Move lmnet/lmnet/utils utils to blueoil/utils

blueoil/cmd/build_tfds.py

@@ -21,9 +21,9 @@
 
 from blueoil.datasets.base import ObjectDetectionBase, SegmentationBase
 from blueoil.datasets.tfds import TFDSMixin
-from lmnet.utils import config as config_util
-from lmnet.utils.tfds_builders.classification import ClassificationBuilder
-from lmnet.utils.tfds_builders.object_detection import ObjectDetectionBuilder
+from blueoil.utils import config as config_util
+from blueoil.utils.tfds_builders.classification import ClassificationBuilder
+from blueoil.utils.tfds_builders.object_detection import ObjectDetectionBuilder
 
 
 def _get_tfds_settings(config_file):

blueoil/cmd/convert_weight_from_darknet.py

@@ -23,8 +23,8 @@
 from lmnet import environment
 from blueoil.networks.classification.darknet import Darknet
 from blueoil.networks.object_detection.yolo_v2 import YoloV2
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
 
 
 def convert(config, weight_file):

blueoil/cmd/evaluate.py

@@ -25,9 +25,9 @@
 from blueoil.datasets.base import ObjectDetectionBase
 from blueoil.datasets.dataset_iterator import DatasetIterator
 from blueoil.datasets.tfds import TFDSClassification, TFDSObjectDetection
-from lmnet.utils import config as config_util
-from lmnet.utils import executor, module_loader
-from lmnet.utils.predict_output.writer import save_json
+from blueoil.utils import config as config_util
+from blueoil.utils import executor, module_loader
+from blueoil.utils.predict_output.writer import save_json
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)

blueoil/cmd/export.py

@@ -22,9 +22,9 @@
 import tensorflow as tf
 
 from lmnet import environment
-from lmnet.utils.image import load_image
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
+from blueoil.utils.image import load_image
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
 
 DEFAULT_INFERENCE_TEST_DATA_IMAGE = os.path.join(
     os.path.dirname(os.path.realpath(__file__)),

blueoil/cmd/measure_latency.py

@@ -23,9 +23,9 @@
 from tensorflow.python.client import device_lib
 
 from lmnet import environment
-from lmnet.utils.image import load_image
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
+from blueoil.utils.image import load_image
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
 
 
 # TODO(wakisaka): duplicated function with blueoil/cmd/export.py

blueoil/cmd/profile_model.py

@@ -22,8 +22,8 @@
 import tensorflow as tf
 
 from lmnet import environment
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)

blueoil/cmd/train.py

@@ -21,7 +21,7 @@
 
 from blueoil.generate_lmnet_config import generate
 from executor.train import run as run_train
-from lmnet.utils import horovod as horovod_util
+from blueoil.utils import horovod as horovod_util
 
 
 def run(blueoil_config_file, experiment_id):

blueoil/cmd/tune_ray.py

@@ -26,8 +26,8 @@
 from blueoil.datasets.base import ObjectDetectionBase
 from blueoil.datasets.dataset_iterator import DatasetIterator
 from blueoil.datasets.tfds import TFDSClassification, TFDSObjectDetection
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
 from ray.tune import Trainable, register_trainable, run_experiments
 from ray.tune.schedulers import AsyncHyperBandScheduler
 from ray.tune.suggest import HyperOptSearch

blueoil/datasets/bdd100k.py

@@ -7,7 +7,7 @@
 import numpy as np
 
 from blueoil.datasets.base import ObjectDetectionBase, SegmentationBase
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 
 
 class BDD100KObjectDetection(ObjectDetectionBase):

blueoil/datasets/camvid.py

@@ -22,7 +22,7 @@
 
 from lmnet.common import get_color_map
 from blueoil.datasets.base import SegmentationBase, StoragePathCustomizable
-from lmnet.utils.random import shuffle, train_test_split
+from blueoil.utils.random import shuffle, train_test_split
 
 
 def get_image(filename, convert_rgb=True, ignore_class_idx=None):

blueoil/datasets/cifar10.py

@@ -21,7 +21,7 @@
 
 from lmnet import data_processor
 from blueoil.datasets.base import Base
-from lmnet.utils.random import shuffle
+from blueoil.utils.random import shuffle
 
 
 class Cifar10(Base):

blueoil/datasets/cifar100.py

@@ -21,7 +21,7 @@
 
 from lmnet import data_processor
 from blueoil.datasets.base import Base
-from lmnet.utils.random import shuffle
+from blueoil.utils.random import shuffle
 
 
 class Cifar100(Base):

blueoil/datasets/delta_mark.py

@@ -22,8 +22,8 @@
 
 from lmnet import data_processor
 from blueoil.datasets.base import Base, ObjectDetectionBase, StoragePathCustomizable
-from lmnet.utils.image import load_image
-from lmnet.utils.random import shuffle, train_test_split
+from blueoil.utils.image import load_image
+from blueoil.utils.random import shuffle, train_test_split
 
