args.height
max_num_faces = args.max_num_faces
refine_landmarks = args.refine_landmarks
min_detection_confidence = args.min_detection_confidence
min_tracking_confidence = args.min_tracking_confidence
use_brect = args.use_brect
# カメラ準備 ###############################################################
cap = cv.VideoCapture(cap_device)
cap.set(cv.CAP_PROP_FRAME_WIDTH, cap_width)
cap.set(cv.CAP_PROP_FRAME_HEIGHT, cap_height)
# モデルロード #############################################################
mp_face_mesh = mp.solutions.face_mesh
face_mesh = mp_face_mesh.FaceMesh(
max_num_faces=max_num_faces,
refine_landmarks=refine_landmarks,
min_detection_confidence=min_detection_confidence,
min_tracking_confidence=min_tracking_confidence,
)
# FPS計測モジュール ########################################################
cvFpsCalc = CvFpsCalc(buffer_len=10)
while True:
display_fps = cvFpsCalc.get()
# カメラキャプチャ #####################################################
ret, image = cap.read()
if not ret:
break
image = cv.flip(image, 1) # ミラー表示
debug_image = copy.deepcopy(image)
# 検出実施 #############################################################
image = cv.cvtColor(image, cv.COLOR_BGR2RGB)
results = face_mesh.process(image)
# 描画 ################################################################
if results.multi_face_landmarks is not None:
for face_landmarks in results.multi_face_landmarks:
# 外接矩形の計算
brect = calc_bounding_rect(debug_image, face_landmarks)
# 虹彩の外接円の計算
left_eye, right_eye = None, None
if refine_landmarks:
left_eye, right_eye = calc_iris_min_enc_losingCircle(
debug_image,
face_landmarks,
)
# 描画
debug_image = draw_landmarks(
debug_image,
face_landmarks,
refine_landmarks,
left_eye,
right_eye,
)
debug_image = draw_bounding_rect(use_brect, debug_image, brect)
cv.putText(debug_image, "FPS:" + str(display_fps), (10, 30),
cv.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 2, cv.LINE_AA)
# キー処理(ESC：終了) #################################################
key = cv.waitKey(1)
if key == 27: # ESC
break
# 画面反映 #############################################################
cv.imshow('MediaPipe Face Mesh Demo', debug_image)
cap.release()
cv.destroyAllWindows()
def calc_bounding_rect(image, landmarks):
image_width, image_height = image.shape[1], image.shape[0]
landmark_array = np.empty((0, 2), int)
for _, landmark in enumerate(landmarks.landmark):
landmark_x = min(int(landmark.x * image_width), image_width - 1)
landmark_y = min(int(landmark.y * image_height), image_height - 1)
landmark_point = [np.array((landmark_x, landmark_y))]
landmark_array = np.append(landmark_array, landmark_point, axis=0)
x, y, w, h = cv.boundingRect(landmark_array)
return [x, y, x + w, y + h]
def calc_iris_min_enc_losingCircle(image, landmarks):
image_width, image_height = image.shape[1], image.shape[0]
landmark_point = []
for index, landmark in enumerate(landmarks.landmark):
landmark_x = min(int(landmark.x * image_width), image_width - 1)
landmark_y = min(int(landmark.y * image_height), image_height - 1)
landmark_point.append((landmark_x, landmark_y))
left_eye_points = [
landmark_point[468],
landmark_point[469],
landmark_point[470],
landmark_point[471],
landmark_point[472],
]
right_eye_points = [
landmark_point[473],
landmark_point[474],
landmark_point[475],
landmark_point[476],
landmark_point[477],
]
left_eye_info = calc_min_enc_losingCircle(left_eye_points)
right_eye_info = calc_min_enc_losingCircle(right_eye_points)
return left_eye_info, right_eye_info
def calc_min_enc_losingCircle(landmark_list):
center, radius = cv.minEnclosingCircle(np.array(landmark_list))
center = (int(center[0]), int(center[1]))
radius = int(radius)
return center, radius
def draw_landmarks(image, landmarks, refine_landmarks, left_eye, right_eye):
image_width, image_height = image.shape[1], image.shape[0]
landmark_point = []
for index, landmark in enumerate(landmarks.landmark):
if landmark.visibility < 0 or landmark.presence < 0:
continue
landmark_x = min(int(landmark.x * image_width), image_width - 1)
landmark_y = min(int(landmark.y * image_height), image_height - 1)
# landmark_z = landmark.z
landmark_point.append((landmark_x, landmark_y))
cv.circle(image, (landmark_x, landmark_y), 1, (0, 255, 0), 1)
if len(landmark_point) > 0:
# 参考：https://github.com/tensorflow/tfjs-models/blob/master/facemesh/mesh_map.jpg
# 左眉毛(55：内側、46：外側)
cv.line(image, landmark_point[55], landmark_point[65], (0, 255, 0), 2)
cv.line(image, landmark_point[65], landmark_point[52], (0, 255, 0), 2)
cv.line(image, landmark_point[52], landmark_point[53], (0, 255, 0), 2)
cv.line(image, landmark_point[53], landmark_point[46], (0, 255, 0), 2)
# 右眉毛(285：内側、276：外側)
cv.line(image, landmark_point[285], landmark_point[295], (0, 255, 0),
2)
cv.line(image, landmark_point[295], landmark_point[282], (0, 255, 0),
