'literally should just work rn'

app.py

@@ -1,16 +1,23 @@
 import streamlit as st
-
 from transformers import TrOCRProcessor, VisionEncoderDecoderModel
 from PIL import Image
-import requests
 
-# load image from the IAM database
-url = "https://fki.tic.heia-fr.ch/static/img/a01-122-02-00.jpg"
-image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+# Streamlit app
+st.title("Handwritten Text Recognition")
+
+# Upload an image
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
-processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
-model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
-pixel_values = processor(images=image, return_tensors="pt").pixel_values
+if uploaded_file is not None:
+    image = Image.open(uploaded_file).convert("RGB")
+    st.image(image, caption='Uploaded Image', use_column_width=True)
+    
+    processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
+    model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
+    pixel_values = processor(images=image, return_tensors="pt").pixel_values
 
-generated_ids = model.generate(pixel_values)
-generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    generated_ids = model.generate(pixel_values)
+    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
+    
+    st.write("Recognized Text:")
+    st.write(generated_text)