Packaged application

efficientdet/aug/autoaugment.py

@@ -23,7 +23,7 @@
 import tensorflow.compat.v1 as tf
 from tensorflow_addons import image as image_ops
 
-import hparams_config
+from .. import hparams_config
 
 # This signifies the max integer that the controller RNN could predict for the
 # augmentation scheme.

efficientdet/aug/autoaugment_test.py

@@ -16,7 +16,7 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-from aug import autoaugment
+from . import autoaugment
 
 
 class AutoaugmentTest(tf.test.TestCase):

efficientdet/aug/gridmask_test.py

@@ -16,7 +16,7 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-from aug import gridmask
+from . import gridmask
 
 
 class GridMaskTest(tf.test.TestCase):

efficientdet/aug/mosaic_test.py

@@ -16,7 +16,7 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-from aug import mosaic
+from . import mosaic
 
 
 class MosaicTest(tf.test.TestCase):

efficientdet/backbone/backbone_factory.py

@@ -17,9 +17,9 @@
 from absl import logging
 import tensorflow as tf
 
-from backbone import efficientnet_builder
-from backbone import efficientnet_lite_builder
-from backbone import efficientnet_model
+from . import efficientnet_builder
+from . import efficientnet_lite_builder
+from . import efficientnet_model
 
 
 def get_model_builder(model_name):

efficientdet/backbone/efficientnet_builder.py

@@ -24,8 +24,8 @@
 import numpy as np
 import tensorflow as tf
 
-import utils
-from backbone import efficientnet_model
+from .. import utils
+from . import efficientnet_model
 
 
 def efficientnet_params(model_name):

efficientdet/backbone/efficientnet_builder_test.py

@@ -17,7 +17,7 @@
 import numpy as np
 import tensorflow.compat.v1 as tf
 
-from backbone import efficientnet_builder
+from . import efficientnet_builder
 
 
 class EfficientnetBuilderTest(tf.test.TestCase):

efficientdet/backbone/efficientnet_lite_builder.py

@@ -21,9 +21,9 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-import utils
-from backbone import efficientnet_builder
-from backbone import efficientnet_model
+from .. import utils
+from . import efficientnet_builder
+from . import efficientnet_model
 
 # Edge models use inception-style MEAN and STDDEV for better post-quantization.
 MEAN_RGB = [127.0, 127.0, 127.0]

efficientdet/backbone/efficientnet_lite_builder_test.py

@@ -17,7 +17,7 @@
 import numpy as np
 import tensorflow.compat.v1 as tf
 
-from backbone import efficientnet_lite_builder
+from . import efficientnet_lite_builder
 
 
 class EfficientnetBuilderTest(tf.test.TestCase):

efficientdet/backbone/efficientnet_model.py

@@ -29,7 +29,7 @@
 from six.moves import xrange
 import tensorflow as tf
 
-import utils
+from .. import utils
 
 GlobalParams = collections.namedtuple('GlobalParams', [
     'batch_norm_momentum', 'batch_norm_epsilon', 'dropout_rate', 'data_format',

efficientdet/backbone/efficientnet_model_test.py

@@ -16,8 +16,8 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-import utils
-from backbone import efficientnet_model
+from .. import utils
+from . import efficientnet_model
 
 
 class ModelTest(tf.test.TestCase):

efficientdet/coco_metric.py

@@ -25,7 +25,7 @@
 from pycocotools.cocoeval import COCOeval
 import tensorflow as tf
 
-from keras import label_util
+from .keras import label_util
 
 
 class EvaluationMetric():

efficientdet/coco_metric_test.py

@@ -16,7 +16,7 @@
 
 from absl import logging
 import tensorflow.compat.v1 as tf
-import coco_metric
+from . import coco_metric
 
 
 class CocoMetricTest(tf.test.TestCase):

efficientdet/dataloader.py

@@ -16,10 +16,10 @@
 from absl import logging
 import tensorflow as tf
 
-import utils
-from keras import anchors
-from object_detection import preprocessor
-from object_detection import tf_example_decoder
+from . import utils
+from .keras import anchors
+from .object_detection import preprocessor
+from .object_detection import tf_example_decoder
 
 
 class InputProcessor:

efficientdet/dataloader_test.py

@@ -17,11 +17,11 @@
 import tempfile
 import tensorflow as tf
 
-import dataloader
-import hparams_config
-from dataset import tfrecord_util
-from keras import anchors
-from object_detection import tf_example_decoder
+from . import dataloader
+from . import hparams_config
+from .dataset import tfrecord_util
+from .keras import anchors
+from .object_detection import tf_example_decoder
 
 
 class DataloaderTest(tf.test.TestCase):

efficientdet/dataset/create_coco_tfrecord.py

@@ -39,8 +39,8 @@
 
 from pycocotools import mask
 import tensorflow as tf
-from dataset import label_map_util
-from dataset import tfrecord_util
+from . import label_map_util
+from . import tfrecord_util
 
 flags.DEFINE_boolean(
     'include_masks', False, 'Whether to include instance segmentations masks '
@@ -359,5 +359,8 @@ def main(_):
                                           FLAGS.include_masks)
 
 
-if __name__ == '__main__':
+def launcher():
   app.run(main)
+
+if __name__ == '__main__':
+  launcher()

efficientdet/dataset/create_coco_tfrecord_test.py

@@ -25,7 +25,7 @@
 import six
 import tensorflow as tf
 
-from dataset import create_coco_tfrecord
+from . import create_coco_tfrecord
 
 
 class CreateCocoTFRecordTest(tf.test.TestCase):

efficientdet/dataset/create_pascal_tfrecord.py

@@ -31,7 +31,7 @@
 import PIL.Image
 import tensorflow as tf
 
-from dataset import tfrecord_util
+from . import tfrecord_util
 
 flags.DEFINE_string('data_dir', '', 'Root directory to raw PASCAL VOC dataset.')
 flags.DEFINE_string('set', 'train', 'Convert training set, validation set or '
@@ -315,5 +315,8 @@ def main(_):
     json.dump(ann_json_dict, f)
 
