Advanced face recognition with Python

import tkinter as tkfrom threading import Threadfrom tkinter.filedialog import askopenfilenamefrom tkinter.filedialog import askdirectoryfrom PIL import ImageTk, Imagefrom tkinter.ttk import Progressbarfrom tkinter import messageboximport face_recognitionimport os

class FaceApp(tk.Tk):    def __init__(self):        tk.Tk.__init__(self)        self.geometry("900x800")        self.resizable(True, True)        self.title('Bulker')        row = tk.Frame(self)        lab = tk.Label(row, width=5, text="Image : ", anchor='w')        self._file_field = tk.Entry(row)        self._file_open_btn = tk.Button(row, text='Find',                                        command=lambda: self.load_file())        row1 = tk.Frame(self)        lab1 = tk.Label(row1, width=5, text="Folder : ", anchor='w')        self._folder_field = tk.Entry(row1)        self._folder_open_btn = tk.Button(row1, text='Open',                                          command=lambda: self.load_folder())        self._image_panel = tk.Frame(self)        bottom_row = tk.Frame(self)        self._start_btn = tk.Button(bottom_row, text='Start',                                    command=lambda: self.run_process())        self._progress = Progressbar(bottom_row, orient=tk.HORIZONTAL, length=500, mode='determinate')        lab.pack(side=tk.LEFT, padx=30)        self._file_field.pack(side=tk.LEFT, ipadx=250)        self._file_open_btn.pack(side=tk.LEFT, ipadx=10, padx=10)        row.pack(side=tk.TOP, fill=tk.X, padx=10, pady=8)        lab1.pack(side=tk.LEFT, padx=30)        self._folder_field.pack(side=tk.LEFT, ipadx=250)        self._folder_open_btn.pack(side=tk.LEFT, ipadx=10, padx=10)        row1.pack(side=tk.TOP, fill=tk.X, padx=10, pady=8)        self._image_panel.pack(side=tk.TOP, fill=tk.X, padx=10, pady=8)        self._start_btn.pack(side=tk.BOTTOM, ipadx=10, padx=10)        self._progress.pack(side=tk.BOTTOM, pady=5)        bottom_row.pack(side=tk.TOP, fill=tk.X, padx=10, pady=8)

def load_file(self):        filename = askopenfilename()        self._file_field.delete(0, tk.END)          self._file_field.insert(0, filename)        for widget in self._image_panel.winfo_children():            widget.destroy()        img = ImageTk.PhotoImage(Image.open(filename))        panel = tk.Label(self._image_panel, image=img)        panel.img = img        panel.pack(side="bottom", fill="both", expand="yes")    def load_folder(self):        filename = askdirectory()        self._folder_field.delete(0, tk.END)          self._folder_field.insert(0, filename)

 def start_process(self):        ref_path = self._file_field.get()        folder_path = self._folder_field.get()        self.find_and_delete(folder_path, ref_path)    def run_process(self):        self._run_task = True        t = Thread(target=self.start_process)        t.start()

def find_and_delete(self, directory, ref_image_path):        ref_face = self.get_ref_face(ref_image_path)        if ref_face is None:            messagebox.showinfo("Error", "Can't find a face. Reference Image quality is not enough")            return        files = os.listdir(directory)        i = 1        for filename in files:            try:                percentage = int((i / len(files)) * 100)                self._progress['value'] = percentage                self.update_idletasks()                i += 1                file_path = os.path.join(directory, filename)                if self.is_user_in_image(ref_face, file_path):                    os.remove(file_path)                    print(filename, 'deleted.')            except:                print('Error reading file', filename)        messagebox.showinfo("Information", "Process Finished")    def get_ref_face(self, ref_image_path):        try:            ref_image = face_recognition.load_image_file(ref_image_path)            ref_face = face_recognition.face_encodings(ref_image)[0]            return ref_face        except:            return None    def is_user_in_image(self, ref_face, image_path):        unknown_picture = face_recognition.load_image_file(image_path)        unknown_faces = face_recognition.face_encodings(unknown_picture)        for unknown_face in unknown_faces:            results = face_recognition.compare_faces([ref_face], unknown_face)            if results[0]:                return True        return Falseif __name__ == "__main__":    app = FaceApp()    app.mainloop()