Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+import requests
+import io
+
+# Load the OCR model and processor
+model_name = "microsoft/trocr-base-stage1"
+processor = TrOCRProcessor.from_pretrained(model_name)
+model = VisionEncoderDecoderModel.from_pretrained(model_name)
+
+# Streamlit app title
+st.title("OCR with TrOCR")
+
+# Upload image section
+uploaded_image = st.file_uploader("Upload an image for OCR", type=["jpg", "jpeg", "png"])
+
+if uploaded_image is not None:
+    # Open and display the uploaded image
+    image = Image.open(uploaded_image)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Convert image to suitable format
+    inputs = processor(images=image, return_tensors="pt")
+
+    # Perform OCR
+    with torch.no_grad():
+        outputs = model.generate(**inputs)
+
+    # Decode the generated text
+    text = processor.decode(outputs[0], skip_special_tokens=True)
+
+    # Display the OCR result
+    st.write("Extracted Text:")
+    st.text(text)