Update app.py

app.py

@@ -1,34 +1,96 @@
 import gradio as gr
-from PyPDF2 import PdfReader
-import io
+import pytesseract
+from PIL import Image
+import pdf2image
+import tempfile
+import os
+import cv2
+import numpy as np
 
-# Function to convert PDF to text (handles both byte data and file uploads)
-def pdf_to_text(file_input):
-    # If the input is in byte format (i.e., it comes as raw bytes from a file or Base64 encoding)
-    if isinstance(file_input, bytes):
-        # Treat it as byte data and convert it to a file-like object
-        pdf_file = io.BytesIO(file_input)
-    else:
-        # If it's a regular PDF file (file upload), open it from the file input
-        pdf_file = file_input.name  # This will get the file path if it's a regular file upload
+# You may need to set the path to tesseract executable if it's not in PATH
+# pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'  # For Windows
+# For Linux/Mac, ensure Tesseract is installed
+
+def preprocess_image(img):
+    """Preprocess image to improve OCR accuracy for handwritten text"""
+    # Convert to grayscale
+    gray = cv2.cvtColor(np.array(img), cv2.COLOR_BGR2GRAY)
+    
+    # Apply thresholding
+    _, binary = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)
+    
+    # Noise removal
+    kernel = np.ones((1, 1), np.uint8)
+    binary = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel)
+    binary = cv2.morphologyEx(binary, cv2.MORPH_OPEN, kernel)
+    
+    # Invert back
+    binary = 255 - binary
+    
+    return Image.fromarray(binary)
+
+def extract_text_from_image(img):
+    """Extract text from an image using OCR"""
+    # Preprocess for better handwriting recognition
+    processed_img = preprocess_image(img)
+    
+    # Use pytesseract with configuration optimized for handwritten text
+    custom_config = r'--oem 3 --psm 6 -l eng -c tessedit_char_whitelist="ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789.,!?@#$%^&*()-+=_:;\'\" "'
+    text = pytesseract.image_to_string(processed_img, config=custom_config)
+    
+    return text.strip()
 
-    try:
-        reader = PdfReader(pdf_file)
-        text = ""
-        for page in reader.pages:
-            text += page.extract_text()
-        return text
-    except Exception as e:
-        return f"Error while processing the PDF: {str(e)}"
+def extract_text_from_pdf(pdf_path):
+    """Extract text from all pages of a PDF file"""
+    # Convert PDF to images
+    with tempfile.TemporaryDirectory() as path:
+        images = pdf2image.convert_from_path(pdf_path, output_folder=path)
+        
+        # Extract text from each page
+        full_text = []
+        for img in images:
+            text = extract_text_from_image(img)
+            full_text.append(text)
+        
+        return "\n\n--- Page Break ---\n\n".join(full_text)
+
+def process_file(file):
+    """Process the uploaded file (PDF or image)"""
+    if file is None:
+        return "No file uploaded. Please upload an image or PDF file."
+    
+    file_extension = os.path.splitext(file.name)[1].lower()
+    
+    if file_extension == ".pdf":
+        # Process PDF
+        return extract_text_from_pdf(file.name)
+    elif file_extension in [".jpg", ".jpeg", ".png", ".bmp", ".tiff", ".tif"]:
+        # Process Image
+        img = Image.open(file.name)
+        return extract_text_from_image(img)
+    else:
+        return "Unsupported file format. Please upload a PDF or image file (JPG, PNG, BMP, TIFF)."
 
-# Gradio interface: allow both file uploads and byte data input
-iface = gr.Interface(
-    fn=pdf_to_text,  # Function to call for text extraction
-    inputs=gr.File(label="Upload PDF or send Byte data"),  # File input
-    outputs="text",  # Output the extracted text
-    title="PDF to Text Conversion",
-    description="Upload a PDF file or send byte data (Base64 encoded) to extract its text."
-)
+# Create Gradio interface
+with gr.Blocks(title="Handwritten Text OCR Extractor") as app:
+    gr.Markdown("# Handwritten Text OCR Extraction Tool")
+    gr.Markdown("Upload an image or PDF containing handwritten text to extract the content.")
+    
+    with gr.Row():
+        with gr.Column():
+            file_input = gr.File(label="Upload Image or PDF", file_types=["image", "pdf"])
+            extract_button = gr.Button("Extract Text")
+        
+        with gr.Column():
+            text_output = gr.Textbox(label="Extracted Text", lines=10, placeholder="Extracted text will appear here...")
+    
+    extract_button.click(fn=process_file, inputs=[file_input], outputs=[text_output])
+    
+    gr.Markdown("### Notes:")
+    gr.Markdown("- For best results, ensure the handwriting is clear and the image is well-lit")
+    gr.Markdown("- The system works best with dark text on light background")
+    gr.Markdown("- Multiple page PDFs will show page breaks in the output")
 
+# Launch the app
 if __name__ == "__main__":
-    iface.launch()
+    app.launch()