import gradio as gr
import os
from gradio_app.config import setup_logging, setup_sys_path
from gradio_app.processor import gradio_process, update_preview, update_visibility

# Initialize logging and sys.path
setup_logging()
setup_sys_path()

# Load custom CSS
custom_css = open(os.path.join(os.path.dirname(__file__), "gradio_app", "static", "styles.css"), "r").read()

# Path to examples directory
examples_dir = os.path.join(os.path.dirname(__file__), "gradio_app", "assets", "examples", "license_plate_detector_ocr")

# Collect example files
examples = [
    {
        "Input File": os.path.join(examples_dir, "1", "lp_image.jpg"),
        "Output File": os.path.join(examples_dir, "1", "lp_image_output.jpg"),
        "Input Type": "Image"
    },
    {
        "Input File": os.path.join(examples_dir, "2", "lp_video.mp4"),
        "Output File": os.path.join(examples_dir, "2", "lp_video_output.mp4"),
        "Input Type": "Video"
    }
]

# Function to handle example selection
def select_example(input_file, input_type):
    return input_file, input_type, None, None, None  # Reset outputs

# Gradio Interface
with gr.Blocks(css=custom_css) as iface:
    gr.Markdown(
        """
        # License Plate Detection and OCR
        Detect license plates from images or videos and read their text using 
        advanced computer vision and OCR for accurate identification.
        """,
        elem_classes="markdown-title"
    )

    with gr.Row():
        with gr.Column(scale=1):
            input_file = gr.File(label="Upload Image or Video", elem_classes="custom-file-input")
            input_type = gr.Radio(choices=["Image", "Video"], label="Input Type", value="Image", elem_classes="custom-radio")
            with gr.Blocks():
                input_preview_image = gr.Image(label="Input Preview", visible=True, elem_classes="custom-image")
                input_preview_video = gr.Video(label="Input Preview", visible=False, elem_classes="custom-video")
            with gr.Row():
                clear_button = gr.Button("Clear", variant="secondary", elem_classes="custom-button secondary")
                submit_button = gr.Button("Submit", variant="primary", elem_classes="custom-button primary")
            
            # Examples table
            gr.Markdown("### Examples")
            examples_table = gr.Dataframe(
                value=[[ex["Input File"], ex["Output File"], ex["Input Type"]] for ex in examples],
                headers=["Input File", "Output File", "Input Type"],
                interactive=False,
                elem_classes="custom-table"
            )
            examples_table.click(
                fn=select_example,
                inputs=[examples_table, examples_table],
                outputs=[input_file, input_type, output_image, output_video, output_text]
            )

        with gr.Column(scale=2):
            with gr.Blocks():
                output_image = gr.Image(label="Processed Output (Image)", type="numpy", visible=True, elem_classes="custom-image")
                output_video = gr.Video(label="Processed Output (Video)", visible=False, elem_classes="custom-video")
            output_text = gr.Textbox(label="Detected License Plates", lines=10, elem_classes="custom-textbox")

    # Update preview and output visibility when input type changes
    input_type.change(
        fn=update_visibility,
        inputs=input_type,
        outputs=[input_preview_image, input_preview_video, output_image, output_video]
    )

    # Update preview when file is uploaded
    input_file.change(
        fn=update_preview,
        inputs=[input_file, input_type],
        outputs=[input_preview_image, input_preview_video]
    )

    # Bind the processing function
    submit_button.click(
        fn=gradio_process,
        inputs=[input_file, input_type],
        outputs=[output_image, output_video, output_text, input_preview_image, input_preview_video]
    )

    # Clear button functionality
    clear_button.click(
        fn=lambda: (None, None, None, "Image", None, None, None, None),
        outputs=[input_file, output_image, output_video, input_type, input_preview_image, input_preview_video, output_image, output_video]
    )

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