test.py

# import numpy as np
# from multiprocessing import Pool, cpu_count

# # 矩阵加法函数
# def matrix_add_subsection(a, b, start, end):
#     return np.add(a[start:end], b[start:end])

# # 将矩阵划分为多个子部分并分配给不同的进程
# def parallel_matrix_add(a, b):
#     num_processes = cpu_count()  # 获取CPU核心数

#     print(num_processes)
#     # exit(0)
#     rows = a.shape[0]
#     step = rows // num_processes

#     # 创建进程池
#     pool = Pool(processes=num_processes)

#     # 分配任务
#     results = [pool.apply_async(matrix_add_subsection, args=(a, b, i, i + step)) for i in range(0, rows, step)]

#     # 收集结果
#     results = [p.get() for p in results]

#     breakpoint()

#     # 合并结果
#     result_matrix = np.concatenate(results, axis=0)

#     # 关闭进程池
#     pool.close()
#     pool.join()

#     return result_matrix

# # 创建两个矩阵
# a = np.random.rand(1000, 1000)
# b = np.random.rand(1000, 1000)

# # 使用多进程进行矩阵加法
# result = parallel_matrix_add(a, b)

# # 输出结果的一部分以验证
# print(result[:5, :5])


import numpy as np



    print(bbox)
    print(label)
    breakpoint()
    print()





print(layout_np.shape)
breakpoint()
print()