 
 @functools.lru_cache(maxsize=None)

blueoil/datasets/div2k.py

@@ -18,7 +18,7 @@
 from glob import glob
 
 from blueoil.datasets.base import Base
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 
 
 class Div2k(Base):

blueoil/datasets/ilsvrc_2012.py

@@ -21,7 +21,7 @@
 import pandas as pd
 
 from lmnet import data_processor
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import Base
 
 

blueoil/datasets/image_folder.py

@@ -22,9 +22,9 @@
 import numpy as np
 
 from lmnet import data_processor
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import Base, StoragePathCustomizable
-from lmnet.utils.random import train_test_split
+from blueoil.utils.random import train_test_split
 
 
 class ImageFolderBase(StoragePathCustomizable, Base):

blueoil/datasets/mscoco.py

@@ -19,7 +19,7 @@
 import numpy as np
 from pycocotools.coco import COCO
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import ObjectDetectionBase, SegmentationBase
 
 DEFAULT_CLASSES = [

blueoil/datasets/mscoco_2017.py

@@ -18,7 +18,7 @@
 import numpy as np
 from pycocotools.coco import COCO
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import KeypointDetectionBase
 
 

blueoil/datasets/open_images_v4.py

@@ -25,8 +25,8 @@
 
 from lmnet import data_processor
 from blueoil.datasets.base import Base, ObjectDetectionBase, StoragePathCustomizable
-from lmnet.utils.image import load_image
-from lmnet.utils.random import train_test_split
+from blueoil.utils.image import load_image
+from blueoil.utils.random import train_test_split
 
 
 class OpenImagesV4(Base):

blueoil/datasets/pascalvoc_2007_2012.py

@@ -17,7 +17,7 @@
 
 import numpy as np
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import ObjectDetectionBase
 from blueoil.datasets.pascalvoc_2007 import Pascalvoc2007
 from blueoil.datasets.pascalvoc_2012 import Pascalvoc2012

blueoil/datasets/pascalvoc_base.py

@@ -21,7 +21,7 @@
 import numpy as np
 import pandas as pd
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import ObjectDetectionBase
 
 

blueoil/datasets/tfds.py

@@ -20,8 +20,8 @@
 import tensorflow_datasets as tfds
 
 from blueoil.datasets.base import Base, ObjectDetectionBase
-from lmnet.utils.tfds_builders.classification import ClassificationBuilder
-from lmnet.utils.tfds_builders.object_detection import ObjectDetectionBuilder
+from blueoil.utils.tfds_builders.classification import ClassificationBuilder
+from blueoil.utils.tfds_builders.object_detection import ObjectDetectionBuilder
 
 
 def _grayscale_to_rgb(record):

blueoil/datasets/widerface.py

@@ -18,7 +18,7 @@
 
 import numpy as np
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import ObjectDetectionBase
 
 

blueoil/datasets/ytfaces.py

@@ -17,7 +17,7 @@
 
 import numpy as np
 
-from lmnet.utils.image import load_image
+from blueoil.utils.image import load_image
 from blueoil.datasets.base import KeypointDetectionBase
 
 

blueoil/generate_lmnet_config.py

@@ -23,7 +23,7 @@
 from jinja2 import Environment, FileSystemLoader
 from tensorflow.io import gfile
 
-from lmnet.utils.module_loader import load_class
+from blueoil.utils.module_loader import load_class
 
 
 _TASK_TYPE_TEMPLATE_FILE = {

lmnet/lmnet/utils/predict_output/writer.py → blueoil/utils/predict_output/writer.py

@@ -3,8 +3,8 @@
 
 import numpy as np
 
-from lmnet.utils.predict_output.output import ImageFromJson
-from lmnet.utils.predict_output.output import JsonOutput
+from blueoil.utils.predict_output.output import ImageFromJson
+from blueoil.utils.predict_output.output import JsonOutput
 
 logger = logging.getLogger(__name__)
 

lmnet/executor/predict.py

@@ -23,10 +23,10 @@
 import tensorflow as tf
 
 from lmnet import environment
-from lmnet.utils.image import load_image
-from lmnet.utils import config as config_util
-from lmnet.utils.executor import search_restore_filename
-from lmnet.utils.predict_output.writer import OutputWriter
+from blueoil.utils.image import load_image
+from blueoil.utils import config as config_util
+from blueoil.utils.executor import search_restore_filename
+from blueoil.utils.predict_output.writer import OutputWriter
 
