fix: file_upload uses BytesIO

app.py

@@ -2,6 +2,7 @@ import torch
 import streamlit as st
 
 from PIL import Image
+from io import BytesIO
 from transformers import VisionEncoderDecoderModel, VisionEncoderDecoderConfig , DonutProcessor
 
 
@@ -50,6 +51,17 @@ def run_prediction(sample):
 
 task_prompt = f"<s>"
 
+st.markdown("""
+<h3 align="center">
+  <img
+    src="https://https://huggingface.co/spaces/unstructuredio/receipt-parser/tree/main/img/unstructured_logo.png"
+    height="200"
+  >
+</h3>
+
+<div align="center">
+""")
+
 st.text('''
 This is OCR-free Document Understanding Transformer nicknamed 🍩. It was fine-tuned with 1000 receipt images -> SROIE dataset.
 The original 🍩 implementation can be found on: https://github.com/clovaai/donut
@@ -59,7 +71,7 @@ image_upload = None
 with st.sidebar:
     information = st.radio(
     "What information inside the are you interested in?",
-    ('Receipt Summary', 'Receipt Menu Details', 'Extract all!'))
+    ('Receipt Summary', 'Receipt Menu Details', 'Extract all'))
     receipt = st.selectbox('Pick one 🧾', ['1', '2', '3', '4', '5', '6'], index=1)
 
     # file upload
@@ -67,7 +79,7 @@ with st.sidebar:
     if uploaded_file is not None:
         # To read file as bytes:
         image_bytes_data = uploaded_file.getvalue()
-        image_upload = Image.open(image_bytes_data)  #.frombytes('RGBA', (128,128), image_bytes_data, 'raw')
+        image_upload = Image.open(BytesIO(image_bytes_data))  #.frombytes('RGBA', (128,128), image_bytes_data, 'raw')
         # st.write(bytes_data)
 
 st.text(f'{information} mode is ON!\nTarget 🧾: {receipt}')  # \n(opening image @:./img/receipt-{receipt}.png)')