app.py

import gradio as gr
import cv2
import pytesseract
import numpy as np
import pkg_resources

# Function to log installed packages (for debugging purposes)
def log_installed_packages():
    installed_packages = {pkg.key: pkg.version for pkg in pkg_resources.working_set}
    return installed_packages

# Function to process the image
def preprocess_image_for_tesseract(image):
    # Convert the image to grayscale
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    return gray

def ocr_and_search(image, keyword):
    processed_image = preprocess_image_for_tesseract(image)

    # Ensure Tesseract is available
    if not pytesseract.pytesseract.get_tesseract_version():
        return "Tesseract is not available in PATH.", []

    try:
        # Extract text in both Hindi and English
        extracted_text = pytesseract.image_to_string(processed_image, lang='hin+eng')
    except Exception as e:
        return f"Error during OCR: {str(e)}", []

    # Search for the keyword in the extracted text (case insensitive)
    search_results = [line for line in extracted_text.split('\n') if keyword.lower() in line.lower()]
    
    return extracted_text, search_results

# Create Gradio interface
iface = gr.Interface(
    fn=ocr_and_search,
    inputs=[gr.Image(type="numpy"), gr.Textbox(label="Keyword")],
    outputs=["text", "text"],
    title="OCR and Keyword Search",
    description="Upload an image with text and search for a keyword."
)

# Optionally log installed packages
print(log_installed_packages())

# Launch the interface
iface.launch(share=True)