import os
import sys
from glob import glob
import cv2
import torch
sys.path.append(os.path.abspath(os.path.dirname(__file__)) + '/../../')
from botr.yolov8.model import Predictor


ROOT = os.path.abspath(os.path.dirname(__file__)) + '/../../'
model_path = ROOT + 'botr/yolov8/weights.pt'
image_size = 640
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")


def detect(image_np, predictor=None, show=False):
    if predictor is None:
        predictor = Predictor(image_size, device, model_path)
    result_list = predictor.predict(image_np, show=show)
    return result_list


if __name__ == '__main__':
    p = r'C:\Users\Administrator\Desktop\test_b_table\real2.png'
    paths = glob(r'C:\Users\Administrator\Desktop\test_b_table\error10.png')
    for p in paths:
        img = cv2.imread(p)
        detect(img, show=True)