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https://gitcode.com/gh_mirrors/eas/EasyFace.git
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88 lines
3.0 KiB
Python
88 lines
3.0 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import shutil
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import subprocess
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import sys
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import tempfile
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import unittest
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from modelscope.hub.utils.utils import get_cache_dir
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from modelscope.metainfo import Trainers
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from modelscope.msdatasets import MsDataset
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from modelscope.trainers import build_trainer
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from modelscope.utils.constant import DownloadMode
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from modelscope.utils.test_utils import test_level
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class TestImageDefrcnFewShotTrainer(unittest.TestCase):
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def setUp(self):
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print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
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cmd = [
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sys.executable, '-m', 'pip', 'install', 'detectron2==0.3', '-f',
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'https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html'
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]
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subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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self.tmp_dir = tempfile.TemporaryDirectory().name
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if not os.path.exists(self.tmp_dir):
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os.makedirs(self.tmp_dir)
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self.model_id = 'damo/cv_resnet101_detection_fewshot-defrcn'
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data_voc = MsDataset.load(
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dataset_name='VOC_fewshot',
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namespace='shimin2023',
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split='train',
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download_mode=DownloadMode.REUSE_DATASET_IF_EXISTS)
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self.data_dir = os.path.join(
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data_voc.config_kwargs['split_config']['train'], 'data')
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def tearDown(self):
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shutil.rmtree(self.tmp_dir)
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super().tearDown()
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_trainer(self):
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split = 1
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def base_cfg_modify_fn(cfg):
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cfg.train.work_dir = self.tmp_dir
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cfg.model.roi_heads.backward_scale = 0.75
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cfg.model.roi_heads.num_classes = 15
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cfg.model.roi_heads.freeze_feat = False
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cfg.model.roi_heads.cls_dropout = False
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cfg.model.weights = os.path.join(
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get_cache_dir(), self.model_id,
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'ImageNetPretrained/MSRA/R-101.pkl')
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cfg.datasets.root = self.data_dir
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cfg.datasets.type = 'pascal_voc'
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cfg.datasets.train = [
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'voc_2007_trainval_base{}'.format(split),
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'voc_2012_trainval_base{}'.format(split)
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]
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cfg.datasets.test = ['voc_2007_test_base{}'.format(split)]
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cfg.input.min_size_test = 50
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cfg.train.dataloader.ims_per_batch = 4
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cfg.train.max_iter = 300
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cfg.train.optimizer.lr = 0.001
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cfg.train.lr_scheduler.warmup_iters = 100
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cfg.test.pcb_enable = False
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return cfg
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kwargs = dict(model=self.model_id, cfg_modify_fn=base_cfg_modify_fn)
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trainer = build_trainer(name=Trainers.image_fewshot_detection,
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default_args=kwargs)
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trainer.train()
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results_files = os.listdir(self.tmp_dir)
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self.assertIn('metrics.json', results_files)
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self.assertIn('model_final.pth', results_files)
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if __name__ == '__main__':
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unittest.main()
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