目录
1、项目背景
2019年新型冠状病毒感染的肺炎疫情发生以来,牵动人心,举国哀痛,口罩、酒精、消毒液奇货可居。
抢不到口罩,怎么办?作为技术人今天分享如何使用Python实现自动戴口罩系统,来安慰自己,系统效果如下所示:
本系统的实现原理是借助 Dlib模块的Landmark人脸68个关键点检测库轻松识别出人脸五官数据,根据这些数据,确定嘴唇部分的位置数据(48点~67点位置),根据检测到嘴部的尺寸和方向,借助PLL模块调整口罩的尺寸和方向,实现将口罩放在图像的适当位置。
2、页面设计
基于tkinter模块实现GUI设计,可载入人物图像,选择四种类型口罩(这里的口罩是处理好的图片),展示佩戴好口罩的效果,操作完成退出系统,效果如下所示:
页面布局实现代码如下所示:
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def __init__(self):
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self.root = tk.Tk()
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self.root.title(
'基于Pyhon的人脸自动戴口罩系统')
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self.root.geometry(
'1200x500')
-
-
self.path1_ =
None
-
self.path2_ =
None
-
self.seg_img_path =
None
-
self.mask =
None
-
self.label_Img_seg =
None
-
-
decoration = PIL.Image.open(
'./pic/bg.png').resize((
1200,
500))
-
render = ImageTk.PhotoImage(decoration)
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img = tk.Label(image=render)
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img.image = render
-
img.place(x=
0, y=
0)
-
-
# 原图1的展示
-
tk.Button(self.root, text=
"打开头像", command=self.show_original1_pic).place(x=
50, y=
120)
-
tk.Button(self.root, text=
"退出软件", command=quit).place(x=
900, y=
40)
-
-
tk.Label(self.root, text=
"头像", font=
10).place(x=
280, y=
120)
-
self.cv_orinial1 = tk.Canvas(self.root, bg=
'white', width=
270, height=
270)
-
self.cv_orinial1.create_rectangle(
8,
8,
260,
260, width=
1, outline=
'red')
-
self.cv_orinial1.place(x=
180, y=
150)
-
self.label_Img_original1 = tk.Label(self.root)
-
self.label_Img_original1.place(x=
180, y=
150)
-
-
tk.Label(self.root,text=
"选择口罩",font=
10).place(x=
600,y=
120)
-
-
first_pic = Image.open(
"./pic/Mask.png")
-
first_pic = first_pic.resize((
60,
60), Image.ANTIALIAS)
-
first_pic = ImageTk.PhotoImage(first_pic)
-
self.first = tk.Label(self.root, image=first_pic)
-
self.first.place(x=
600,y=
160, width=
60, height=
60)
-
self.first.bind(
"<Button-1>", self.mask0)
-
-
second_pic = Image.open(
"./pic/Mask1.png")
-
second_pic = second_pic.resize((
60,
60), Image.ANTIALIAS)
-
second_pic = ImageTk.PhotoImage(second_pic)
-
self.second_pic = tk.Label(self.root, image=second_pic)
-
self.second_pic.place(x=
600, y=
230, width=
60, height=
60)
-
self.second_pic.bind(
"<Button-1>", self.mask1)
-
-
third_pic = Image.open(
"./pic/Mask3.png")
-
third_pic = third_pic.resize((
60,
60), Image.ANTIALIAS)
-
third_pic = ImageTk.PhotoImage(third_pic)
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self.third_pic = tk.Label(self.root, image=third_pic)
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self.third_pic.place(x=
600, y=
300, width=
60, height=
60)
-
self.third_pic.bind(
"<Button-1>", self.mask3)
-
-
forth_pic = Image.open(
"./pic/Mask4.png")
-
forth_pic = forth_pic.resize((
60,
60), Image.ANTIALIAS)
-
forth_pic = ImageTk.PhotoImage(forth_pic)
-
self.forth_pic = tk.Label(self.root, image=forth_pic)
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self.forth_pic.place(x=
600, y=
370, width=
60, height=
60)
-
self.forth_pic.bind(
"<Button-1>", self.mask4)
-
-
tk.Label(self.root, text=
"佩戴效果", font=
10).place(x=
920, y=
120)
-
self.cv_seg = tk.Canvas(self.root, bg=
'white', width=
270, height=
270)
-
self.cv_seg.create_rectangle(
8,
8,
260,
260, width=
1, outline=
'red')
-
self.cv_seg.place(x=
820, y=
150)
-
self.label_Img_seg = tk.Label(self.root)
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self.label_Img_seg.place(x=
820, y=
150)
-
-
self.root.mainloop()
载入人物图像,实现代码如下所示:
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# 原图1展示
-
def show_original1_pic(self):
-
self.path1_ = askopenfilename(title=
'选择文件')
-
print(self.path1_)
-
self.Img = PIL.Image.open(
r'{}'.format(self.path1_))
-
Img = self.Img.resize((
270,
270),PIL.Image.ANTIALIAS)
# 调整图片大小至256x256
-
img_png_original = ImageTk.PhotoImage(Img)
-
self.label_Img_original1.config(image=img_png_original)
-
self.label_Img_original1.image = img_png_original
# keep a reference
-
self.cv_orinial1.create_image(
5,
5,anchor=
'nw', image=img_png_original)
人脸戴口罩展示,实现代码如下所示:
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# 人脸戴口罩效果展示
-
def show_morpher_pic(self):
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img1 = cv2.imread(self.path1_)
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x_min, x_max, y_min, y_max, size = self.get_mouth(img1)
-
