Update app.py

app.py

@@ -75,7 +75,7 @@ import numpy as np
 import cv2
 import copy
 import random
-video_files =  glob.glob('/content/drive/MyDrive/Face_only_data/*.mp4')
+video_files =  glob.glob('dataset final/*.mp4')
 random.shuffle(video_files)
 random.shuffle(video_files)
 frame_count = []
@@ -146,7 +146,7 @@ def im_plot(tensor):
 #count the number of fake and real videos
 def number_of_real_and_fake_videos(data_list):
   header_list = ["filename","label"]
-  lab = pd.read_csv('/content/drive/MyDrive/labels.csv',names=header_list)
+  lab = pd.read_csv('labels.csv',names=header_list)
   fake = 0
   real = 0
   for i in data_list:
@@ -164,7 +164,7 @@ import pandas as pd
 from sklearn.model_selection import train_test_split
 
 header_list = ["filename","label"]
-labels = pd.read_csv('/content/drive/MyDrive/labels.csv',names=header_list)
+labels = pd.read_csv('labels.csv',names=header_list)
 #print(labels)
 train_videos = video_files[:int(0.75*len(video_files))]
 valid_videos = video_files[int(0.75*len(video_files)):]