如何解决我想为使用CLI的面部识别程序实现gui
我不太擅长编写完整的GUI。 所以基本上我想做的是使用tkinter为我的面部识别程序创建GUI，而不是用户在命令提示符下手动输入命令行参数，而我希望输出像这样（左侧面板中的原始图像，以及右侧的识别图像。 这里的代码是一个工作代码，允许用户在命令提示符下输入参数。
提前谢谢。
import face_recognition
import argparse
import pickle
import cv2
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-e","--encodings",required=True,help="path to serialized db of facial encodings")
ap.add_argument("-i","--image",help="path to input image")
ap.add_argument("-d","--detection-method",type=str,default="cnn",help="face detection model to use: either `hog` or `cnn`")
args = vars(ap.parse_args())
# load the kNown faces and embeddings
print("[INFO] loading encodings...")
data = pickle.loads(open(args["encodings"],"rb").read())
# load the input image and convert it from BGR to RGB
image = cv2.imread(args["image"])
rgb = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
# detect the (x,y)-coordinates of the bounding Boxes corresponding
# to each face in the input image,then compute the facial embeddings
# for each face
print("[INFO] recognizing faces...")
Boxes = face_recognition.face_locations(rgb,model=args["detection_method"])
encodings = face_recognition.face_encodings(rgb,Boxes)
# initialize the list of names for each face detected
names = []
# loop over the facial embeddings
for encoding in encodings:
# attempt to match each face in the input image to our kNown
# encodings
matches = face_recognition.compare_faces(data["encodings"],encoding)
name = "UnkNown"
# check to see if we have found a match
if True in matches:
# find the indexes of all matched faces then initialize a
# dictionary to count the total number of times each face
# was matched
matchedIdxs = [i for (i,b) in enumerate(matches) if b]
counts = {}
# loop over the matched indexes and maintain a count for
# each recognized face face
for i in matchedIdxs:
name = data["names"][i]
counts[name] = counts.get(name,0) + 1
# determine the recognized face with the largest number of
# Votes (note: in the event of an unlikely tie Python will
# select first entry in the dictionary)
name = max(counts,key=counts.get)
# update the list of names
names.append(name)
# loop over the recognized faces
for ((top,right,bottom,left),name) in zip(Boxes,names):
# draw the predicted face name on the image
cv2.rectangle(image,(left,top),(right,bottom),(0,255,0),2)
y = top - 15 if top - 15 > 15 else top + 15
cv2.putText(image,name,y),cv2.FONT_HERShey_SIMPLEX,0.75,2)
# show the output image
cv2.imshow("Image",image)
cv2.waitKey(0)
这就是我尝试过的
import face_recognition
import argparse
import pickle
import cv2
from tkinter import *
from tkinter import filedialog
def select_image():
# grab a reference to the image panels
global panelA,panelB
# open a file chooser dialog and allow the user to select an input
# image
imagepath = filedialog.askopenfilename()
encodingspath = filedialog.askopenfilename()
# ensuring a file path is selected
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-d",help="face detection model to use: either `hog` or `cnn`")
args = vars(ap.parse_args())
if len(imagepath and encodingspath) > 0:
data = pickle.loads(open(encodingspath,"rb").read())
# load the input image and convert it from BGR to RGB
initial_image = cv2.imread(imagepath)
image = cv2.imread(imagepath)
rgb = cv2.cvtColor(image,cv2.COLOR_BGR2RGB)
# detect the (x,y)-coordinates of the bounding Boxes corresponding
# to each face in the input image,then compute the facial embeddings
# for each face
print("[INFO] recognizing faces...")
Boxes = face_recognition.face_locations(rgb,model=args["detection_method"])
encodingspath = face_recognition.face_encodings(rgb,Boxes)
# initialize the list of names for each face detected
names = []
# loop over the facial embeddings
for encoding in encodingspath:
# attempt to match each face in the input image to our kNown
# encodings
matches = face_recognition.compare_faces(data(encodingspath),encoding)
name = "UnkNown"
# check to see if we have found a match
if True in matches:
# find the indexes of all matched faces then initialize a
# dictionary to count the total number of times each face
# was matched
matchedIdxs = [i for (i,b) in enumerate(matches) if b]
counts = {}
# loop over the matched indexes and maintain a count for
# each recognized face face
for i in matchedIdxs:
name = data["names"][i]
counts[name] = counts.get(name,0) + 1
# determine the recognized face with the largest number of
# Votes (note: in the event of an unlikely tie Python will
# select first entry in the dictionary)
name = max(counts,key=counts.get)
# update the list of names
names.append(name)
# loop over the recognized faces
for ((top,names):
# draw the predicted face name on the image
cv2.rectangle(image,2)
y = top - 15 if top - 15 > 15 else top + 15
cv2.putText(image,2)
# show the output image
#cv2.imshow("Image",image)
#cv2.waitKey(0)
# if the panels are None,initialize them
if panelA is None or panelB is None:
# the first panel will store our original image
panelA = Label(image=initial_image)
panelA.image = initial_image
panelA.pack(side="left",padx=10,pady=10)
# while the second panel will store the recognized image
panelB = Label(image=image)
panelB.image = image
panelB.pack(side="right",pady=10)
# otherwise,update the image panels
else:
# update the pannels
panelA.configure(image=initial_image)
panelB.configure(image=image)
panelA.image = initial_image
panelB.image = image
# initialize the window toolkit along with the two image panels
root = Tk()
panelA = None
panelB = None
# create a button,then when pressed,will trigger a file chooser
# dialog and allow the user to select an input image; then add the
# button the GUI
btn = Button(root,text="Select an image",command=select_image)
btn.pack(side="bottom",fill="both",expand="yes",padx="10",pady="10")
# kick off the GUI
root.mainloop()
解决方法
您应该保持命令行工具不变，并在选择参数后让GUI调用它。因此，您仍然可以在命令行中使用它。
要让您开始考虑这样的事情（假设您的cli工具名为face_recognition）
#! /usr/bin/env python3
import subprocess
import sys
import tkinter as tk
import tkinter.filedialog
class Application(tk.Frame):
def __init__(self,master=None):
super().__init__(master)
self.master = master
self.pack()
self.create_widgets()
self.image = ""
def create_widgets(self):
tk.Button(self,text="Choose image...",command=self.get_image_filename).pack(fill=tk.X)
# TODO: add a way to enter all the desired arguments...
tk.Button(self,text="Run",command=self.run_face_recognition).pack(fill=tk.X)
tk.Button(self,text="Quit",command=self.master.destroy).pack(fill=tk.X)
def get_image_filename(self):
self.image = tkinter.filedialog.askopenfilename()
def run_face_recognition(self):
subprocess.run([sys.executable,"/path/to/face_recognition.py","--image",self.image,"args..."])
root = tk.Tk()
app = Application(master=root)
app.mainloop()
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