Fix accumulated step error in det_rearrange_forward

        _psize = _h = patch_lst[0].shape[-1]

        _step = int(ph_step * _psize / patch_size)

        _pw = int(_psize / pw_num)

        if ph_num > 1:

            _h += (ph_num - 1) * _step

        _h = int(_pw / w * h)

        tgtmap = np.zeros((channel, _h, _pw), dtype=np.float32)

        num_patches = len(patch_lst) * pw_num - pad_num

        for ii, p in enumerate(patch_lst):

                p = einops.rearrange(p, 'c h w -> c w h')

            for jj in range(pw_num):

                pidx = ii * pw_num + jj

                t = pidx * _step

                rel_t = rel_step_list[pidx]

                t = int(round(rel_t * _h))

                b = t + _psize

                l = jj * _pw

                r = l + _pw

            pad_size = pad_h

            batches[-1].append(p)

            if verbose:

                cv2.imwrite(f'result/rearrange_{ii}.jpg', p[..., ::-1])

                cv2.imwrite(f'result/rearrange_{ii}.png', p[..., ::-1])

        return batches, down_scale_ratio, pad_size

    h, w = img.shape[:2]

        if verbose:

            print(f'Input image will be rearranged to square batches before fed into network.\

                \n Rearranged batches will be saved to result/rearrange_%d.jpg')

                \n Rearranged batches will be saved to result/rearrange_%d.png')

        if transpose:

            img = einops.rearrange(img, 'h w c -> w h c')

        ph_num = int(np.ceil(h / ph))

        ph_step = int((h - ph) / (ph_num - 1)) if ph_num > 1 else 0

        rel_ph_step = ph_step / h

        rel_step_list = []

        patch_list = []

        for ii in range(ph_num):

            patch_list.append(img[ii * ph_step: ii * ph_step + ph])

            t = ii * ph_step

            b = t + ph

            rel_step_list.append(t / h)

            patch_list.append(img[t: b])

        p_num = int(np.ceil(ph_num / pw_num))

        pad_num = p_num * pw_num - ph_num