# Copyright (c) OpenMMLab. All rights reserved.
import copy
from os.path import dirname, exists, join

import numpy as np
from mmengine.config import Config


def _get_config_directory():
    """Find the predefined detector config directory."""
    try:
        # Assume we are running in the source mmyolo repo
        repo_dpath = dirname(dirname(dirname(__file__)))
    except NameError:
        # For IPython development when this __file__ is not defined
        import mmyolo
        repo_dpath = dirname(dirname(mmyolo.__file__))
    config_dpath = join(repo_dpath, 'configs')
    if not exists(config_dpath):
        raise Exception('Cannot find config path')
    return config_dpath


def _get_config_module(fname):
    """Load a configuration as a python module."""
    config_dpath = _get_config_directory()
    config_fpath = join(config_dpath, fname)
    config_mod = Config.fromfile(config_fpath)
    return config_mod


def get_detector_cfg(fname):
    """Grab configs necessary to create a detector.

    These are deep copied to allow for safe modification of parameters without
    influencing other tests.
    """
    config = _get_config_module(fname)
    model = copy.deepcopy(config.model)
    return model


def _rand_bboxes(rng, num_boxes, w, h):
    """Randomly generate a specified number of bboxes."""
    cx, cy, bw, bh = rng.rand(num_boxes, 4).T

    tl_x = ((cx * w) - (w * bw / 2)).clip(0, w)
    tl_y = ((cy * h) - (h * bh / 2)).clip(0, h)
    br_x = ((cx * w) + (w * bw / 2)).clip(0, w)
    br_y = ((cy * h) + (h * bh / 2)).clip(0, h)

    bboxes = np.vstack([tl_x, tl_y, br_x, br_y]).T
    return bboxes