Update app.py

app.py

@@ -1,24 +1,19 @@
-# from google.colab import drive
-# drive.mount('/content/drive')
-
-# import gradio as gr
 import gradio as gr
 import webbrowser
 from threading import Timer
 import torch
-import torch.nn.functional as F
 from facenet_pytorch import InceptionResnetV1
 import cv2
-from PIL import Image
+from PIL import Image, ImageOps
 import numpy as np
 import warnings
+
 warnings.filterwarnings("ignore")
 
 DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
 
 model = InceptionResnetV1(pretrained="vggface2", classify=True, num_classes=1).to(DEVICE).eval()
 
-# checkpoint_path = "/content/drive/MyDrive/resnetinceptionv1_epoch_32.pth"
 checkpoint_path = "resnetinceptionv1_epoch_32.pth"
 checkpoint = torch.load(checkpoint_path, map_location=DEVICE)
 if 'model_state_dict' in checkpoint:
@@ -40,7 +35,8 @@ def create_montage(frames, size=(512, 512)):
     thumb_size = (size[0] // montage_grid, size[1] // montage_grid)
 
     for i, frame in enumerate(frames):
-        thumbnail = frame.resize(thumb_size, Image.ANTIALIAS)
+        # Updated resize method
+        thumbnail = ImageOps.fit(frame, thumb_size, Image.Resampling.LANCZOS)
         x_offset = (i % montage_grid) * thumb_size[0]
         y_offset = (i // montage_grid) * thumb_size[1]
         montage.paste(thumbnail, (x_offset, y_offset))