upgraded

app.py

@@ -12,16 +12,24 @@ from pathlib import Path
 import cv2
 import time
 
+from numpy.lib.type_check import imag
 from FaceAnalyzer import FaceAnalyzer
 
+import matplotlib.pyplot as plt
 from pathlib import Path
 import pickle
+import tensorflow as tf
 from tqdm import tqdm  # used to draw a progress bar pip install tqdm
+import tkinter as tk
+from tkinter import simpledialog
 from deepface import DeepFace
 
 # Number of images to use to build the embedding
 nb_images=50
 
+# create Tkinter root window
+root = tk.Tk()
+root.withdraw()
 
 
 # If faces path is empty then make it
@@ -59,6 +67,7 @@ class UI():
         self.current_name = None
         self.current_face_files = []
         self.draw_landmarks = True
+        self.upgrade_faces()
 
         with gr.Blocks() as demo:
             gr.Markdown("## FaceAnalyzer face recognition test")
@@ -115,6 +124,7 @@ class UI():
                                     headers=["Face Name"],
                                     datatype=["str"],
                                     label="Faces",
+                                    value=[[n] for n in self.known_faces_names]
                                 )
             with gr.Row():
                 with gr.Accordion(label="Options", open=False):
@@ -125,7 +135,6 @@ class UI():
                     self.cb_draw_landmarks = gr.Checkbox(label="Draw landmarks", value=True)
                     self.cb_draw_landmarks.change(self.set_draw_landmarks, self.cb_draw_landmarks)
 
-        self.upgrade_faces()
         demo.queue().launch()
     def add_files(self, files):
         for file in files:
@@ -168,7 +177,8 @@ class UI():
                 finger_print = pickle.load(f)
                 self.known_faces.append(finger_print)
             self.known_faces_names.append(file.stem)
-        self.faces_list.update(self.known_faces_names)
+        if hasattr(self, "faces_list"):
+            self.faces_list.update([self.known_faces])
 
     def set_face_name(self, face_name):
         self.face_name=face_name