Update eda.py

eda.py

@@ -27,47 +27,24 @@ def run():
     
 
     st.markdown('---')
-    import os
-    import torch
-    import torchvision.transforms as transforms
-    from torch.utils.data import DataLoader
-    from datasets import load_dataset
-    
+        
     # Define the path to the dataset
-    dataset_path = 'andrewsunanda/fast_food_image_classification'
     
     # Load the dataset from Hugging Face
-    dataset = load_dataset(dataset_path)
+    from datasets import load_dataset
+    dataset = load_dataset("andrewsunanda/fast_food_image_classification")
     
     # Define the batch size and image size
     batch_size = 256
     img_size = (64, 64)
     
     # Define the paths to the train, validation, and test folders
+    dataset_path = "andrewsunanda/fast_food_image_classification"
     train_path = os.path.join(dataset_path, 'Train')
     valid_path = os.path.join(dataset_path, 'Valid')
     test_path = os.path.join(dataset_path, 'Test')
     
-    # Define the transforms for the dataset
-    transform = transforms.Compose([
-        transforms.Resize(img_size),
-        transforms.ToTensor(),
-    ])
-    
-    # Load the training dataset
-    train_dataset = dataset['train']
-    train_dataset = train_dataset.map(lambda x: {'image': transform(x['image']), 'label': x['label']})
-    train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True)
-    
-    # Load the validation dataset
-    valid_dataset = dataset['validation']
-    valid_dataset = valid_dataset.map(lambda x: {'image': transform(x['image']), 'label': x['label']})
-    valid_loader = DataLoader(valid_dataset, batch_size=batch_size, shuffle=False)
     
-    # Load the testing dataset
-    test_dataset = dataset['test']
-    test_dataset = test_dataset.map(lambda x: {'image': transform(x['image']), 'label': x['label']})
-    test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False)
     # Create data generators for training, validation, and testing
     train_datagen = ImageDataGenerator(
         rescale=1./255,