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Functions132 in github.com/AyanKumarBhunia/semisupervised-FGSBIR

⨍ Functions 132◇ Types & classes 30
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/Image_Networks.py:130
Methodforward
(self, x, Seq_Len=None)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Sketch_Networks.py:16
Methodforward
(self, inputs, z_vector, seq_len = None, hidden_cell=None, isTrain = True, get_deterministic = True)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Sketch_Networks.py:35
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:13
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:24
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:40
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:65
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:87
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:100
Methodforward
(self, x)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:111
Methodfreeze_weights
(self)
Photo_to_Sketch_2D_Attention/base_model.py:29
Methodfreeze_weights
(self)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/base_model.py:369
Functionget_bounds
Return bounds of data.
Photo_to_Sketch_2D_Attention/utils.py:38
Functionget_bounds
Return bounds of data.
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/utils.py:36
Methodmax_size
larger sequence length in the data set
Photo_to_Sketch_2D_Attention/dataset.py:264
Methodmax_size
larger sequence length in the data set
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/dataset.py:248
Methodpretrain_ImageBranch
(self, epoch = 200)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/base_model.py:191
Methodpretrain_SketchBranch
(self, iteration = 100000)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/base_model.py:29
Functionrasterize_relative
(stroke_list, fig, xlim=[0,255], ylim=[0,255])
Photo_to_Sketch_2D_Attention/rasterize.py:113
Functionrasterize_relative
(stroke_list, fig, xlim=[0,255], ylim=[0,255])
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/rasterize.py:113
Functionsample_next_state
(output, hp, temperature =0.01)
Photo_to_Sketch_2D_Attention/utils.py:85
Methodsketch_generation_sample
(self, dataloader, number_of_sample=64, condition = True)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/base_model.py:151
FunctiontoStrokeList
(sketch)
Photo_to_Sketch_2D_Attention/rasterize.py:73
FunctiontoStrokeList
(sketch)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/rasterize.py:73
Functionto_Absolute
(sketch, start_point=(0,0))
Photo_to_Sketch_2D_Attention/rasterize.py:64
Functionto_Absolute
(sketch, start_point=(0,0))
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/rasterize.py:64
Functiontransfer_ImageNomralization
(x, type='to_Gen')
Photo_to_Sketch_2D_Attention/utils.py:61
Functiontransfer_ImageNomralization
(x, type='to_Gen')
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/utils.py:59
Methodvalid_batch
(self, batch_size_sketch_rnn=100)
Photo_to_Sketch_2D_Attention/dataset.py:325
Methodvis_image
(self, visularize, step, normalize=False)
Photo_to_Sketch_2D_Attention/utils.py:141
Functionweights_init_normal
(m)
Photo_to_Sketch_2D_Attention/Image_Networks.py:137
Functionweights_init_normal
(m)
Photo_to_Sketch_2D_Attention/CVPR_18_Baseline/Image_Networks.py:118
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