# import gradio as gr
# import numpy as np
# from PIL import Image

# from inference import generate_image


# # Create a square image for the coordinate selector
# def create_selector_image():
#     # Create a white square with black border
#     size = 400
#     border = 2
#     img = np.ones((size, size, 3), dtype=np.uint8) * 255
#     # Add black border
#     img[:border, :] = 0  # top
#     img[-border:, :] = 0  # bottom
#     img[:, :border] = 0  # left
#     img[:, -border:] = 0  # right
#     return Image.fromarray(img)


# def process_click(image_idx: int, x: int, y: int) -> tuple[Image.Image, str]:
#     """
#     Process the click event on the coordinate selector
#     """
#     try:
#         # Normalize coordinates to [0, 1]
#         x_norm, y_norm = x / 400, y / 400  # Divide by image size (400x400)

#         # Debug message
#         debug_msg = f"Processing: image_idx={image_idx}, coordinates=({x_norm:.3f}, {y_norm:.3f})"
#         print(debug_msg)

#         # Generate image using the model
#         generated_img = generate_image(image_idx, x_norm, y_norm)
#         return generated_img, debug_msg
#     except Exception as e:
#         error_msg = f"Error: {str(e)}"
#         print(error_msg)
#         return None, error_msg


# with gr.Blocks() as demo:
#     gr.Markdown(
#         """
#     # Interactive Image Generation
#     Choose a reference image and click on the coordinate selector to generate a new image.
#     """
#     )

#     with gr.Row():
#         # Left column: Reference images and coordinate selector
#         with gr.Column(scale=1):
#             # Radio buttons for image selection
#             image_idx = gr.Radio(
#                 choices=list(range(2)), value=0, label="Select Reference Image", type="index"
#             )

#             # Display reference images
#             gallery = gr.Gallery(
#                 value=["imgs/pattern_1.png", "imgs/pattern_2.png"],
#                 columns=2,
#                 rows=1,
#                 height=500,
#                 label="Different Tasks",
#             )

#             # Coordinate selector
#             coord_selector = gr.Image(
#                 value=create_selector_image(),
#                 label="Click to select (x, y) coordinates",
#                 show_label=True,
#                 interactive=True,
#                 height=400,
#                 width=400,
#             )

#         # Right column: Generated image and debug info
#         with gr.Column(scale=1):
#             output_image = gr.Image(label="Generated Image", height=400)
#             debug_text = gr.Textbox(label="Debug Info", interactive=False)

#     # Handle click events using click instead of select
#     coord_selector.click(
#         fn=process_click,
#         inputs=[image_idx, coord_selector],  # coord_selector will provide x, y coordinates
#         outputs=[output_image, debug_text],
#     )

# if __name__ == "__main__":
#     print("Starting Gradio app...")
#     demo.launch(debug=True)


import gradio as gr
import numpy as np
from PIL import Image


def create_white_square(size=400):
    # Create a white square image
    print("Creating white square")
    return np.full((size, size, 3), 255, dtype=np.uint8)


def get_click_coordinates(evt: gr.SelectData):
    # Get click coordinates
    x, y = evt.index
    print(f"Clicked at coordinates: x={x}, y={y}")
    return f"Clicked at coordinates: x={x}, y={y}"


# Create the interface
with gr.Blocks() as demo:
    gr.Markdown("## Click Coordinate Detector\nClick anywhere on the white square to see coordinates")

    # Display the white square
    image = gr.Image(
        label="Click on the white square",
        value=create_white_square(),
        interactive=True,
        height=400,
        width=400,
        mirror_webcam=False,
    )

    # Display coordinates
    output_text = gr.Textbox(label="Coordinates")
    print("oh yeah")
    # Handle click events
    image.select(get_click_coordinates, inputs=[], outputs=output_text)

# Launch the app
if __name__ == "__main__":
    demo.launch()