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Functions140 in github.com/HuiZeng/Grid-Anchor-based-Image-Cropping-Pytorch

⨍ Functions 140◇ Types & classes 44
↓ 6 callersMethod__init__
(self, loadweights=True, downsample=4)
croppingModel.py:14
↓ 3 callersFunction_make_divisible
This function is taken from the original tf repo. It ensures that all layers have a channel number that is divisible by 8 It can be seen
mobilenetv2.py:15
↓ 3 callersFunctionbuild_crop_model
(scale='single', alignsize=8, reddim=32, loadweight=True, model=None, downsample=4)
croppingModel.py:296
↓ 3 callersFunctionfc_layers
(reddim = 32, alignsize = 8)
croppingModel.py:116
↓ 2 callersMethod__init__
(self, aligned_height, aligned_width, spatial_scale)
rod_align/modules/rod_align.py:7
↓ 2 callersMethod__init__
(self, aligned_height, aligned_width, spatial_scale)
roi_align/modules/roi_align.py:7
↓ 2 callersMethod_concat
(x, out)
ShuffleNetV2.py:90
↓ 1 callersFunctionRODAlignBackwardCpu
rod_align/src/rod_align.c:132
↓ 1 callersFunctionRODAlignForwardCpu
rod_align/src/rod_align.c:80
↓ 1 callersFunctionROIAlignBackwardCpu
roi_align/src/roi_align.c:138
↓ 1 callersFunctionROIAlignForwardCpu
roi_align/src/roi_align.c:80
↓ 1 callersMethod__init__
(self, n_class=1000, input_size=224, width_mult=1.)
ShuffleNetV2.py:106
↓ 1 callersMethod__init__
(self, num_classes=1000, input_size=224, width_mult=1.)
mobilenetv2.py:92
↓ 1 callersFunction_import_symbols
(locals)
rod_align/_ext/rod_align/__init__.py:6
↓ 1 callersFunction_import_symbols
(locals)
roi_align/_ext/roi_align/__init__.py:6
↓ 1 callersMethod_initialize_weights
(self)
mobilenetv2.py:136
↓ 1 callersMethodbackward
(self, grad_output)
rod_align/functions/rod_align.py:37
↓ 1 callersFunctionchannel_shuffle
(x, groups)
ShuffleNetV2.py:24
↓ 1 callersFunctionconv_1x1_bn
(inp, oup)
ShuffleNetV2.py:17
↓ 1 callersFunctionconv_1x1_bn
(inp, oup)
mobilenetv2.py:43
↓ 1 callersFunctionconv_3x3_bn
(inp, oup, stride)
mobilenetv2.py:35
↓ 1 callersFunctionconv_bn
(inp, oup, stride)
ShuffleNetV2.py:9
↓ 1 callersFunctiongenerate_bboxes
(image)
croppingDataset.py:135
↓ 1 callersFunctionintersect
(box_a, box_b)
augmentations.py:9
↓ 1 callersFunctionjaccard_numpy
(box_a, box_b)
augmentations.py:16
↓ 1 callersFunctionshufflenetv2
(width_mult=1.)