adding = self.mask.resize(size)
-
im = Image.fromarray(img1[:, :, ::
-1])
# 切换RGB格式
-
# 在合适位置添加头发图片
-
im.paste(adding, (int(x_min), int(y_min)), adding)
-
# im.show()
-
save_path = self.path1_.split(
'.')[
0]+
'_result.jpg'
-
im.save(save_path)
-
Img = im.resize((
270,
270), PIL.Image.ANTIALIAS)
# 调整图片大小至270x270
-
img_png_seg = ImageTk.PhotoImage(Img)
-
self.label_Img_seg.config(image=img_png_seg)
-
self.label_Img_seg.image = img_png_seg
# keep a reference
导入四种口罩图像,实现代码如下所示:
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def mask0(self, event):
-
self.mask = Image.open(
'pic/mask.png')
-
self.show_morpher_pic()
-
-
def mask1(self, event):
-
self.mask = Image.open(
'pic/mask1.png')
-
self.show_morpher_pic()
-
-
def mask3(self, event):
-
self.mask = Image.open(
'pic/mask3.png')
-
self.show_morpher_pic()
-
-
def mask4(self, event):
-
self.mask = Image.open(
'pic/mask4.png')
-
self.show_morpher_pic()
3、器官识别
页面功能实现后就是依托Dlib库实现人脸器官关键点的识别,分析出嘴部位置及尺寸,这里为了方便各位直观了解,写了一个测试Demo,将人物脸部关键点都显示出来,代码如下所示:
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#coding=utf-8
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#图片检测 - Dlib版本
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import cv2
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import dlib
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import time
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t=time.time()
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path =
"./pic/im.jpg"
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img = cv2.imread(path)
-
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-
-
#人脸分类器
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detector = dlib.get_frontal_face_detector()
-
# 获取人脸检测器
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predictor = dlib.shape_predictor(
-
"./shape_predictor_68_face_landmarks.dat"
-
)
-
-
dets = detector(gray,
1)
-
for face
in dets:
-
shape = predictor(img, face)
# 寻找人脸的68个标定点
-
# 遍历所有点,打印出其坐标,并圈出来
-
for pt
in shape.parts():
-
pt_pos = (pt.x, pt.y)
-
cv2.circle(img, pt_pos,
1, (
0,
255,
0),
2)
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cv2.imshow(
"image", img)
-
print(
'所用时间为{}'.format(time.time()-t))
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cv2.waitKey(
0)
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#cv2.destroyAllWindows()
-
time.sleep(
5)
效果如下所示:
在本系统中这些关键点无需绘制显示,直接使用就可以,实现代码如下所示:
-
def get_mouth(self, img):
-
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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detector = dlib.get_frontal_face_detector()
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predictor = dlib.shape_predictor(
'./shape_predictor_68_face_landmarks.dat')
-
faces = detector(img_gray,
0)
-
for k, d
in enumerate(faces):
-
x = []
-
y = []
-
# 人脸大小的高度
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height = d.bottom() - d.top()
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# 人脸大小的宽度
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width = d.right() - d.left()
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shape = predictor(img_gray, d)
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# 48-67 为嘴唇部分
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for i
in range(
48,
68):
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x.append(shape.part(i).x)
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y.append(shape.part(i).y)
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# 根据人脸的大小扩大嘴唇对应口罩的区域
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y_max = (int)(max(y) + height /
3)
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y_min = (int)(min(y) - height /
3)
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x_max = (int)(max(x) + width /
3)
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x_min = (int)(min(x) - width /
3)
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size = ((x_max - x_min), (y_max - y_min))
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return x_min, x_max, y_min, y_max, size
4、退出系统
退出系统非常简单,一行Demo即可实现,如下所示:
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def quit(self):
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self.root.destroy()
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转载:https://blog.csdn.net/m0_38106923/article/details/104174562
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