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Functions124 in github.com/HuiZeng/Image-Adaptive-3DLUT

⨍ Functions 124◇ Types & classes 27
↓ 17 callersFunctiondiscriminator_block
Returns downsampling layers of each discriminator block
models.py:179
↓ 12 callersFunctiondiscriminator_block
Returns downsampling layers of each discriminator block
models_x.py:50
↓ 10 callersMethod__init__
(self, dim=33)
models.py:341
↓ 7 callersMethod__init__
(self, dim=33)
models_x.py:221
↓ 4 callersFunctiongenerator
(img)
image_adaptive_lut_train_unpaired.py:182
↓ 3 callersFunction_is_numpy_image
(img)
torchvision_x_functional.py:47
↓ 3 callersMethodbackward
(self, grad_x)
models.py:324
↓ 2 callersFunctioncalculate_psnr
()
image_adaptive_lut_train_unpaired.py:128
↓ 2 callersFunctioncrop
crop image Arguments: img {ndarray} -- image to be croped top {int} -- top size left {int} -- left size hei
torchvision_x_functional.py:327
↓ 2 callersFunctiongenerator
(img)
image_adaptive_lut_evaluation.py:74
↓ 2 callersFunctiongenerator_eval
(img)
image_adaptive_lut_train_paired.py:141
↓ 1 callersFunctionTriLinearBackwardCpu
trilinear_cpp/src/trilinear.cpp:104
↓ 1 callersFunctionTriLinearBackwardCpu
trilinear_c/src/trilinear.c:104
↓ 1 callersFunctionTriLinearForwardCpu
trilinear_cpp/src/trilinear.cpp:50
↓ 1 callersFunctionTriLinearForwardCpu
trilinear_c/src/trilinear.c:50
↓ 1 callersFunction_is_tensor_image
(img)
torchvision_x_functional.py:43
↓ 1 callersFunctioncalculate_psnr
()
image_adaptive_lut_train_paired.py:154
↓ 1 callersFunctioncompute_gradient_penalty
Calculates the gradient penalty loss for WGAN GP
image_adaptive_lut_train_unpaired.py:160
↓ 1 callersMethodforward
(self, LUT)
models_x.py:232
↓ 1 callersFunctiongenerate_LUT
(img)
demo_eval.py:64
↓ 1 callersFunctiongenerate_identity_3DLUT
(dim, output_file)
utils/generate_identity_3DLUT.py:4
↓ 1 callersFunctiongenerator_train
(img)
image_adaptive_lut_train_paired.py:122
↓ 1 callersFunctionresize
resize the image TODO: opencv resize 之后图像就成了0~1了 Arguments: img {ndarray} -- the input ndarray image size {int, iterable} -- t
torchvision_x_functional.py:269
↓ 1 callersFunctionvis_lut
(lut, lut_dim)
utils/visualize_lut.py:14
↓ 1 callersFunctionvisualize_result
Saves a generated sample from the validation set
image_adaptive_lut_evaluation.py:86
FunctionPYBIND11_MODULE
trilinear_cpp/src/trilinear.cpp:170
FunctionPYBIND11_MODULE
trilinear_cpp/src/trilinear_cuda.cpp:31
Method__getitem__
(self, index)
datasets.py:49
Method__getitem__
(self, index)
datasets.py:129
Method__getitem__
(self, index)
datasets.py:203
Method__getitem__
(self, index)
datasets.py:295
Method__getitem__
(self, index)
datasets.py:372
Method__getitem__
(self, index)
datasets.py:450
Method__init__
(self, out_dim=5, aug_test=False)
models_x.py:22
Method__init__
(self, in_channels=3)
models_x.py:61
Method__init__
(self, in_channels=3)
models_x.py:81
Method__init__
(self, in_channels=3)
models_x.py:102
Method__init__
(self, dim=33)
models_x.py:123
Method__init__
(self, dim=33)
models_x.py:149
Method__init__
(self)
models_x.py:213
Method__init__
(self, out_dim=5, aug_test=False)
models.py:22
Method__init__
(self, in_size, out_size, normalize=True, dropout=0.0)
models.py:51
Method__init__
(self, in_size, out_size, normalize=True, dropout=0.0)
models.py:67
Method__init__
(self, in_channels=3, out_channels=3)
models.py:92
Method__init__
(self, in_channels=3)
models.py:156
Method__init__
(self, in_channels=3)
models.py:190
Method__init__
(self, in_channels=3)
models.py:210
Method__init__
(self, in_channels=3)
models.py:231
