def register(self, cfg):
super().register(cfg)
self.original_cfg = cfg.clone()
inject_coco_datasets(cfg)
register_dynamic_datasets(cfg)
update_cfg_if_using_adhoc_dataset(cfg)
patch_d2_meta_arch()
def setUp(self):
# Add APIs to D2's meta arch, this is usually called in runner's setup,
# however in unittest it needs to be called sperarately.
# TODO: maybe we should apply this by default
patch_d2_meta_arch()
self.setup_test_dir()
assert hasattr(self, "test_dir")
self.setup_custom_test()
assert hasattr(self, "runner")
assert hasattr(self, "cfg")
self.force_apply_overwrite_opts()
self.test_model = self.runner.build_model(self.cfg, eval_only=True)
def register(self, cfg: CfgNode):
inject_coco_datasets(cfg)
register_dynamic_datasets(cfg)
update_cfg_if_using_adhoc_dataset(cfg)
patch_d2_meta_arch()
import os
import unittest
from PIL import Image
import torch
from d2go.export.api import convert_and_export_predictor
from d2go.export.d2_meta_arch import patch_d2_meta_arch
from d2go.runner import create_runner, GeneralizedRCNNRunner
from d2go.model_zoo import model_zoo
from mobile_cv.common.misc.file_utils import make_temp_directory
#from d2go.tests.data_loader_helper import LocalImageGenerator, register_toy_dataset
from d2go.utils.testing.data_loader_helper import LocalImageGenerator
from d2go.utils.testing.data_loader_helper import _register_toy_dataset as register_toy_dataset
patch_d2_meta_arch()
@contextlib.contextmanager
def create_fake_detection_data_loader(height, width, is_train):
with make_temp_directory("detectron2go_tmp_dataset") as dataset_dir:
runner = create_runner("d2go.runner.GeneralizedRCNNRunner")
cfg = runner.get_default_cfg()
cfg.DATASETS.TRAIN = ["default_dataset_train"]
cfg.DATASETS.TEST = ["default_dataset_test"]
with make_temp_directory("detectron2go_tmp_dataset") as dataset_dir:
image_dir = os.path.join(dataset_dir, "images")
os.makedirs(image_dir)
image_generator = LocalImageGenerator(image_dir,
width=width,
