import gradio as gr
import cv2
from carPlate_recognize import car_plate_recognize

def Car_segmentation():
    def pridict(query_image=None):
        img_cvt = cv2.cvtColor(query_image, cv2.COLOR_BGR2RGB)
        plate, word_all = car_plate_recognize(img_cvt)
        return plate,word_all

    title = "<h1 align='center'>基于Opencv图像处理的车牌定位和分割</h1>"
    description = "对输入的车牌进行车牌的定位与分割操作"
    examples = [['images/car.jpg'],['images/car.png'],['images/car_test.jpg']]
    
    with gr.Blocks() as demo:
        gr.Markdown(title)
        gr.Markdown(description)
        with gr.Row():
            with gr.Column(scale=1):
                #with gr.Column(scale=2):
                img = gr.components.Image(label="图片")
                btn = gr.Button("点击定位与分割", )
            with gr.Column(scale=1):
                out_1 = gr.components.Image(label="车牌定位:",height="auto")
                out_2 = gr.Gallery(label="车牌分割:",columns=[4], height="auto",object_fit="contain")

        inputs = [img]
        outputs = [out_1,out_2]
        btn.click(fn=pridict, inputs=inputs, outputs=outputs)
        gr.Examples(examples, inputs=inputs)
        
    return demo
        
    
if __name__ == "__main__":
    with gr.TabbedInterface(
            [Car_segmentation()],
            ["Opencv车牌定位与分割"],
    ) as demo:
        demo.launch(show_api=False,inbrowser=False,)#auth=("admin", '1234')