Update app.py

app.py

@@ -1,23 +1,20 @@
 import streamlit as st
 from transformers import pipeline
+from PIL import Image
+import easyocr
 
-# Create a text2text-generation pipeline
-pipe = pipeline("text2text-generation", model="kaist-ai/prometheus-13b-v1.0")
+pipe = pipeline("text2text-generation", model="google/flan-t5-base")
 
 st.title("Text Classification Model")
 uploaded_file = st.file_uploader("Upload an image:")
 
 if uploaded_file is not None:
-    # Read the uploaded image
     image = Image.open(uploaded_file)
-
-    # Extract text from the image using OCR
-    ocr_results = extract_text(image)
+    ocr_reader = easyocr.Reader(['en'])
+    ocr_results = ocr_reader.readtext(image)
     extracted_text = " ".join([res[1] for res in ocr_results])
     st.markdown("**Extracted text:**")
     st.markdown(extracted_text)
-
-    # Generate an explanation for the extracted text using the Hugging Face pipeline
     explanation = pipe(extracted_text, max_length=100, do_sample=True)[0]["generated_text"]
     st.markdown("**Explanation:**")
     st.markdown(explanation)