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,