def create_image_classification_test_case(**kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..',
'expected_outputs')
TrainTestCase = create_test_case('image_classification',
**kwargs,
metric_keys=['accuracy'],
expected_outputs_dir=expected_outputs_dir,
batch_size=2)
class ClassificationTrainTestCase(TrainTestCase):
def do_finetuning(self, on_gpu):
self.total_epochs = 5
log_file = os.path.join(self.output_folder, 'test_finetuning.log')
initial_command = 'export CUDA_VISIBLE_DEVICES=;' if not on_gpu else ''
run_through_shell(
f'{initial_command}'
f'cd {self.template_folder};'
f'python3 train.py'
f' --train-ann-files {self.ann_file}'
f' --train-data-roots {os.path.join(self.img_root, "train")}'
f' --val-ann-files {self.ann_file}'
f' --val-data-roots {os.path.join(self.img_root, "val")}'
f' --load-weights snapshot.pth'
f' --save-checkpoints-to {self.output_folder}'
f' --gpu-num 1'
f' --batch-size {self.batch_size}'
f' --epochs {self.total_epochs}'
f' | tee {log_file}')
self.assertTrue(
os.path.exists(os.path.join(self.output_folder, 'latest.pth')))
return ClassificationTrainTestCase
def create_object_detection_test_case(**kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..',
'expected_outputs')
return create_test_case('object_detection',
**kwargs,
metric_keys=['bbox'],
expected_outputs_dir=expected_outputs_dir)
def create_image_classification_test_case(**kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..',
'expected_outputs')
return create_test_case('image_classification',
**kwargs,
metric_keys=['accuracy'],
expected_outputs_dir=expected_outputs_dir)
def create_text_spotting_test_case(**kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..', 'expected_outputs')
TestCase = create_test_case('text_spotting',
**kwargs,
metric_keys=['f1', 'word_spotting'],
expected_outputs_dir=expected_outputs_dir)
return TestCase
def create_action_recognition_test_case(enable_metrics_eval=True, **kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..',
'expected_outputs')
TrainTestCase = create_test_case('action_recognition',
**kwargs,
metric_keys=['accuracy'],
expected_outputs_dir=expected_outputs_dir,
batch_size=2)
class ActionRecognitionTrainTestCase(TrainTestCase):
def do_finetuning(self, on_gpu):
self.total_epochs = 5
log_file = os.path.join(self.output_folder, 'test_finetuning.log')
initial_command = 'export CUDA_VISIBLE_DEVICES=;' if not on_gpu else ''
run_through_shell(f'{initial_command}'
f'cd {self.template_folder};'
f'python3 train.py'
f' --train-ann-files {self.ann_file}'
f' --train-data-roots {self.img_root}'
f' --val-ann-files {self.ann_file}'
f' --val-data-roots {self.img_root}'
f' --load-weights snapshot.pth'
f' --save-checkpoints-to {self.output_folder}'
f' --gpu-num 1'
f' --batch-size {self.batch_size}'
f' --epochs {self.total_epochs}'
f' | tee {log_file}')
self.assertTrue(
os.path.exists(os.path.join(self.output_folder, 'latest.pth')))
if enable_metrics_eval:
return ActionRecognitionTrainTestCase
class CustomActionRecognitionTrainTestCase(ActionRecognitionTrainTestCase):
def do_evaluation(self, on_gpu):
initial_command = 'export CUDA_VISIBLE_DEVICES=;' if not on_gpu else ''
metrics_path = os.path.join(self.output_folder, "metrics.yaml")
run_through_shell(f'{initial_command}'
f'cd {self.template_folder};'
f'python3 eval.py'
f' --test-ann-files {self.ann_file}'
f' --test-data-roots {self.img_root}'
f' --save-metrics-to {metrics_path}'
f' --load-weights snapshot.pth')
self.assertTrue(os.path.exists(metrics_path))
return CustomActionRecognitionTrainTestCase
def create_instance_segmentation_test_case(**kwargs):
expected_outputs_dir = os.path.join(os.path.dirname(__file__), '..', 'expected_outputs')
TestCase = create_test_case('instance_segmentation_2',
**kwargs,
metric_keys=['bbox', 'segm'],
expected_outputs_dir=expected_outputs_dir)
class InstanceSegmenationTestCase(TestCase):
@classmethod
def setUpClass(cls):
super().setUpClass()
coco_dir = os.path.abspath(f'{os.path.dirname(__file__)}/../../../../data/coco')
download_and_extract_coco_val2017(coco_dir)
return InstanceSegmenationTestCase