 DUMMY_FILENAME = "DUMMY_FILE"
 

lmnet/executor/train.py

@@ -26,10 +26,10 @@
 from blueoil.datasets.base import ObjectDetectionBase
 from blueoil.datasets.dataset_iterator import DatasetIterator
 from blueoil.datasets.tfds import TFDSClassification, TFDSObjectDetection
-from lmnet.utils import config as config_util
-from lmnet.utils import executor
-from lmnet.utils import horovod as horovod_util
-from lmnet.utils import module_loader
+from blueoil.utils import config as config_util
+from blueoil.utils import executor
+from blueoil.utils import horovod as horovod_util
+from blueoil.utils import module_loader
 
 
 def _save_checkpoint(saver, sess, global_step, step):

lmnet/lmnet/data_augmentor.py

@@ -22,7 +22,7 @@
 from PIL import Image, ImageEnhance, ImageFilter
 
 from lmnet import data_processor, pre_processor
-from lmnet.utils.box import fill_dummy_boxes, crop_boxes, iou
+from blueoil.utils.box import fill_dummy_boxes, crop_boxes, iou
 
 
 class Blur(data_processor.Processor):

lmnet/lmnet/post_processor.py

@@ -19,7 +19,7 @@
 
 from lmnet.data_augmentor import iou
 from lmnet.data_processor import Processor
-from lmnet.utils.box import format_cxcywh_to_xywh
+from blueoil.utils.box import format_cxcywh_to_xywh
 
 
 def _softmax(x):

lmnet/tests/executor_tests/test_build_tfds.py

@@ -21,7 +21,7 @@
 from lmnet import environment
 from blueoil.datasets.dataset_iterator import DatasetIterator
 from blueoil.datasets.tfds import TFDSClassification, TFDSObjectDetection
-from lmnet.utils import config as config_util
+from blueoil.utils import config as config_util
 
 _RUN_AS_A_SCRIPT = False
 

lmnet/tests/lmnet_tests/networks_tests/classification_test/test_darknet.py

@@ -23,7 +23,7 @@
 from blueoil.networks.classification.darknet import Darknet
 from blueoil.datasets.image_folder import ImageFolderBase
 from lmnet.pre_processor import Resize
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/classification_test/test_lm_resnet_quantize.py

@@ -24,7 +24,7 @@
 from blueoil.datasets.image_folder import ImageFolderBase
 from lmnet.pre_processor import Resize
 from blueoil.nn.quantizations import binary_mean_scaling_quantizer, linear_mid_tread_half_quantizer
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/classification_test/test_lmnet_quantize.py

@@ -24,7 +24,7 @@
 from blueoil.datasets.image_folder import ImageFolderBase
 from lmnet.pre_processor import Resize
 from blueoil.nn.quantizations import binary_mean_scaling_quantizer, linear_mid_tread_half_quantizer
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/keypoint_detection_tests/test_lm_single_pose_v1.py

@@ -21,7 +21,7 @@
 from lmnet.common import Tasks
 from blueoil.networks.keypoint_detection.lm_single_pose_v1 import LmSinglePoseV1Quantize
 from blueoil.datasets.mscoco_2017 import MscocoSinglePersonKeypoints
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 from lmnet.pre_processor import (
     DivideBy255,
     ResizeWithJoints,

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v1.py

@@ -24,7 +24,7 @@
 from blueoil.networks.object_detection.yolo_v1 import YoloV1
 from blueoil.datasets.pascalvoc_2007 import Pascalvoc2007
 from lmnet.pre_processor import ResizeWithGtBoxes
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v2.py

@@ -26,7 +26,7 @@
 from blueoil.datasets.pascalvoc_2007 import Pascalvoc2007
 from lmnet.post_processor import NMS, ExcludeLowScoreBox, FormatYoloV2
 from lmnet.pre_processor import ResizeWithGtBoxes
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/object_detection_tests/test_yolo_v2_quantize.py

@@ -24,7 +24,7 @@
 from blueoil.datasets.pascalvoc_2007 import Pascalvoc2007
 from lmnet.pre_processor import ResizeWithGtBoxes
 from blueoil.nn.quantizations import binary_channel_wise_mean_scaling_quantizer, linear_mid_tread_half_quantizer
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() in conftest.py to all tests in this file.
 # Set test environment

lmnet/tests/lmnet_tests/networks_tests/segmentation_tests/test_lm_bisenet.py

@@ -26,7 +26,7 @@
 from blueoil.datasets.camvid import Camvid
 from lmnet.post_processor import Bilinear, Softmax
 from lmnet.pre_processor import Resize
-from lmnet.utils.executor import prepare_dirs
+from blueoil.utils.executor import prepare_dirs
 
 # Apply reset_default_graph() and set_test_environment() in conftest.py to all tests in this file.
 pytestmark = pytest.mark.usefixtures("reset_default_graph", "set_test_environment")