#!/usr/bin/env python
# -*- coding:utf-8-*-
# file: {NAME}.py
# @author: jory.d
# @contact: [email protected]
# @time: 2020/04/10 19:42
# @desc: 使用dlib進行人臉檢測和人臉關鍵點

import cv2
import numpy as np
import glob
import dlib

FACE_DETECT_PATH = '/home/build/dlib-v19.18/data/mmod_human_face_detector.dat'
FACE_LANDMAKR_5_PATH = '/home/build/dlib-v19.18/data/shape_predictor_5_face_landmarks.dat'
FACE_LANDMAKR_68_PATH = '/home/build/dlib-v19.18/data/shape_predictor_68_face_landmarks.dat'


def face_detect():
  root = '/media/dangxs/E/Project/DataSet/VGG Face Dataset/vgg_face_dataset/vgg_face_dataset/vgg_face_dataset'
  imgs = glob.glob(root + '/**/*.jpg',recursive=True)
  assert len(imgs) > 0

  detector = dlib.get_frontal_face_detector()
  predictor = dlib.shape_predictor(FACE_LANDMAKR_68_PATH)
  for f in imgs:
    img = cv2.imread(f)
    # The 1 in the second argument indicates that we should upsample the image
    # 1 time. This will make everything bigger and allow us to detect more
    # faces.
    dets = detector(img,1)
    print("Number of faces detected: {}".format(len(dets)))
    for i,d in enumerate(dets):
      x1,y1,x2,y2 = d.left(),d.top(),d.right(),d.bottom()
      print("Detection {}: Left: {} Top: {} Right: {} Bottom: {}".format(
        i,x1,y2))

      cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0),1)

      # Get the landmarks/parts for the face in box d.
      shape = predictor(img,d)
      print("Part 0: {},Part 1: {} ...".format(shape.part(0),shape.part(1)))
      # # Draw the face landmarks on the screen.
      '''
      # landmark 順序： 外輪廓 - 左眉毛 - 右眉毛 - 鼻子 - 左眼 - 右眼 - 嘴巴
      '''
      for i in range(shape.num_parts):
        x,y = shape.part(i).x,shape.part(i).y
        cv2.circle(img,(x,y),2,255),1)
        cv2.putText(img,str(i),cv2.FONT_HERSHEY_COMPLEX,0.3,1)

    cv2.resize(img,dsize=None,dst=img,fx=2,fy=2)
    cv2.imshow('w',img)
    cv2.waitKey(0)


def face_detect_mask():
  root = '/media/dangxs/E/Project/DataSet/VGG Face Dataset/vgg_face_dataset/vgg_face_dataset/vgg_face_dataset'
  imgs = glob.glob(root + '/**/*.jpg',shape.part(1)))
      # # Draw the face landmarks on the screen.
      '''
      # landmark 順序： 外輪廓 - 左眉毛 - 右眉毛 - 鼻子 - 左眼 - 右眼 - 嘴巴
      '''
      points = []
      for i in range(shape.num_parts):
        x,shape.part(i).y
        if i < 26:
          points.append([x,y])
        # cv2.circle(img,1)
        # cv2.putText(img,1)

      # 只把臉切出來
      points[17:] = points[17:][::-1]
      points = np.asarray(points,np.int32).reshape(-1,1,2)
      img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
      black_img = np.zeros_like(img)
      cv2.polylines(black_img,[points],255)
      cv2.fillPoly(black_img,(1,1))
      mask = black_img
      masked_bgr = img * mask

      # 位運算時需要轉化成灰度影象
      mask_gray = cv2.cvtColor(mask,cv2.COLOR_BGR2GRAY)
      masked_gray = cv2.bitwise_and(img_gray,img_gray,mask=mask_gray)

    cv2.resize(img,img)
    cv2.imshow('mask',mask)
    cv2.imshow('mask2',masked_gray)
    cv2.imshow('mask3',masked_bgr)
    cv2.waitKey(0)


if __name__ == '__main__':
  face_detect()

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