Update app.py

app.py

@@ -2,6 +2,10 @@ import datasets
 from datasets import load_dataset
 import gradio as gr
 import torch
+from transformers import Trainer, TrainingArguments
+from transformers import AutoModelForImageClassification
+import numpy as np
+import evaluate
 from transformers import AutoFeatureExtractor, AutoModelForImageClassification
 
 dataset = load_dataset('beans') # This should be the same as the first line of Python code in this Colab notebook
@@ -10,6 +14,7 @@ extractor = AutoFeatureExtractor.from_pretrained("saved_model_files")
 model = AutoModelForImageClassification.from_pretrained("saved_model_files")
 
 labels = dataset['train'].features['labels'].names
+image_processor = ViTImageProcessor.from_pretrained('google/vit-base-patch16-224')
 
 def classify(im):
   features = image_processor(im, return_tensors='pt')