Update app.py

app.py

@@ -4,8 +4,13 @@ import torch
 from PIL import Image
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-tokenizer = AutoTokenizer.from_pretrained("usvsnsp/code-vs-nl")
-model = AutoModelForSequenceClassification.from_pretrained("usvsnsp/code-vs-nl")
+st.title(':blue[_SnapCode_]')
+
+with st.spinner('Model is loading'):
+    tokenizer = AutoTokenizer.from_pretrained("usvsnsp/code-vs-nl")
+    model = AutoModelForSequenceClassification.from_pretrained("usvsnsp/code-vs-nl")
+
+st.success('Model loaded')
 
 def classify_text(text):
     input_ids = tokenizer(text, return_tensors="pt")
@@ -20,7 +25,7 @@ uploaded_file = st.file_uploader("Upload Image", type= ['png', 'jpeg', 'jpg'])
 
 if uploaded_file is not None:
     img = Image.open(uploaded_file)
-    ocr_list = [x for x in pytesseract.image_to_string(uploaded_file).split("\n") if x != '']
+    ocr_list = [x for x in pytesseract.image_to_string(img).split("\n") if x != '']
     ocr_class = [classify_text(x) for x in ocr_list]
     idx = []
     for i in range(len(ocr_class)):