import gradio as gr
import cv2
import numpy as np
from captcha_solver_hf import solve_captcha

def predict_captcha(image):
    if image is None:
        return "Please upload an image."
    img_array = np.array(image)
    img_cv = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
    result = solve_captcha(img_cv)
    return result

# Example images (replace these with actual CAPTCHA images)
examples = [
    "example_captcha1.png",
    "example_captcha2.png",
    "example_captcha3.png"
]

css = """
.gradio-container {
    font-family: 'Arial', sans-serif;
}
.gr-button {
    color: white;
    border-color: black;
    background: linear-gradient(45deg, #007bff, #00bcd4);
}
.gr-button:hover {
    background: linear-gradient(45deg, #0056b3, #008ba3);
}
.gr-form {
    flex-direction: column;
    align-items: center;
}
.gr-image-input {
    width: 100% !important;
    max-width: 400px;
    margin: auto;
}
.footer {
    margin-top: 20px;
    text-align: center;
    color: #666;
}
h1, h3 {
    text-align: center;
}
"""

with gr.Blocks(css=css) as iface:
    gr.Markdown(
    """
    # CAPTCHA Solver
    ### Unlock the Power of AI-Driven CAPTCHA Recognition
    Upload your CAPTCHA image and let our advanced AI model decipher it instantly!
    """
    )
    with gr.Column(scale=1):
        input_image = gr.Image(type="numpy", label="Upload CAPTCHA Image")
        output_text = gr.Textbox(label="Predicted Text")
    
    solve_button = gr.Button("Solve CAPTCHA", variant="primary")
    solve_button.click(fn=predict_captcha, inputs=input_image, outputs=output_text)
    
    gr.Examples(examples, inputs=input_image)
    
    gr.Markdown(
    """
    ### How It Works
    1. Upload a CAPTCHA image
    2. Click "Solve CAPTCHA"
    3. Get instant results!
    
    Our state-of-the-art AI model processes your image and provides accurate text recognition.
    """
    )
    
    gr.Markdown(
    """
    <div class="footer">
    Developed with ❤️ by Arnav Agarwal | © 2024 All Rights Reserved
    </div>
    """
    )

if __name__ == "__main__":
    iface.launch()