Fix import structure and bump version

Author: tteepe

Diff for: CenterNet/centernet.py

@@ -4,7 +4,7 @@
 import torch
 import pytorch_lightning as pl
 
-from models import create_model
+from .models import create_model
 
 
 class CenterNet(pl.LightningModule):

Diff for: CenterNet/centernet_detection.py

@@ -13,15 +13,15 @@
 from pycocotools.cocoeval import COCOeval
 from torchvision.datasets import CocoDetection
 
-from centernet import CenterNet
-from models.heads import CenterHead
-from transforms import CategoryIdToClass, ImageAugmentation
-from transforms.sample import ComposeSample
-from transforms.ctdet import CenterDetectionSample
-from decode.ctdet import ctdet_decode
-from utils.losses import RegL1Loss, FocalLoss
-from utils.decode import sigmoid_clamped
-from utils.nms import soft_nms
+from .centernet import CenterNet
+from .models.heads import CenterHead
+from .transforms import CategoryIdToClass, ImageAugmentation
+from .transforms.sample import ComposeSample
+from .transforms.ctdet import CenterDetectionSample
+from .decode.ctdet import ctdet_decode
+from .utils.losses import RegL1Loss, FocalLoss
+from .utils.decode import sigmoid_clamped
+from .utils.nms import soft_nms
 
 
 class CenterNetDetection(CenterNet):

Diff for: CenterNet/centernet_multi_pose.py

@@ -13,16 +13,16 @@
 from torch.utils.data import DataLoader
 from torchvision.datasets import CocoDetection
 
-from centernet import CenterNet
-from models.heads import CenterHead
-from transforms import ImageAugmentation
-from transforms.ctdet import CenterDetectionSample
-from transforms.multi_pose import MultiPoseSample
-from transforms.sample import MultiSampleTransform, PoseFlip, ComposeSample
-from decode.multi_pose import multi_pose_decode
-from utils.decode import sigmoid_clamped
-from utils.losses import RegL1Loss, FocalLoss, RegWeightedL1Loss
-from utils.nms import soft_nms_39
+from .centernet import CenterNet
+from .models.heads import CenterHead
+from .transforms import ImageAugmentation
+from .transforms.ctdet import CenterDetectionSample
+from .transforms.multi_pose import MultiPoseSample
+from .transforms.sample import MultiSampleTransform, PoseFlip, ComposeSample
+from .decode.multi_pose import multi_pose_decode
+from .utils.decode import sigmoid_clamped
+from .utils.losses import RegL1Loss, FocalLoss, RegWeightedL1Loss
+from .utils.nms import soft_nms_39
 
 
 class CenterNetMultiPose(CenterNet):

Diff for: CenterNet/centernet_test.py

@@ -5,11 +5,11 @@
 from torch.utils.data import DataLoader
 from torchvision.datasets import CocoDetection
 
-from centernet import CenterNet
-from centernet_detection import CenterNetDetection
-from centernet_multi_pose import CenterNetMultiPose
-from transforms import ImageAugmentation
-from transforms.sample import ComposeSample
+from .centernet import CenterNet
+from .centernet_detection import CenterNetDetection
+from .centernet_multi_pose import CenterNetMultiPose
+from .transforms import ImageAugmentation
+from .transforms.sample import ComposeSample
 
 task = {
     "detection": (CenterNetDetection, "instances_val2017.json"),

Diff for: CenterNet/decode/ctdet.py

@@ -1,6 +1,6 @@
 import torch
 
-from utils.decode import _nms, _topk, _transpose_and_gather_feat
+from ..utils.decode import _nms, _topk, _transpose_and_gather_feat
 
 
 def ctdet_decode(heat, wh, reg=None, K=100):

Diff for: CenterNet/decode/multi_pose.py

@@ -1,7 +1,7 @@
 import torch
 import numpy as np
 
-from utils.decode import _nms, _topk, _topk_channel, _transpose_and_gather_feat
+from ..utils.decode import _nms, _topk, _topk_channel, _transpose_and_gather_feat
 
 
 def multi_pose_decode(heat, wh, kps, reg=None, hm_hp=None, hp_offset=None, K=100):

Diff for: CenterNet/models/backbones/__init__.py

@@ -5,13 +5,6 @@
 # Licensed under the BSD 3-Clause License
 # ------------------------------------------------------------------------------
 
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-import torch
 import torch.nn as nn
 
 

Diff for: CenterNet/models/backbones/large_hourglass.py

@@ -5,13 +5,6 @@
 # Modified by Xingyi Zhou
 # ------------------------------------------------------------------------------
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import os
-
-import torch
 import torch.nn as nn
 import torch.utils.model_zoo as model_zoo
 

