Create mmsocrapp.py

mmsocrapp.py

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+import streamlit as st
+from transformers import TrOCRProcessor, VisionEncoderDecoderModel
+from PIL import Image
+
+# Load Hugging Face model
+processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-handwritten")
+model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-handwritten")
+
+st.title("OCR Application")
+uploaded_file = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
+
+if uploaded_file:
+    # Process the image
+    image = Image.open(uploaded_file).convert("RGB")
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    # Perform OCR
+    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]
+
+    # Display OCR result
+    st.text("Extracted Text:")
+    st.write(generated_text)