2)
cv.line(image, landmark_point[282], landmark_point[283], (0, 255, 0),
2)
cv.line(image, landmark_point[283], landmark_point[276], (0, 255, 0),
2)
# 左目 (133：目頭、246：目尻)
cv.line(image, landmark_point[133], landmark_point[173], (0, 255, 0),
2)
cv.line(image, landmark_point[173], landmark_point[157], (0, 255, 0),
2)
cv.line(image, landmark_point[157], landmark_point[158], (0, 255, 0),
2)
cv.line(image, landmark_point[158], landmark_point[159], (0, 255, 0),
2)
cv.line(image, landmark_point[159], landmark_point[160], (0, 255, 0),
2)
cv.line(image, landmark_point[160], landmark_point[161], (0, 255, 0),
2)
cv.line(image, landmark_point[161], landmark_point[246], (0, 255, 0),
2)
cv.line(image, landmark_point[246], landmark_point[163], (0, 255, 0),
2)
cv.line(image, landmark_point[163], landmark_point[144], (0, 255, 0),
2)
cv.line(image, landmark_point[144], landmark_point[145], (0, 255, 0),
2)
cv.line(image, landmark_point[145], landmark_point[153], (0, 255, 0),
2)
cv.line(image, landmark_point[153], landmark_point[154], (0, 255, 0),
2)
cv.line(image, landmark_point[154], landmark_point[155], (0, 255, 0),
2)
cv.line(image, landmark_point[155], landmark_point[133], (0, 255, 0),
2)
# 右目 (362：目頭、466：目尻)
cv.line(image, landmark_point[362], landmark_point[398], (0, 255, 0),
2)
cv.line(image, landmark_point[398], landmark_point[384], (0, 255, 0),
2)
cv.line(image, landmark_point[384], landmark_point[385], (0, 255, 0),
2)
cv.line(image, landmark_point[385], landmark_point[386], (0, 255, 0),
2)
cv.line(image, landmark_point[386], landmark_point[387], (0, 255, 0),
2)
cv.line(image, landmark_point[387], landmark_point[388], (0, 255, 0),
2)
cv.line(image, landmark_point[388], landmark_point[466], (0, 255, 0),
2)
cv.line(image, landmark_point[466], landmark_point[390], (0, 255, 0),
2)
cv.line(image, landmark_point[390], landmark_point[373], (0, 255, 0),
2)
cv.line(image, landmark_point[373], landmark_point[374], (0, 255, 0),
2)
cv.line(image, landmark_point[374], landmark_point[380], (0, 255, 0),
2)
cv.line(image, landmark_point[380], landmark_point[381], (0, 255, 0),
2)
cv.line(image, landmark_point[381], landmark_point[382], (0, 255, 0),
2)
cv.line(image, landmark_point[382], landmark_point[362], (0, 255, 0),
2)
# 口 (308：右端、78：左端)
cv.line(image, landmark_point[308], landmark_point[415], (0, 255, 0),
2)
cv.line(image, landmark_point[415], landmark_point[310], (0, 255, 0),
2)
cv.line(image, landmark_point[310], landmark_point[311], (0, 255, 0),
2)
cv.line(image, landmark_point[311], landmark_point[312], (0, 255, 0),
2)
cv.line(image, landmark_point[312], landmark_point[13], (0, 255, 0), 2)
cv.line(image, landmark_point[13], landmark_point[82], (0, 255, 0), 2)
cv.line(image, landmark_point[82], landmark_point[81], (0, 255, 0), 2)
cv.line(image, landmark_point[81], landmark_point[80], (0, 255, 0), 2)
cv.line(image, landmark_point[80], landmark_point[191], (0, 255, 0), 2)
cv.line(image, landmark_point[191], landmark_point[78], (0, 255, 0), 2)
cv.line(image, landmark_point[78], landmark_point[95], (0, 255, 0), 2)
cv.line(image, landmark_point[95], landmark_point[88], (0, 255, 0), 2)
cv.line(image, landmark_point[88], landmark_point[178], (0, 255, 0), 2)
cv.line(image, landmark_point[178], landmark_point[87], (0, 255, 0), 2)
cv.line(image, landmark_point[87], landmark_point[14], (0, 255, 0), 2)
cv.line(image, landmark_point[14], landmark_point[317], (0, 255, 0), 2)
cv.line(image, landmark_point[317], landmark_point[402], (0, 255, 0),
2)
cv.line(image, landmark_point[402], landmark_point[318], (0, 255, 0),
2)
cv.line(image, landmark_point[318], landmark_point[324], (0, 255, 0),
2)
cv.line(image, landmark_point[324], landmark_point[308], (0, 255, 0),
2)
if refine_landmarks:
# 虹彩：外接円
cv.circle(image, left_eye[0], left_eye[1], (0, 255, 0), 2)
cv.circle(image, right_eye[0], right_eye[1], (0, 255, 0), 2)
# 左目：中心
cv.circle(image, landmark_point[468], 2, (0, 0, 255), -1)
# 左目：目頭側
cv.circle(image, landmark_point[469], 2, (0, 0, 255), -1)
# 左目：上側
cv.circle(image, landmark_point[470], 2, (0, 0, 255), -1)
# 左目：目尻側
cv.circle(image, landmark_point[471], 2, (0, 0, 255), -1)
# 左目：下側
cv.circle(image, landmark_point[472], 2, (0, 0, 255), -1)
# 右目：中心
cv.circle(image, landmark_point[473], 2, (0, 0, 255), -1)
# 右目：目尻側
cv.circle(image, landmark_point[474], 2, (0, 0, 255), -1)
# 右目：上側
cv.circle(image, landmark_point[475], 2, (0, 0, 255), -1)
# 右目：目頭側
cv.circle(image, landmark_point[476], 2, (0, 0, 255), -1)
# 右目：下側
cv.circle(image, landmark_point[477], 2, (0, 0, 255), -1)
return image
def draw_bounding_rect(use_brect, image, brect):
if use_brect:
# 外接矩形
cv.rectangle(image, (brect[0], brect[1]), (brect[2], brect[3]),
(0, 255, 0), 2)
return image
if __name__ == '__main__':
main()