Update app.py

app.py

@@ -1,34 +1,14 @@
-import transformers
 import torch
-import torchvision
-from transformers import TrainingArguments, Trainer
-from transformers import ViTImageProcessor
-from transformers import ViTForImageClassification
-from torch.utils.data import DataLoader
-from datasets import load_dataset
-from torchvision.transforms import (CenterCrop, 
-                                    Compose, 
-                                    Normalize, 
-                                    RandomHorizontalFlip,
-                                    RandomResizedCrop, 
-                                    Resize, 
-                                    ToTensor)
 from transformers import ViTImageProcessor, ViTForImageClassification
 from PIL import Image
-import torch
 import torch.nn.functional as F
-import time
 import gradio as gr
  
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
  
 processor = ViTImageProcessor.from_pretrained("ViT_LCZs_v3",local_files_only=True)
 model = ViTForImageClassification.from_pretrained("ViT_LCZs_v3",local_files_only=True).to(device)
- 
-import os, glob
 
-examples_dir = './samples'
-example_files = glob.glob(os.path.join(examples_dir, '*.jpg'))
 
 def classify_image(image):