import gradio as gr
import ObjCharRec
from deep_translator import GoogleTranslator
import markdown as md
import translate_speak
import base64

langs_list = GoogleTranslator().get_supported_languages()
langs_dict = GoogleTranslator().get_supported_languages(as_dict=True)

def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# Encode the images
github_logo_encoded = encode_image("Images/github-logo.png")
linkedin_logo_encoded = encode_image("Images/linkedin-logo.png")
website_logo_encoded = encode_image("Images/ai-logo.png")

usecase_img_encoded = encode_image("Images/UML/Usecase.png")
class_img_encoded = encode_image("Images/UML/class.png")
object_img_encoded = encode_image("Images/UML/object.png")
sequence_img_encoded = encode_image("Images/UML/sequence.png")
component_img_encoded = encode_image("Images/UML/component.png")
colab_img_encoded = encode_image("Images/UML/colab.png")
activity_img_encoded = encode_image("Images/UML/activity.png")

with gr.Blocks(theme=gr.themes.Ocean(font=[gr.themes.GoogleFont("Noto Sans")]), css='footer {visibility: hidden}') as main_interface:
    gr.Markdown("# Welcome to The Linguistic Lens 👓🗣️")
    with gr.Tabs():
        with gr.TabItem("Intro"):
            gr.HTML(md.description)
            gr.HTML(md.usecase_diagram.format(usecase_img_encoded))
            gr.HTML(md.class_diagram.format(class_img_encoded))
            gr.HTML(md.object_diagram.format(object_img_encoded))
            gr.HTML(md.sequence_diagram.format(sequence_img_encoded))
            gr.HTML(md.colab_diagram.format(colab_img_encoded))
            gr.HTML(md.activity_diagram.format(activity_img_encoded))
            gr.HTML(md.component_diagram.format(component_img_encoded))

        with gr.TabItem("⭐Translator"):
            with gr.Row():
                with gr.Column():
                    with gr.Row():
                        image_input = gr.Image(label="Upload Image")

                    with gr.Row():
                        clear_btn = gr.ClearButton()
                        submit_btn = gr.Button("Submit")
                with gr.Column():
                    with gr.Row():
                        output_text = gr.Text(label="Output")
                        audio_out = gr.Audio(label="Streamed Audio")
                    lang_drop = gr.Dropdown(langs_dict, label="language", interactive=True)
                    translate_btn = gr.Button("Translate")
                    with gr.Row():
                        translated_txt = gr.Text(label="translated text")
                        translated_out = gr.Audio(label="Streamed Audio")

            submit_btn.click(fn=ObjCharRec.ocr_with_paddle, inputs=image_input, outputs=[output_text, audio_out])
            translate_btn.click(fn=translate_speak.translate_txt, inputs=[lang_drop, output_text],
                                outputs=[translated_txt, translated_out])
            clear_btn.click(lambda: [None] * 5, outputs=[image_input, output_text, translated_txt, translated_out, audio_out])

        with gr.TabItem("Simple OCR"):
            gr.Markdown("Paddle OCR")
            with gr.Row():
                with gr.Column():
                    image_input = gr.Image(label="Upload Image")
                    with gr.Row():
                        clear_btn = gr.ClearButton()
                        submit_btn = gr.Button("Submit")
                output_text = gr.Text(label="Output")

            submit_btn.click(fn=ObjCharRec.ocr_with_paddle, inputs=image_input, outputs=output_text)
            clear_btn.click(lambda :[None]*2, outputs=[image_input, output_text])

        gr.HTML(md.footer.format(github_logo_encoded, linkedin_logo_encoded, website_logo_encoded))
        # gr.Markdown(md.footer.format(github_logo_encoded, linkedin_logo_encoded, website_logo_encoded))


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