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# 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