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from mmocr.ocr import MMOCR
import gradio as gr
import cv2

model_dir = 'model'
ocr = MMOCR(det_config=f'{model_dir}/config.py',
            det_ckpt=f'{model_dir}/epoch_40.pth', device='cpu')
def get_rec(points):
    xs = []
    ys = []
    for ix, iv in enumerate(points):
        if ix % 2:
            ys.append(iv)
        else:
            xs.append(iv)
    return (min(xs), min(ys)), (max(xs), max(ys))
        
    
def predict(image_input):
    draw_img = image_input.copy()
    output = ocr.readtext(image_input)
    for polygon in output['det_polygons']:
        p0, p1 = get_rec([int(i) for i in polygon])
        draw_img = cv2.rectangle(draw_img, p0, p1, (255,255,255))
    return draw_img

def run():
    demo = gr.Interface(
        fn=predict,
        inputs=gr.components.Image(),
        outputs=gr.components.Image(),
    )

    demo.launch(server_name="0.0.0.0", server_port=7860)


if __name__ == "__main__":
    run()