Functions — github.com/DingLei14/WiCoNet

hub / github.com/DingLei14/WiCoNet / functions

Functions180 in github.com/DingLei14/WiCoNet

⨍ Functions 180◇ Types & classes 21

↓ 34 callersMethodupdate

(self, val, count=1, weight=1)

utils/utils.py:130

↓ 12 callersMethodaverage

(self)

utils/utils.py:145

↓ 10 callersFunctionaccuracy

(pred, label)

utils/utils.py:171

↓ 9 callersMethod__init__

(self)

models/WiCoNet.py:48

↓ 6 callersFunctioncrop_around_center

Given a NumPy / OpenCV 2 image, crops it to the given width and height, around it's centre point

utils/transform.py:621

↓ 6 callersFunctionrotate_image

Rotates an OpenCV 2 / NumPy image about it's centre by the given angle (in degrees). The returned image will be large enough to hold the enti

utils/transform.py:78

↓ 4 callersFunctionCaclTP

(imPred, imLab, numClass)

utils/utils.py:209

↓ 4 callersFunction_pad

(x, crop_size)

utils/misc.py:120

↓ 4 callersFunctionconv1x1

(in_planes, out_planes)

models/WiCoNet.py:17

↓ 4 callersFunctioncreate_crops

(img, size)

utils/load.py:238

↓ 4 callersFunctioncreate_crops_1C

(img, size)

utils/load.py:275

↓ 3 callersMethod__init__

(self, in_channels=3, num_classes=7, pretrained=True)

models/FCN_8s.py:52

↓ 3 callersFunctionget_square

Extract a left or a right square from ndarray shape : (H, W, C))

utils/utils.py:25

↓ 3 callersFunctionlargest_rotated_rect

Given a rectangle of size wxh that has been rotated by 'angle' (in radians), computes the width and height of the largest possible axis-a

utils/transform.py:643

↓ 3 callersFunctionnormalize_image

(im)

datasets/GID_WiCo.py:23

↓ 3 callersFunctionnormalize_image

(im)

datasets/PD_WiCo.py:21

↓ 3 callersFunctionnormalize_image

(im)

datasets/BLU_WiCo.py:16

↓ 3 callersFunctionrescale_image

(img, scale=8, order=0)

datasets/GID_WiCo.py:97

↓ 3 callersFunctionrescale_image

(img, scale=8, order=0)

datasets/BLU_WiCo.py:87

↓ 3 callersMethodstep

(self)

utils/misc.py:75

↓ 3 callersMethodtranspose_for_scores

(self, x)

models/WiCoNet.py:128

↓ 2 callersFunctionColor2Index

(ColorLabel)

datasets/GID_WiCo.py:45

↓ 2 callersFunctionColor2Index

(ColorLabel)

datasets/PD_WiCo.py:48

↓ 2 callersFunctionColor2Index

(ColorLabel)

datasets/BLU_WiCo.py:43

↓ 2 callersFunctionconv3x3

(in_planes, out_planes, stride=1)

models/WiCoNet.py:21

↓ 2 callersFunctionnorm_gray

(x, out_range=(0, 255))

Eval_WiCo_BLU.py:36

↓ 2 callersFunctionnorm_gray

(x, out_range=(0, 255))

Eval_WiCo_PD.py:34

↓ 2 callersFunctionnorm_gray

(x, out_range=(0, 255))

Eval_WiCo_GID.py:36

↓ 2 callersFunctionrescale_images

(imgs, scale, order=0)

datasets/GID_WiCo.py:91

↓ 2 callersFunctionrescale_images

(imgs, scale, order)

datasets/PD_WiCo.py:101

↓ 2 callersFunctionrescale_images

(imgs, scale, order=0)

datasets/BLU_WiCo.py:80

↓ 1 callersFunctionColor2Index0

(ColorLabel, colormap2label)

utils/load.py:166

↓ 1 callersFunctionDataAug

(data, labels, size)

utils/load.py:99

↓ 1 callersFunctionDataAug_1C

(data, labels, size)

utils/load.py:128

↓ 1 callersMethod__init__

(self, optimizer, curr_iter, max_iter, lr_decay)

utils/misc.py:66

↓ 1 callersFunction_fast_hist

(label_pred, label_true, num_classes)

utils/misc.py:42

↓ 1 callersMethod_init_weights

(self)

models/WiCoNet.py:56

↓ 1 callersMethodadd

(self, val, count, weight)

utils/utils.py:136

↓ 1 callersFunctionadjust_learning_rate

(optimizer, curr_iter, all_iter)

Train_WiCo_BLU.py:184

↓ 1 callersFunctionadjust_learning_rate

(optimizer, curr_iter, all_iter)

Train_WiCo_PD.py:182

↓ 1 callersFunctionadjust_learning_rate

(optimizer, curr_iter, all_iter)

Train_WiCo_GID.py:190

↓ 1 callersFunctioncalc_alpha

(curr_iter, all_iters, weight=1.0)

Train_WiCo_BLU.py:180

↓ 1 callersFunctioncalc_alpha

(curr_iter, all_iters, weight=1.0)

Train_WiCo_PD.py:178

↓ 1 callersFunctioncalc_alpha

(curr_iter, all_iters, weight=1.0)

