jupyter notebookで、カムの画像から、顔の形状とその大きさを解析表示する。

gistfile1.txt

# https://stackoverflow.com/questions/37210655/opencv-detect-face-landmarks-ear-chin-ear-line
# 結果サンプルは prCIc.png を参照。
#FACE_POINTS = list(range(17, 68))
#MOUTH_POINTS = list(range(48, 61))
#RIGHT_BROW_POINTS = list(range(17, 22))
#LEFT_BROW_POINTS = list(range(22, 27))
#RIGHT_EYE_POINTS = list(range(36, 42))
#LEFT_EYE_POINTS = list(range(42, 48))
#NOSE_POINTS = list(range(27, 35))
#JAW_POINTS = list(range(0, 17))
#CHIN_POINTS=list(range(6,11))

import cv2
import numpy as np
from matplotlib import pyplot as plt
import dlib

# 顔のランドマーク検出。
# https://www.pyimagesearch.com/?s=face+landmark&submit=Search

# http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2 
PREDICTOR_PATH = "shape_predictor_68_face_landmarks.dat"
#PREDICTOR_PATH = "shape_predictor_5_face_landmarks.dat"
predictor = dlib.shape_predictor(PREDICTOR_PATH)
cascade_path='haarcascade_frontalface_default.xml'
cascade = cv2.CascadeClassifier(cascade_path)

# #This is using the Dlib Face Detector . Better result more time taking
#def get_landmarks(im):
#     rects = detector(im, 1)
#     rect=rects[0]
#     print type(rect.width())
#     fwd=int(rect.width())
#     if len(rects) == 0:
#         return None,None
#     return np.matrix([[p.x, p.y] for p in predictor(im, rects[0]).parts()]),fwd

def get_landmarks(im):
    rects = cascade.detectMultiScale(im, 1.3,5)
    if len(rects) == 0:
        return []
    x,y,w,h =rects[0]
    rect=dlib.rectangle(x,y,x+w,y+h)
    object_detection=predictor(im, rect)
#    print(object_detection.parts())
    return object_detection.parts()
#   return np.matrix([[p.x, p.y] for p in object_detection.parts()])

def get_length(points):
    length = 0
    point = points[0]
    for p in points:
#        print(point, p)         
        diff = p - point           
        dist = np.sqrt(pow(diff.x,2) + pow(diff.y,2))
        length += dist
        point = p
    return length

#   検出した特徴点を画像に描画するメソッドです。
def annotate_landmarks(im, parts):
#    im = im.copy()
    landmarks = np.matrix([[p.x, p.y] for p in parts])
    for idx, point in enumerate(landmarks):
        pos = (point[0, 0], point[0, 1])
        cv2.putText(im, str(idx), pos,
                    fontFace=cv2.FONT_HERSHEY_SCRIPT_SIMPLEX,
                    fontScale=0.2,
                    color=(0, 0, 255))
        cv2.circle(im, pos, 3, color=(0, 255, 255))
    return im

# 顔の線分の長さなどのテキストを、画像に表示するメソッドです。
def annotate_text(im, point, text, color=(255, 0,0)):
#    im = im.copy()
    cv2.putText(im, text, point,
                fontFace=cv2.FONT_HERSHEY_SCRIPT_SIMPLEX,
                fontScale=0.6,
                color=color)
    return im

#顔の線分などを画像に表示するメソッドです。
def annotate_line(im, parts, lineColor=(255, 0, 0)):
#    im = im.copy()
    landmarks  = np.matrix([[p.x, p.y] for p in parts])
    startPoint = landmarks[0]
    for idx, point in enumerate(landmarks):
        p1 = (startPoint[0, 0], startPoint[0, 1])
        p2 = (point[0, 0], point[0, 1])
        cv2.line(im, p1, p2, color=lineColor, thickness=3)
        startPoint = point
    return im 

cap = cv2.VideoCapture(0)
while True:
    ret_value, img = cap.read()
    img = cv2.flip(img, 1)    
#    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    parts = get_landmarks(img)
    if len(parts) > 0:
        left_cheek  = parts[2:8]
        right_cheek = parts[9:15]
        left_cheek_line  = [parts[2],  parts[31]]
        right_cheek_line = [parts[14], parts[35]]
        #print(left_cheek, right_cheek)
        #print(left_cheek_line, right_cheek_line)
        print("左の頬の長さ    {:.0f}".format(get_length(left_cheek)))
        print("左の頬-鼻の距離 {:.0f}".format(get_length(left_cheek_line)))
        print("右の頬の長さ    {:.0f}".format(get_length(right_cheek)))
        print("右の頬-鼻の距離 {:.0f}".format(get_length(right_cheek_line)))

        img = annotate_landmarks(img, parts)
        img = annotate_line(img, left_cheek, (0, 250, 0))
        img = annotate_line(img, left_cheek_line)
        img = annotate_line(img, right_cheek, (0, 250, 0))
        img = annotate_line(img, right_cheek_line)    

        img = annotate_text(img, (parts[2].x  - 80, parts[2].y  + 40), "{:.0f}".format(get_length(left_cheek)), (0, 250, 0))
        img = annotate_text(img, (parts[31].x - 20, parts[31].y - 20), "{:.0f}".format(get_length(left_cheek_line)))        
        img = annotate_text(img, (parts[14].x + 80, parts[14].y + 40), "{:.0f}".format(get_length(right_cheek)), (0, 250, 0))
        img = annotate_text(img, (parts[35].x + 20, parts[35].y - 20), "{:.0f}".format(get_length(right_cheek_line)))

#    plt.figure(figsize=(10,10))
    cv2.imshow('face', img)
    if cv2.waitKey(1) == ord('q'):
        break

cap.release
cv2.destroyAllWindows()