Update app.py

app.py

@@ -52,12 +52,9 @@ def convert_to_ela_image(path, quality):
 
     return ela_im
 
-from google.colab import drive
-drive.mount('/content/drive')
+Image.open('https://huggingface.co/spaces/Hemant0000/Deep_Fake_Detection/blob/main/Images%20for%20Deep%20Fake/real_images/6401_0.jpg')
 
-Image.open('/content/drive/MyDrive/Images for Deep Fake/real_images/6401_0.jpg')
-
-convert_to_ela_image('/content/drive/MyDrive/Images for Deep Fake/real_images/6401_0.jpg', 90)
+convert_to_ela_image('https://huggingface.co/spaces/Hemant0000/Deep_Fake_Detection/blob/main/Images%20for%20Deep%20Fake/real_images/6401_0.jpg', 90)
 
 Image.open('https://huggingface.co/spaces/Hemant0000/Deep_Fake_Detection/blob/main/Images%20for%20Deep%20Fake/fake_images/1601_0.jpg')
 
@@ -96,8 +93,8 @@ def create_image_dataset_csv(fake_folder, real_folder, output_csv):
     print(f"CSV file '{output_csv}' has been created successfully with {len(image_data)} entries.")
 
 # Example usage:
-fake_images_folder = '/content/drive/MyDrive/Images for Deep Fake/fake_images'
-real_images_folder = '/content/drive/MyDrive/Images for Deep Fake/real_images'
+fake_images_folder = 'Images for Deep Fake/fake_images'
+real_images_folder = 'Images for Deep Fake/real_images'
 output_csv_file = 'image_dataset.csv'
 
 create_image_dataset_csv(fake_images_folder, real_images_folder, output_csv_file)