Train_WiCo_GID.py:185

↓ 1 callersFunctionhwc_to_chw

(img)

utils/utils.py:36

↓ 1 callersMethodinitialize

(self, val, count, weight)

utils/utils.py:123

↓ 1 callersFunctioninitialize_weights

(*models)

utils/misc.py:16

↓ 1 callersFunctionmain

()

Train_WiCo_BLU.py:50

↓ 1 callersFunctionmain

()

Train_WiCo_PD.py:48

↓ 1 callersFunctionmain

()

Eval_WiCo_BLU.py:60

↓ 1 callersFunctionmain

()

Train_WiCo_GID.py:51

↓ 1 callersFunctionmain

()

Eval_WiCo_PD.py:56

↓ 1 callersFunctionmain

()

Eval_WiCo_GID.py:60

↓ 1 callersFunctionpredict

(net, pred_loader, pred_path, f_out=None)

Eval_WiCo_BLU.py:77

↓ 1 callersFunctionpredict

(net, pred_loader, pred_path, f_out=None)

Eval_WiCo_PD.py:72

↓ 1 callersFunctionpredict

(net, pred_loader, pred_path, f_out=None)

Eval_WiCo_GID.py:77

↓ 1 callersFunctionread_RSimages

(data_dir, mode, rescale_ratio=False)

datasets/GID_WiCo.py:65

↓ 1 callersFunctionread_RSimages

(data_dir, mode)

datasets/PD_WiCo.py:68

↓ 1 callersFunctionread_RSimages

(data_dir, mode, rescale_ratio=False)

datasets/BLU_WiCo.py:51

↓ 1 callersFunctionrescale_image

(img, scale=8, order = 0)

datasets/PD_WiCo.py:108

↓ 1 callersFunctionresize_and_crop

(pilimg, scale=0.5, final_height=None)

utils/utils.py:39

↓ 1 callersFunctiontrain

(train_loader, net, criterion, optimizer, val_loader)

Train_WiCo_BLU.py:67

↓ 1 callersFunctiontrain

(train_loader, net, criterion, optimizer, val_loader)

Train_WiCo_PD.py:66

↓ 1 callersFunctiontrain

(train_loader, net, criterion, optimizer, val_loader)

Train_WiCo_GID.py:70

↓ 1 callersFunctionvalidate

(val_loader, net, criterion, curr_epoch)

Train_WiCo_BLU.py:136

↓ 1 callersFunctionvalidate

(val_loader, net, criterion, curr_epoch)

Train_WiCo_PD.py:135

↓ 1 callersFunctionvalidate

(val_loader, net, criterion, curr_epoch)

Train_WiCo_GID.py:140

↓ 1 callersMethodvalue

(ColorLabels, colormap2label)

utils/load.py:157

FunctionColorls2Index

(ColorLabels)

datasets/GID_WiCo.py:40

FunctionColorls2Index

(ColorLabels)

datasets/PD_WiCo.py:42

FunctionColorls2Index

(ColorLabels)

datasets/BLU_WiCo.py:37

FunctionConfMap

(output, pred)

utils/utils.py:155

FunctionCrossEntropy2d

(input, target, weight=None, size_average=False)

utils/loss.py:16

FunctionIRRGB2RGBIR

(img)

datasets/GID_WiCo.py:19

FunctionImageValStretch2D

(img)

utils/utils.py:148

FunctionIndex2Color

(pred, colormap2label)

utils/load.py:171

FunctionIndex2Color

(pred)

datasets/GID_WiCo.py:35

FunctionIndex2Color

(pred)

datasets/PD_WiCo.py:36

FunctionIndex2Color

(pred)

datasets/BLU_WiCo.py:31

FunctionRotate_Aug

(imgs, labels, step=20, start_angle=20, max_angle=179)

utils/transform.py:678

FunctionRotate_Aug_S

(im, l, step=20, start_angle=15, max_angle=89)

utils/transform.py:695

Method__getitem__

(self, idx)

datasets/GID_WiCo.py:131

Method__getitem__

(self, idx)

datasets/PD_WiCo.py:141

Method__getitem__

(self, idx)

datasets/BLU_WiCo.py:122

Method__init__

(self, weight=None, ignore_index=0,)

utils/loss.py:6

Method__init__

(self, regular_filter, cuda=True)

(self, data_dir, mode, random_crop=False, crop_nums=40, random_flip=False, sliding_crop=False,\ size_

datasets/GID_WiCo.py:106

Method__init__

(self, data_dir, mode, random_crop=False, crop_nums=40, random_flip = False, sliding_crop=False,

datasets/PD_WiCo.py:117

Method__init__

(self, data_dir, mode, random_crop=False, crop_nums=40, random_flip=False, sliding_crop=False,\

datasets/BLU_WiCo.py:97

Method__init__

(self, in_channels=3, num_classes=7, pretrained=True)

models/WiCoNet.py:112

Method__init__

(self, in_channels=3, hidden_size=args['D'], img_size=args['input_size'])

models/WiCoNet.py:158

Method__init__

(self, in_channels, out_channels, downsample=True)

models/WiCoNet.py:175

Method__init__

(self, in_channels1, in_channels2, feat_size1, feat_size2, hidden_size=args['D'])

models/WiCoNet.py:196

Method__init__

(self, in_channels=3, num_classes=1)

models/WiCoNet.py:214

next →1–100 of 180, ranked by callers