# Import required libraries
import cv2
import easyocr
import numpy as np
import gradio as gr

# Function to process the uploaded image and extract text
def extract_text_from_image(image):
    # Save the uploaded image to disk
    image_path = "uploaded_image.jpg"
    cv2.imwrite(image_path, image)

    # Read the image with OpenCV
    img = cv2.imread(image_path)

    # Initialize the EasyOCR reader
    reader = easyocr.Reader(['en', 'ar'], gpu=False)

    # Perform text detection
    results = reader.readtext(image_path)

    # Draw bounding boxes and overlay text on the image
    conf_threshold = 0.2
    extracted_text = []  # To store extracted text
    for (bbox, text, conf) in results:
        if conf > conf_threshold:
            # Append text to the list
            extracted_text.append(text)

            # Get coordinates
            top_left = tuple(map(int, bbox[0]))
            bottom_right = tuple(map(int, bbox[2]))

            # Draw rectangle and text
            img = cv2.rectangle(img, top_left, bottom_right, (0, 0, 255), 2)
            img = cv2.putText(img, text, top_left, cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)

    # Convert the image to RGB (Gradio requires RGB format)
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

    # Join the extracted text into a single string with line breaks
    extracted_text_str = "\n".join(extracted_text)

    return img, extracted_text_str

# Define the Gradio interface
interface = gr.Interface(
    fn=extract_text_from_image,
    inputs=gr.Image(type="numpy", label="Upload Image"),
    outputs=[
        gr.Image(type="numpy", label="Processed Image"),
        gr.Text(label="Extracted Text (Line by Line)")
    ],
    title="Image Text Extractor",
    description="Upload an image to extract text using EasyOCR. The extracted text will be displayed line by line.",
)

# Launch the Gradio app
interface.launch()