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import os
import fitz # PyMuPDF for PDF handling
import easyocr # OCR for text extraction
import tempfile
import streamlit as st
def extract_text_with_positions_using_ocr(pdf_path):
"""
Extract text with bounding box positions using OCR for both English and Arabic text.
:param pdf_path: Path to the input PDF file.
:return: List of dictionaries containing text and positions for each page.
"""
extracted_data = []
doc = fitz.open(pdf_path)
# Convert each PDF page to an image for OCR processing
for page_num in range(len(doc)):
page = doc.load_page(page_num)
pix = page.get_pixmap(dpi=300) # Convert PDF page to image
image_path = f"temp_page_{page_num}.png"
pix.save(image_path)
# Perform OCR on the image
reader = easyocr.Reader(['en', 'ar']) # Supports English and Arabic
results = reader.readtext(image_path, detail=1) # detail=1 returns bounding box info
# Extract text and positions
page_data = []
for (bbox, text, confidence) in results:
(x0, y0), (x1, y1) = bbox[0], bbox[2]
page_data.append({
"text": text,
"x0": x0,
"y0": y1, # Adjust to bottom-left corner (PDF coordinates)
"x1": x1,
"y1": y0,
"font_size": y1 - y0 # Approximate font size
})
extracted_data.append(page_data)
# Cleanup temporary image
os.remove(image_path)
return extracted_data
def overlay_text_with_fonts(pdf_path, extracted_data, output_pdf_path):
"""
Overlay extracted text onto the original PDF using fonts from different font families.
:param pdf_path: Path to the input PDF file.
:param extracted_data: List of extracted text with positions.
:param output_pdf_path: Path to save the output PDF file.
"""
doc = fitz.open(pdf_path)
# Define font families for overlay
font_families = ["Times-Roman", "Helvetica", "Courier"] # Example font families
for page_num, page_data in enumerate(extracted_data):
page = doc[page_num]
for item in page_data:
font = font_families[page_num % len(font_families)] # Rotate fonts across pages
page.insert_text(
(item["x0"], item["y0"]),
item["text"],
fontsize=item["font_size"],
fontname=font,
color=(0, 0, 0), # Black text
render_mode=0 # Ensure text is not outlined
)
doc.save(output_pdf_path)
print(f"PDF saved to: {output_pdf_path}")
def process_pdf(uploaded_pdf, output_pdf_path):
"""
Process the uploaded PDF to extract text using OCR and overlay it as editable text.
:param uploaded_pdf: The uploaded PDF file.
:param output_pdf_path: Path to save the output PDF file.
"""
with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_pdf:
temp_pdf.write(uploaded_pdf.read())
temp_pdf_path = temp_pdf.name
# Step 1: Extract text using OCR
extracted_data = extract_text_with_positions_using_ocr(temp_pdf_path)
# Step 2: Overlay extracted text onto the original PDF
overlay_text_with_fonts(temp_pdf_path, extracted_data, output_pdf_path)
# Cleanup temporary file
if os.path.exists(temp_pdf_path):
os.remove(temp_pdf_path)
# Streamlit App
def main():
st.title("PDF Text OCR and Overlay Tool")
st.write("Upload a PDF to extract and overlay text as editable layers with different fonts.")
uploaded_file = st.file_uploader("Upload PDF", type=["pdf"])
if uploaded_file:
output_pdf_path = "corrected_output_with_fonts.pdf"
with st.spinner("Processing your PDF..."):
process_pdf(uploaded_file, output_pdf_path)
st.success("PDF processing complete!")
# Provide a download button for the processed PDF
with open(output_pdf_path, "rb") as f:
st.download_button(
label="Download Corrected PDF",
data=f,
file_name="corrected_output_with_fonts.pdf",
mime="application/pdf"
)
# Cleanup the processed output PDF
if os.path.exists(output_pdf_path):
os.remove(output_pdf_path)
if __name__ == "__main__":
main() |