import os
import gradio as gr
from Plan.AiLLM import llm_recognition
from Plan.pytesseractOCR import ocr_recognition
from Preprocess.preprocessImg import (
    preprocess_image001, preprocess_image002, preprocess_image003,
    preprocess_image004, preprocess_image005
)

# 取得所有語言清單
languages = os.popen('tesseract --list-langs').read().split('\n')[1:-1]


def preprocess_and_ocr(image, valid_type, language):
    # 方案一
    pre_img_001 = preprocess_image001(image)
    ocr_result_001 = ocr_recognition(pre_img_001, valid_type, language)
    # 方案二
    pre_img_002 = preprocess_image002(image)
    ocr_result_002 = ocr_recognition(pre_img_002, valid_type, language)
    # 方案三
    pre_img_003 = preprocess_image003(image)
    ocr_result_003 = ocr_recognition(pre_img_003, valid_type, language)
    # 方案四
    pre_img_004 = preprocess_image004(image)
    ocr_result_004 = ocr_recognition(pre_img_004, valid_type, language)
    # 方案五
    pre_img_005 = preprocess_image005(image)
    ocr_result_005 = ocr_recognition(pre_img_005, valid_type, language)

    return (pre_img_001, pre_img_002, pre_img_003, pre_img_004, pre_img_005,
            ocr_result_001, ocr_result_002, ocr_result_003, ocr_result_004, ocr_result_005)


def preprocess_and_llm(image, valid_type, language):
    # 方案一
    pre_img_001 = preprocess_image001(image)
    llm_result_001 = llm_recognition(pre_img_001, valid_type, language)
    # 方案二
    pre_img_002 = preprocess_image002(image)
    llm_result_002 = llm_recognition(pre_img_002, valid_type, language)
    # 方案三
    pre_img_003 = preprocess_image003(image)
    llm_result_003 = llm_recognition(pre_img_003, valid_type, language)
    # 方案四
    pre_img_004 = preprocess_image004(image)
    llm_result_004 = llm_recognition(pre_img_004, valid_type, language)
    # 方案五
    pre_img_005 = preprocess_image005(image)
    llm_result_005 = llm_recognition(pre_img_005, valid_type, language)

    return (pre_img_001, pre_img_002, pre_img_003, pre_img_004, pre_img_005,
            llm_result_001, llm_result_002, llm_result_003, llm_result_004, llm_result_005)


with gr.Blocks() as demo:
    with gr.Row():
        image_input = gr.Image(type="pil", label="上傳圖片")
        validation_type = gr.Dropdown(choices=["身分證正面", "身分證反面"], label="驗證類別")
        language_dropdown = gr.Dropdown(choices=languages, value="chi_tra", label="語言")

    with gr.Row():
        ocr_button = gr.Button("使用 OCR")
        llm_button = gr.Button("使用 AI LLM")

    with gr.Row():
        preprocess_output_001 = gr.Image(type="pil", label="預處理後的圖片-方案一")
        ocr_output_001 = gr.JSON(label="OCR-001-解析結果")
        llm_output_001 = gr.JSON(label="AiLLM-001-解析結果")
    with gr.Row():
        preprocess_output_002 = gr.Image(type="pil", label="預處理後的圖片-方案二")
        ocr_output_002 = gr.JSON(label="OCR-002-解析結果")
        llm_output_002 = gr.JSON(label="AiLLM-002-解析結果")

    with gr.Row():
        preprocess_output_003 = gr.Image(type="pil", label="預處理後的圖片-方案三")
        ocr_output_003 = gr.JSON(label="OCR-003-解析結果")
        llm_output_003 = gr.JSON(label="AiLLM-003-解析結果")
    with gr.Row():
        preprocess_output_004 = gr.Image(type="pil", label="預處理後的圖片-方案四")
        ocr_output_004 = gr.JSON(label="OCR-004-解析結果")
        llm_output_004 = gr.JSON(label="AiLLM-004-解析結果")
    with gr.Row():
        preprocess_output_005 = gr.Image(type="pil", label="預處理後的圖片-方案五")
        ocr_output_005 = gr.JSON(label="OCR-005-解析結果")
        llm_output_005 = gr.JSON(label="AiLLM-005-解析結果")

    ocr_button.click(preprocess_and_ocr, inputs=[image_input, validation_type, language_dropdown],
                     outputs=[
                         preprocess_output_001, preprocess_output_002, preprocess_output_003, preprocess_output_004,
                         preprocess_output_005,
                         ocr_output_001, ocr_output_002, ocr_output_003, ocr_output_004, ocr_output_005
                     ])
    llm_button.click(preprocess_and_llm, inputs=[image_input, validation_type, language_dropdown],
                     outputs=[
                         preprocess_output_001, preprocess_output_002, preprocess_output_003, preprocess_output_004,
                         preprocess_output_005,
                         llm_output_001, llm_output_002, llm_output_003, llm_output_004, llm_output_005
                     ])

demo.launch(share=False)