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Functions1,778 in github.com/SpenserCai/sd-webui-deoldify

Function_flip_affine
Flip `x` horizontally.
fastai/vision/transform.py:72
Function_flip_lr
Flip `x` horizontally.
fastai/vision/transform.py:63
Method_generate_confusion
Average and Per Image Confusion: intersection of pixels given a true label, true label sums to 1
fastai/vision/interpret.py:60
Method_get_label
(fn)
fastai/vision/data.py:155
Method_get_num_rows_columns
(self, num_images: int, max_columns: int)
deoldify/visualize.py:179
Method_get_val1
(self, val)
fastai/general_optimizer.py:82
Method_get_val2
(self, state, val, param)
fastai/general_optimizer.py:83
Method_get_val3
(self, state, val, param)
fastai/general_optimizer.py:85
Function_hook_inner
(m,i,o)
fastai/callbacks/hooks.py:52
Function_image_maybe_add_crop_pad
(img, tfms)
fastai/vision/transform.py:206
Method_init
(self,*args,**kwargs)
fastai/core.py:64
Function_inner
(x, cpu=True)
fastai/torch_core.py:98
Method_inner
(o)
fastai/data_block.py:166
Method_inner
(*args, **kwargs)
fastai/data_block.py:471
Function_jitter
Replace pixels by random neighbors at `magnitude`.
fastai/vision/transform.py:57
Function_json_set_default
(obj)
fastai/gen_doc/doctest.py:10
Function_learner_distributed
Put `learn` on distributed training with `cuda_id`.
fastai/distributed.py:71
Function_learner_interpret
Create a `ClassificationInterpretation` object from `learner` on `ds_type` with `tta`.
fastai/train.py:217
Function_learner_interpret
Create a `ClassificationInterpretation` object from `learner` on `ds_type` with `tta`.
fastai/vision/learner.py:233
Function_learner_interpret
Create a 'ClassificationInterpretation' object from 'learner' on 'ds_type'.
fastai/tabular/models.py:78
Function_learner_parallel
Use nn.DataParallel when training and remove when done
fastai/distributed.py:65
Function_ll_pre_transform
Call `train_tfm` and `valid_tfm` after opening image, before converting from `PIL.Image`
fastai/vision/data.py:438
Function_loss_C
(real_pred, fake_pred)
fastai/vision/gan.py:197
Function_loss_G
(fake_pred, output, target, weights_gen=weights_gen)
fastai/vision/gan.py:192
Function_new_torch_cuda_set_device
(device)
fastai/torch_core.py:71
Function_noisify
( x, pct_pixels_min: float = 0.001, pct_pixels_max: float = 0.4, noise_range: int = 30 )
deoldify/augs.py:6
Function_normalize_batch
`b` = `x`,`y` - normalize `x` array of imgs and `do_y` optionally `y`.
fastai/vision/data.py:64
Function_pad
(x, padding:int, mode='reflection')
fastai/vision/transform.py:116
Function_pad_default
Pad `x` with `padding` pixels. `mode` fills in space ('zeros','reflection','border').
fastai/vision/transform.py:108
Function_pad_image_points
(x, padding:int, mode='reflection')
fastai/vision/transform.py:113
Method_pass
(self)
fastai/core.py:62
Function_pca
Compute PCA of `x` with `k` dimensions.
fastai/torch_core.py:309
Function_perspective_warp
Apply warp of `magnitude` to `c`.
fastai/vision/transform.py:264
Method_plot_intersect_cm
Plot confusion matrices: self.mean_cm or self.single_img_cm generated by `_generate_confusion`
fastai/vision/interpret.py:79
Function_presize
Resize images to `size` using `RandomResizedCrop`, passing along `kwargs` to train transform
fastai/vision/data.py:450
Method_queue_processor
Processes queued up write requests asynchronously to Tensorboard.
fastai/callbacks/tensorboard.py:223
Function_replace_rep
(m:Collection[str])
fastai/text/transform.py:44
Function_replace_wrep
(m:Collection[str])
fastai/text/transform.py:52
Method_repr_image_format
(self, format_str)
fastai/vision/image.py:279
Method_repr_png_
(self)
fastai/vision/image.py:88
Function_resnet_split
(m:nn.Module)
fastai/vision/learner.py:16
Function_rgb_randomize
Randomize one of the channels of the input image
fastai/vision/transform.py:137
Function_rotate
Rotate image by `degrees`.
fastai/vision/transform.py:25
Function_skew
Skew `c` field with random `direction` and `magnitude`.
fastai/vision/transform.py:289
Function_squeezenet_split
(m:nn.Module)
fastai/vision/learner.py:18
Function_squish
Squish image by `scale`. `row_pct`,`col_pct` select focal point of zoom.
fastai/vision/transform.py:47
Function_symmetric_warp
Apply symmetric warp of `magnitude` to `c`.
fastai/vision/transform.py:271
Function_tilt
Tilt `c` field with random `direction` and `magnitude`.
fastai/vision/transform.py:278
Method_transform
(self, image: PilImage)
deoldify/filters.py:92
Function_tta_only
Computes the outputs for several augmented inputs for TTA
fastai/vision/tta.py:10
Function_vgg_split
(m:nn.Module)
fastai/vision/learner.py:20
Method_write_training_loss
Writes training loss to Tensorboard.
fastai/callbacks/tensorboard.py:140
Method_write_weight_histograms
Writes model weight histograms to Tensorboard.
