# Copyright (c) OpenMMLab. All rights reserved.
import argparse

import cv2
import torch

from mmocr.apis import init_detector, model_inference
from mmocr.datasets import build_dataset  # noqa: F401
from mmocr.models import build_detector  # noqa: F401


def parse_args():
    parser = argparse.ArgumentParser(description='MMDetection webcam demo.')
    parser.add_argument('config', help='Test config file path.')
    parser.add_argument('checkpoint', help='Checkpoint file.')
    parser.add_argument(
        '--device', type=str, default='cuda:0', help='CPU/CUDA device option.')
    parser.add_argument(
        '--camera-id', type=int, default=0, help='Camera device id.')
    parser.add_argument(
        '--score-thr', type=float, default=0.5, help='Bbox score threshold.')
    args = parser.parse_args()
    return args


def main():
    args = parse_args()

    device = torch.device(args.device)

    model = init_detector(args.config, args.checkpoint, device=device)
    if model.cfg.data.test['type'] == 'ConcatDataset':
        model.cfg.data.test.pipeline = model.cfg.data.test['datasets'][
            0].pipeline

    camera = cv2.VideoCapture(args.camera_id)

    print('Press "Esc", "q" or "Q" to exit.')
    while True:
        ret_val, img = camera.read()
        result = model_inference(model, img)

        ch = cv2.waitKey(1)
        if ch == 27 or ch == ord('q') or ch == ord('Q'):
            break

        model.show_result(
            img, result, score_thr=args.score_thr, wait_time=1, show=True)


if __name__ == '__main__':
    main()
