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import gradio as gr
import pytesseract
from pdf2image import convert_from_path
from PIL import Image
import os
# Function to perform OCR
def ocr(input_file, lang='fas'): # 'fas': Persian language (Farsi)
extracted_text = ""
# Check if the input file is a PDF or an image
if isinstance(input_file, str) and input_file.endswith('.pdf'): # Check if the file is a PDF
# Convert PDF to images
images = convert_from_path(input_file)
# Loop through each image and perform OCR
for page_number, image in enumerate(images):
text = pytesseract.image_to_string(image, lang=lang)
extracted_text += text
elif isinstance(input_file, Image.Image): # If the input is an image
text = pytesseract.image_to_string(input_file, lang=lang)
extracted_text = text
return extracted_text
def gradio_interface():
# Define Gradio inputs and outputs
input_type = gr.Radio(["PDF", "Image"], label="Choose Input Type", value="PDF")
file_input = gr.File(label="Upload PDF/Image")
language_input = gr.Dropdown(
label="Select OCR Language",
choices=[
("English", "eng"),
("Mandarin Chinese", "chi_sim"),
("Hindi", "hin"),
("Spanish", "spa"),
("French", "fra"),
("Standard Arabic", "ara"),
("Bengali", "ben"),
("Portuguese", "por"),
("Russian", "rus"),
("Urdu", "urd"),
("Persian (Farsi)", "fas")
],
value="fas" # Default to Persian
)
output_text = gr.Textbox(label="Extracted Text", interactive=False)
# Function to process the inputs and return the outputs
def process(input_type, file, lang):
if input_type == "PDF":
extracted_text = ocr(file.name, lang)
else:
image = Image.open(file.name)
extracted_text = ocr(image, lang)
return extracted_text
# Create and launch Gradio interface
gr.Interface(
fn=process,
inputs=[input_type, file_input, language_input],
outputs=[output_text],
title="OCR (PDF/Image)",
description="Upload a PDF or Image, select the OCR language, and extract the text."
).launch()
# Call the function to create the interface
gradio_interface()
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