Diff for: CenterNet/models/backbones/msra_resnet.py

@@ -8,7 +8,7 @@
 import torch.nn.functional as F
 import torch.utils.model_zoo as model_zoo
 
-from models.backbones.DCNv2.DCN.dcn_v2 import DCN
+from .DCNv2.DCN.dcn_v2 import DCN
 
 BN_MOMENTUM = 0.1
 logger = logging.getLogger(__name__)

Diff for: CenterNet/models/backbones/pose_dla_dcn.py

@@ -9,9 +9,11 @@
 import logging
 
 import torch.nn as nn
-from models.backbones.DCNv2.DCN.dcn_v2 import DCN
 import torch.utils.model_zoo as model_zoo
 
+from .DCNv2.DCN.dcn_v2 import DCN
+
+
 BN_MOMENTUM = 0.1
 logger = logging.getLogger(__name__)
 

Diff for: CenterNet/models/backbones/resnet_dcn.py

@@ -3,7 +3,7 @@
 import torch
 import numpy as np
 
-from utils.gaussian import draw_umich_gaussian, draw_msra_gaussian, gaussian_radius
+from ..utils.gaussian import draw_umich_gaussian, draw_msra_gaussian, gaussian_radius
 
 
 class CenterDetectionSample:

Diff for: CenterNet/transforms/ctdet.py

@@ -3,7 +3,7 @@
 import torch
 import numpy as np
 
-from utils.gaussian import draw_umich_gaussian, draw_msra_gaussian, gaussian_radius
+from ..utils.gaussian import draw_umich_gaussian, draw_msra_gaussian, gaussian_radius
 
 
 class MultiPoseSample:

Diff for: CenterNet/transforms/multi_pose.py

@@ -8,7 +8,7 @@
 import torch.nn as nn
 import torch.nn.functional as F
 
-from utils.decode import _transpose_and_gather_feat
+from .decode import _transpose_and_gather_feat
 
 
 def _neg_loss(pred, gt):

Diff for: CenterNet/utils/losses.py

@@ -4,7 +4,7 @@
 
 setup(
     name='CenterNet',
-    version='0.0.0',
+    version='0.1.0',
     description='Refactored version of CenterNet (Objects as Points). With PyTorch Lightning and imgaug.',
     author='Torben Teepe',
     author_email='[email protected]',

Diff for: setup.py

@@ -1,6 +1,6 @@
 import torch
-from models import create_model
-from models.heads import CenterHead
+from CenterNet.models import create_model
+from CenterNet.models.heads import CenterHead
 
 
 device = "cuda" if torch.cuda.is_available() else "cpu"

Diff for: tests/test_models.py

@@ -5,10 +5,10 @@
 import imgaug.augmenters as iaa
 import pytest
 
-from decode.ctdet import ctdet_decode
-from transforms import CategoryIdToClass, ImageAugmentation
-from transforms.sample import ComposeSample
-from transforms.ctdet import CenterDetectionSample
+from CenterNet.decode.ctdet import ctdet_decode
+from CenterNet.transforms import CategoryIdToClass, ImageAugmentation
+from CenterNet.transforms.sample import ComposeSample
+from CenterNet.transforms.ctdet import CenterDetectionSample
 
 
 def test_cdet_encoding_decoding():

Diff for: tests/test_sample_encode_decode.py

@@ -4,8 +4,8 @@
 
 from tests.utilities import CocoFakeDataset
 
-from centernet_detection import CenterNetDetection
-from transforms.ctdet import CenterDetectionSample
+from CenterNet.centernet_detection import CenterNetDetection
+from CenterNet.transforms.ctdet import CenterDetectionSample
 
 
 def test_detection():

Diff for: tests/test_train_detection.py

@@ -2,12 +2,12 @@
 import torch
 from torch.utils.data import DataLoader
 
-from tests.utilities import CocoFakeDataset
+from .utilities import CocoFakeDataset
 
-from centernet_multi_pose import CenterNetMultiPose
-from transforms import MultiSampleTransform
-from transforms.ctdet import CenterDetectionSample
-from transforms.multi_pose import MultiPoseSample
+from CenterNet.centernet_multi_pose import CenterNetMultiPose
+from CenterNet.transforms import MultiSampleTransform
+from CenterNet.transforms.ctdet import CenterDetectionSample
+from CenterNet.transforms.multi_pose import MultiPoseSample
 
 
 def test_multi_pose():

Diff for: tests/test_train_multi_pose.py

@@ -3,7 +3,7 @@
 import torch
 import imgaug.augmenters as iaa
 
-from transforms import ImageAugmentation, PoseFlip
+from CenterNet.transforms import ImageAugmentation, PoseFlip
 
 
 def test_image_augmentation():