Method__init__
(self, dim=33)
models.py:252
Method__init__
(self, dim=33)
models.py:278
Method__init__
(self, root, mode="train", unpaird_data="fiveK", combined=True)
datasets.py:16
Method__init__
(self, root, mode="train", unpaird_data="fiveK", combined=True)
datasets.py:97
Method__init__
(self, root, mode="train", unpaird_data="fiveK")
datasets.py:174
Method__init__
(self, root, mode="train", unpaird_data="fiveK")
datasets.py:266
Method__init__
(self, root, mode="train", combined=True)
datasets.py:352
Method__init__
(self, root, mode="train")
datasets.py:422
Method__len__
(self)
datasets.py:89
Method__len__
(self)
datasets.py:167
Method__len__
(self)
datasets.py:258
Method__len__
(self)
datasets.py:344
Method__len__
(self)
datasets.py:415
Method__len__
(self)
datasets.py:498
Functionadjust_brightness
(img, value=0)
torchvision_x_functional.py:185
Functionadjust_contrast
(img, factor)
torchvision_x_functional.py:199
Functionadjust_hue
()
torchvision_x_functional.py:216
Functionadjust_saturation
()
torchvision_x_functional.py:212
Methodbackward
(ctx, lut_grad, x_grad)
models_x.py:193
Functionbbox_crop
crop bbox Arguments: img {ndarray} -- image to be croped top {int} -- top size left {int} -- left size heig
torchvision_x_functional.py:518
Functionbbox_hflip
horizontal flip the bboxes ^ ............. . . . . . . . . . . . . .............
torchvision_x_functional.py:480
Functionbbox_pad
(bboxes, padding)
torchvision_x_functional.py:538
Functionbbox_resize
resize the bbox Args: bboxes (ndarray): bbox ndarray [box_nums, 4] img_size (tuple): the image height and width targe
torchvision_x_functional.py:500
Functionbbox_shift
(bboxes, top, left)
torchvision_x_functional.py:457
Functionbbox_vflip
vertical flip the bboxes ........... . . . . >...........< . . . . ........... Args:
torchvision_x_functional.py:461
Functioncenter_crop
crop image Arguments: img {ndarray} -- input image output_size {number or sequence} -- the output image size. if sequence, sh
torchvision_x_functional.py:360
Functionelastic_transform
Elastic deformation of images as described in [Simard2003]_ (with modifications). Based on https://gist.github.com/erniejunior/601cdf56d2b424757de
torchvision_x_functional.py:407
Functionflip
(img, flip_code)
torchvision_x_functional.py:403
Methodforward
(self, x)
models_x.py:35
Methodforward
(self, img_input)
models_x.py:77
Methodforward
(self, img_input)
models_x.py:98
Methodforward
(self, img_input)
models_x.py:118
Methodforward
(self, x)
models_x.py:143
Methodforward
(self, x)
models_x.py:156
Methodforward
(ctx, lut, x)
models_x.py:163
Methodforward
(self, lut, x)
models_x.py:216
Methodforward
(self, x)
models.py:35
Methodforward
(self, x)
models.py:62
Methodforward
(self, x, skip_input)
models.py:84
Methodforward
(self, x)
models.py:130
Methodforward
(self, img_input)
models.py:171
Methodforward
(self, img_input)
models.py:206
Methodforward
(self, img_input)
models.py:227
Methodforward
(self, img_input)
models.py:247
Methodforward
(self, x)
models.py:272
Methodforward
(self, x)
models.py:285
Methodforward
(self, LUT, x)
models.py:291
Methodforward
(self, LUT)
models.py:352
Functiongaussian_blur
(img, kernel_size)
torchvision_x_functional.py:180
Functionhflip
(img)
torchvision_x_functional.py:400
Functionnoise
TODO: Not good for uint16 data
torchvision_x_functional.py:117
Functionnormalize
Normalize a tensor image with mean and standard deviation. .. note:: This transform acts out of place by default, i.e., it does not mutat
torchvision_x_functional.py:90
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