fastai/callbacks/tensorboard.py:115
Function_zoom
Zoom image by `scale`. `row_pct`,`col_pct` select focal point of zoom.
fastai/vision/transform.py:39
Function_zoom_squish
(c, scale:uniform=1.0, squish:uniform=1.0, invert:rand_bool=False, row_pct:uniform=0.5, col_pc
fastai/vision/transform.py:335
Functiona2k
(a)
fastai/gen_doc/doctest.py:81
Methodaccumulate
(self)
fastai/general_optimizer.py:35
Methodaccumulate
(self, val)
fastai/general_optimizer.py:44
Methodaccumulate
(self, val)
fastai/general_optimizer.py:53
Functionaccuracy_thresh
Computes accuracy when `y_pred` and `y_true` are the same size.
fastai/metrics.py:32
Functionaccuracy_thresh_expand
Compute accuracy after expanding `y_true` to the size of `y_pred`.
fastai/vision/gan.py:299
Functionadd_cyclic_datepart
Helper function that adds trigonometric date/time features to a date in the column `field_name` of `df`.
fastai/tabular/transform.py:43
Functionadd_datepart
Helper function that adds columns relevant to a date in the column `field_name` of `df`.
fastai/tabular/transform.py:55
Functionadd_elapsed_times
(df:DataFrame, field_names:Collection[str], date_field:str, base_field:str)
fastai/tabular/transform.py:80
Methodadd_special_cases
(self, toks:Collection[str])
fastai/text/transform.py:30
Methodadd_tfm
Add `tfm` to `self.tfms`.
fastai/basic_data.py:54
Methodaffine
Equivalent to `image.affine_mat = image.affine_mat @ func()`.
fastai/vision/image.py:187
Methodaffine_mat
Get the affine matrix that will be applied by `refresh`.
fastai/vision/image.py:202
Methodanalyze_pred
(self, pred, thresh:float=0.5)
fastai/data_block.py:380
Methodanalyze_pred
(self, pred, thresh:float=0.5)
fastai/data_block.py:424
Methodanalyze_pred
(self, pred)
fastai/vision/data.py:359
Methodanalyze_pred
(self, pred, thresh:float=0.5)
fastai/vision/data.py:386
Methodanalyze_pred
(self, pred, thresh:float=0.5)
fastai/vision/data.py:409
Functionannealing_cos
Cosine anneal from `start` to `end` as pct goes from 0.0 to 1.0.
fastai/callback.py:364
Functionannealing_exp
Exponentially anneal from `start` to `end` as pct goes from 0.0 to 1.0.
fastai/callback.py:361
Functionannealing_linear
Linearly anneal from `start` to `end` as pct goes from 0.0 to 1.0.
fastai/callback.py:358
Functionannealing_no
No annealing, always return `start`.
fastai/callback.py:355
Functionannealing_poly
Anneal polynomically from `start` to `end` as pct goes from 0.0 to 1.0.
fastai/callback.py:372
Methodapply_dropout
If a module contains 'dropout' in it's name, it will be switched to .train() mode.
fastai/basic_train.py:425
Methodapply_test
Function applied to `df` if it's the test set.
fastai/tabular/transform.py:129
Methodapply_test
Transform `self.cat_names` columns in categorical using the codes decided in `apply_train`.
fastai/tabular/transform.py:142
Methodapply_test
Fill missing values in `self.cont_names` like in `apply_train`.
fastai/tabular/transform.py:169
Methodapply_test
Normalize `self.cont_names` with the same statistics as in `apply_train`.
fastai/tabular/transform.py:192
Methodapply_tfms
Subclass this method if you want to apply data augmentation with `tfms` to this `ItemBase`.
fastai/core.py:186
Methodapply_tfms
Apply all `tfms` to the `Image`, if `do_resolve` picks value for random args.
fastai/vision/image.py:96
Methodapply_tfms
(self, tfms, **kwargs)
fastai/vision/gan.py:233
Methodapply_train
Transform `self.cat_names` columns in categorical.
fastai/tabular/transform.py:135
Methodapply_train
Fill missing values in `self.cont_names` according to `self.fill_strategy`.
fastai/tabular/transform.py:155
Methodapply_train
Compute the means and stds of `self.cont_names` columns to normalize them.
fastai/tabular/transform.py:183
Functionawd_lstm_clas_split
Split a RNN `model` in groups for differential learning rates.
fastai/text/models/awd_lstm.py:164
Functionawd_lstm_lm_split
Split a RNN `model` in groups for differential learning rates.
fastai/text/models/awd_lstm.py:159
Methodbackward
(ctx, grad_output:Tensor)
fastai/text/models/qrnn.py:63
Functionbasic_critic
A basic critic for images `n_channels` x `in_size` x `in_size`.
fastai/vision/gan.py:17
Functionbasic_generator
A basic generator from `noise_sz` to images `n_channels` x `in_size` x `in_size`.
fastai/vision/gan.py:28
Methodbatch_size
(self)
fastai/basic_data.py:42
Methodbatch_size
(self)
fastai/basic_data.py:233
Functionbatch_to_half
Set the input of batch `b` to half precision.
fastai/torch_core.py:227
Functionbb_pad_collate
Function that collect `samples` of labelled bboxes and adds padding with `pad_idx`.
fastai/vision/data.py:41
Methodbeam_search
Return the `n_words` that come after `text` using beam search.
fastai/text/learner.py:137
Methodbias
Bias for item or user (based on `is_item`) for all in `arr`. (Set model to `cpu` and no grad.)
fastai/collab.py:82
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