ShuffleNetV2.py:166
↓ 1 callersFunctiontest
()
TrainModel.py:71
↓ 1 callersFunctiontest
()
demo_eval.py:50
↓ 1 callersFunctiontest
()
TestAccuracy.py:37
↓ 1 callersFunctiontrain
()
TrainModel.py:162
↓ 1 callersFunctionxavier
(param)
croppingModel.py:286
Method__call__
(self, sample,image_size)
croppingDataset.py:16
Method__call__
(self, image, image_size)
croppingDataset.py:100
Method__call__
(self, img, boxes=None, labels=None)
augmentations.py:38
Method__call__
(self, img, boxes=None, labels=None)
augmentations.py:51
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:56
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:64
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:71
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:82
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:96
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:109
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:121
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:135
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:148
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:166
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:179
Method__call__
(self, tensor, boxes=None, labels=None)
augmentations.py:187
Method__call__
(self, cvimage, boxes=None, labels=None)
augmentations.py:192
Method__call__
(self, image, boxes=None, labels=None)
augmentations.py:222
Method__call__
(self, image, boxes, labels)
augmentations.py:304
Method__call__
(self, image, annotations, classes)
augmentations.py:329
Method__call__
Args: image (Tensor): image tensor to be transformed Return: a tensor with channels swapped according to swap
augmentations.py:350
Method__call__
(self, image, boxes, labels)
augmentations.py:378
Method__call__
(self, img, annotations)
augmentations.py:396
Method__getitem__
(self, idx)
croppingDataset.py:69
Method__getitem__
(self, idx)
croppingDataset.py:213
Method__init__
(self, loadweights=True, downsample=4)
croppingModel.py:39
Method__init__
(self, loadweights=True, downsample=4, model_path='pretrained_model/mobilenetv2_1.0-0c6065bc.pth')
croppingModel.py:60
Method__init__
(self, loadweights=True, downsample=4, model_path='pretrained_model/shufflenetv2_x1_69.402_88.374.pth.tar')
croppingModel.py:89
Method__init__
(self, alignsize = 8, reddim = 8, loadweight = True, model = None, downsample=4)
croppingModel.py:135
Method__init__
(self, alignsize = 8, reddim = 32, loadweight = True, model = None, downsample = 4)
croppingModel.py:181
Method__init__
(self, alignsize = 8, reddim = 32, loadweight = True, model = None, downsample = 4)
croppingModel.py:234
Method__init__
(self, inp, oup, stride, benchmodel)
ShuffleNetV2.py:41
Method__init__
(self, image_size=256, dataset_dir='dataset/GAIC/', set = 'train', transform=TransformFunctio
croppingDataset.py:51
Method__init__
(self, image_size=256.0,dataset_dir='testsetDir', transform=TransformFunctionTest())
croppingDataset.py:202
Method__init__
(self, transforms)
augmentations.py:35
Method__init__
(self, lambd)
augmentations.py:47
Method__init__
(self, mean)
augmentations.py:61
Method__init__
(self, size=300)
augmentations.py:93
Method__init__
(self, lower=0.5, upper=1.5)
augmentations.py:103
Method__init__
(self, delta=18.0)
augmentations.py:117
Method__init__
(self)
augmentations.py:130
Method__init__
(self, current='BGR', transform='HSV')
augmentations.py:144
Method__init__
(self, lower=0.5, upper=1.5)
augmentations.py:159
Method__init__
(self, delta=32)
augmentations.py:174
Method__init__
(self)
augmentations.py:209
Method__init__
(self, mean)
augmentations.py:301
Method__init__
(self, swaps)
augmentations.py:347
Method__init__
(self)
augmentations.py:366
Method__init__
(self)
augmentations.py:389
Method__init__
(self, inp, oup, stride, expand_ratio)
mobilenetv2.py:52
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
rod_align/modules/rod_align.py:19
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
rod_align/modules/rod_align.py:32
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
rod_align/functions/rod_align.py:8
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
roi_align/modules/roi_align.py:19
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
roi_align/modules/roi_align.py:32
Method__init__
(self, aligned_height, aligned_width, spatial_scale)
roi_align/functions/roi_align.py:8
Method__len__
(self)
croppingDataset.py:94
Method__len__
(self)
croppingDataset.py:226
Method_init_weights
(self)
croppingModel.py:173
Method_init_weights
(self)
croppingModel.py:227
Method_init_weights
(self)
croppingModel.py:281
Functionadd_hooks
(m)
thop/profile.py:45
Methodbackward
(self, grad_output)
roi_align/functions/roi_align.py:37
Functionclever_format
(num, format="%.2f")
thop/utils.py:2
Functioncount_adap_avgpool
(m, x, y)
thop/count_hooks.py:137
Functioncount_adap_maxpool
(m, x, y)
thop/count_hooks.py:118
Functioncount_avgpool
(m, x, y)
thop/count_hooks.py:127
Functioncount_bn
(m, x, y)
thop/count_hooks.py:78
Functioncount_conv2d
(m, x, y)
thop/count_hooks.py:24
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