 
-if __name__ == '__main__':
+def launcher():
   app.run(main)
+
+if __name__ == '__main__':
+  launcher()

efficientdet/dataset/create_pascal_tfrecord_test.py

@@ -22,7 +22,7 @@
 import six
 import tensorflow as tf
 
-from dataset import create_pascal_tfrecord
+from . import create_pascal_tfrecord
 
 
 class CreatePascalTFRecordTest(tf.test.TestCase):

efficientdet/dataset/inspect_tfrecords.py

@@ -23,10 +23,10 @@
 from PIL import Image
 
 sys.path.append('./')
-import dataloader
-import hparams_config
-import utils
-from visualize import vis_utils
+from .. import dataloader
+from .. import hparams_config
+from .. import utils
+from ..visualize import vis_utils
 
 flags.DEFINE_string('save_samples_dir', 'tfrecord_samples',
                     'Location of samples to save')
@@ -134,5 +134,8 @@ def main(_):
     )
 
 
-if __name__ == '__main__':
+def launcher():
   app.run(main)
+
+if __name__ == '__main__':
+  launcher()

efficientdet/det_model_fn.py

@@ -18,14 +18,14 @@
 from absl import logging
 import numpy as np
 import tensorflow.compat.v1 as tf
-import coco_metric
-import efficientdet_arch
-import hparams_config
-import nms_np
-import utils
-from keras import anchors
-from keras import efficientdet_keras
-from keras import postprocess
+from . import coco_metric
+from . import efficientdet_arch
+from . import hparams_config
+from . import nms_np
+from . import utils
+from .keras import anchors
+from .keras import efficientdet_keras
+from .keras import postprocess
 
 _DEFAULT_BATCH_SIZE = 64
 

efficientdet/det_model_fn_test.py

@@ -14,7 +14,7 @@
 # ==============================================================================
 """Tests for det_model_fn."""
 import tensorflow as tf
-import det_model_fn
+from . import det_model_fn
 
 
 def legacy_focal_loss(logits, targets, alpha, gamma, normalizer, _=0):

efficientdet/efficientdet_arch.py

@@ -25,11 +25,11 @@
 import numpy as np
 import tensorflow.compat.v1 as tf
 
-import hparams_config
-import utils
-from backbone import backbone_factory
-from backbone import efficientnet_builder
-from keras import fpn_configs
+from . import hparams_config
+from . import utils
+from .backbone import backbone_factory
+from .backbone import efficientnet_builder
+from .keras import fpn_configs
 
 
 ################################################################################

efficientdet/efficientdet_arch_test.py

@@ -16,9 +16,9 @@
 from absl import logging
 import tensorflow.compat.v1 as tf
 
-import efficientdet_arch
-import hparams_config
-import utils
+from . import efficientdet_arch
+from . import hparams_config
+from . import utils
 
 
 class EfficientDetArchTest(tf.test.TestCase):

efficientdet/hparams_config_test.py

@@ -19,7 +19,7 @@
 import tensorflow.compat.v1 as tf
 import yaml
 
-import hparams_config
+from . import hparams_config
 
 
 class HparamsConfigTest(tf.test.TestCase):

efficientdet/inference.py

@@ -23,14 +23,14 @@
 from PIL import Image
 import tensorflow.compat.v1 as tf
 
-import dataloader
-import det_model_fn
-import hparams_config
-import utils
-from keras import efficientdet_keras
-from keras import label_util
-from keras import postprocess
-from visualize import vis_utils
+from . import dataloader
+from . import det_model_fn
+from . import hparams_config
+from . import utils
+from .keras import efficientdet_keras
+from .keras import label_util
+from .keras import postprocess
+from .visualize import vis_utils
 from tensorflow.python.client import timeline  # pylint: disable=g-direct-tensorflow-import
 
 

efficientdet/iou_utils_test.py

@@ -15,7 +15,7 @@
 """Tests for iou_utils."""
 from absl import logging
 import tensorflow as tf
-import iou_utils
+from . import iou_utils
 
 
 class IouUtilsTest(tf.test.TestCase):

efficientdet/keras/anchors.py

@@ -17,12 +17,12 @@
 import numpy as np
 import tensorflow as tf
 
-import utils
-from object_detection import argmax_matcher
-from object_detection import box_list
-from object_detection import faster_rcnn_box_coder
-from object_detection import region_similarity_calculator
-from object_detection import target_assigner
+from .. import utils
+from ..object_detection import argmax_matcher
+from ..object_detection import box_list
+from ..object_detection import faster_rcnn_box_coder
+from ..object_detection import region_similarity_calculator
+from ..object_detection import target_assigner
 
 MAX_DETECTION_POINTS = 5000
 

efficientdet/keras/efficientdet_keras.py

@@ -18,15 +18,15 @@
 import numpy as np
 import tensorflow as tf
 
-import dataloader
-import hparams_config
-import utils
-from backbone import backbone_factory
-from backbone import efficientnet_builder
-from keras import fpn_configs
-from keras import postprocess
-from keras import tfmot
-from keras import util_keras
+from .. import dataloader
+from .. import hparams_config
+from .. import utils
+from ..backbone import backbone_factory
+from ..backbone import efficientnet_builder
+from . import fpn_configs
+from . import postprocess
+from . import tfmot
+from . import util_keras
 # pylint: disable=arguments-differ  # fo keras layers.