Update app.py

app.py

@@ -5,6 +5,8 @@ from pdf2image import convert_from_path
 from PyPDF2 import PdfReader
 import os
 import torch
+import pytesseract
+from pytesseract import TesseractError
 
 # Load the LayoutLMv3 model and processor
 processor = AutoProcessor.from_pretrained("microsoft/layoutlmv3-base")
@@ -25,15 +27,20 @@ def process_pdf(pdf, page_number):
 def process_image(image):
     try:
         image = image.convert("RGB")
+        
+        # Use Tesseract to extract text from the image
+        try:
+            text = pytesseract.image_to_string(image)
+        except TesseractError as e:
+            return f"Tesseract Error: {str(e)}. Make sure Tesseract is installed and in your PATH."
+        
         encoded_inputs = processor(image, return_tensors="pt")
         with torch.no_grad():
             outputs = model(**encoded_inputs)
         
-        # Placeholder for table extraction logic
-        # You would implement your table detection and extraction here
-        # For now, we'll just return the shape of the last hidden states
+        # For now, we'll just return the extracted text and the shape of the last hidden states
         last_hidden_states = outputs.last_hidden_state
-        return f"Image processed. Output shape: {last_hidden_states.shape}"
+        return f"Extracted Text:\n{text}\n\nImage processed. Output shape: {last_hidden_states.shape}"
     except Exception as e:
         return f"Error processing image: {str(e)}"