Update app.py

app.py

@@ -1,22 +1,16 @@
-from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 import requests
 from PIL import Image
 import streamlit as st
+from transformers import pipeline
 
+pipe = pipeline("image-to-text", model="microsoft/trocr-large-printed")     
 st.title("Duh!")
-processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
-model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
 
 # load image from the IAM dataset
 url = "https://parivahan.gov.in/rcdlstatus/DispplayCaptcha?txtp_cd=1&bkgp_cd=2&noise_cd=2&gimp_cd=3&txtp_length=5&pfdrid_c=true?1429026471&pfdrid_c=true"
 image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
 
-pixel_values = processor(image, return_tensors="pt").pixel_values
-generated_ids = model.generate(pixel_values)
-
-generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-
 col1, col2 = st.columns(2)
-
+predictions = pipeline(image)
 col1.image(image, use_column_width=True)
-col2.subheader(f"Detected Text: {generated_text}")
+col2.subheader(f"Detected Text: {predictions}")