Update app.py

app.py

@@ -10,14 +10,18 @@ from tensorflow.keras.models import Model
 from tensorflow.keras.optimizers import Adam
 
 # Function to download and extract the dataset
-def download_and_extract_dataset(dataset_name):
-    # Make sure the kaggle.json file is in the proper location
+def download_and_extract_dataset():
+    # Set the Kaggle configuration directory
     os.environ['KAGGLE_CONFIG_DIR'] = os.path.expanduser("~/.kaggle/")
+    
     # Download the dataset
-    os.system(f'kaggle datasets download -d mikoajkolman/pokemon-images-first-generation17000-files')
+    dataset_zip = 'pokemon-images-first-generation17000-files.zip'
+    kaggle_dataset = 'mikoajkolman/pokemon-images-first-generation17000-files'
+    os.system(f'kaggle datasets download -d {kaggle_dataset}')
+    
     # Extract the dataset
-    with zipfile.ZipFile(f'{dataset_name}.zip', 'r') as zip_ref:
-        zip_ref.extractall('.')
+    with zipfile.ZipFile(dataset_zip, 'r') as zip_ref:
+        zip_ref.extractall('pokemon_dataset')
 
 # Function to find the greatest batch size that fully divides the total samples
 def find_batch_size(total_samples, initial_batch_size):
@@ -32,8 +36,7 @@ tf.get_logger().setLevel('ERROR')
 tf.autograph.set_verbosity(2)
 
 # Download and extract the dataset
-dataset_name = 'mikoajkolman/pokemon-images-first
-
+download_and_extract_dataset()
 
 # Define the Pokémon classes to be classified
 classes = ['Doduo', 'Geodude', 'Zubat']