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Functions545 in github.com/bcmi/OSInsert-Image-Composition

⨍ Functions 545◇ Types & classes 112
↓ 1 callersFunctionmain
()
libcom/os_insert/source/insertanything_infer.py:503
↓ 1 callersFunctionmain
()
tests/test_os_insert.py:55
↓ 1 callersFunctionmake_beta_schedule
(schedule, n_timestep, linear_start=1e-4, linear_end=2e-2, cosine_s=8e-3)
libcom/os_insert/source/ldm/modules/diffusionmodules/util.py:21
↓ 1 callersMethodmake_cond_schedule
(self, )
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:499
↓ 1 callersMethodmake_schedule
(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True)
libcom/os_insert/source/ldm/models/diffusion/ddim.py:25
↓ 1 callersMethodmake_schedule
(self, ddim_num_steps, ddim_discretize="uniform", ddim_eta=0., verbose=True)
libcom/os_insert/source/ldm/models/diffusion/plms.py:24
↓ 1 callersFunctionmask2bbox
(mask)
libcom/os_insert/source/ldm/data/open_images.py:194
↓ 1 callersFunctionmax_neg_value
(tensor)
libcom/os_insert/source/ldm/modules/x_transformer.py:82
↓ 1 callersFunctionmean_flat
Take the mean over all non-batch dimensions.
libcom/os_insert/source/ldm/modules/diffusionmodules/util.py:192
↓ 1 callersFunctionmeasure_perplexity
(predicted_indices, n_embed)
libcom/os_insert/source/ldm/modules/losses/vqperceptual.py:26
↓ 1 callersMethodmeshgrid
(self, h, w)
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:596
↓ 1 callersFunctionnormal_kl
source: https://github.com/openai/guided-diffusion/blob/27c20a8fab9cb472df5d6bdd6c8d11c8f430b924/guided_diffusion/losses.py#L12 Compute the K
libcom/os_insert/source/ldm/modules/distributions/distributions.py:65
↓ 1 callersFunctionnot_equals
(val)
libcom/os_insert/source/ldm/modules/x_transformer.py:70
↓ 1 callersMethodp_losses
(self, x_start, t, noise=None)
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:300
↓ 1 callersMethodp_mean_variance
(self, x, t, clip_denoised: bool)
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:237
↓ 1 callersMethodp_mean_variance
(self, x, bbox, c, t, clip_denoised: bool, return_codebook_ids=False, quantize_denoised=False,
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:974
↓ 1 callersMethodp_sample
(self, x, t, clip_denoised=True, repeat_noise=False)
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:250
↓ 1 callersMethodp_sample_loop
(self, shape, return_intermediates=False)
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:259
↓ 1 callersMethodp_sample_loop
(self, cond, shape, return_intermediates=False, x_T=None, verbose=True, callback=None, t
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:1093
↓ 1 callersMethodp_sample_plms
(self, x, c, t, index, mask=None, repeat_noise=False, use_original_steps=False, quantize_denoised=False,
libcom/os_insert/source/ldm/models/diffusion/plms.py:174
↓ 1 callersFunctionpatch_context
Temporarily enable the patch within a `with` block and restore afterwards.
diffusers_osinsert/__init__.py:67
↓ 1 callersMethodplms_sampling
(self, cond, shape, x_T=None, ddim_use_original_steps=False, callb
libcom/os_insert/source/ldm/models/diffusion/plms.py:116
↓ 1 callersMethodprepare_latents
( self, image, timestep, batch_size, num_channels_latents, hei
diffusers_osinsert/_patched_pipeline_flux_fill.py:557
↓ 1 callersMethodq_mean_variance
Get the distribution q(x_t | x_0). :param x_start: the [N x C x ...] tensor of noiseless inputs. :param t: the number of diff
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:210
↓ 1 callersMethodrandom_crop_background
(self, image, bbox, mask)
libcom/os_insert/source/ldm/data/open_images.py:167
↓ 1 callersFunctionrescale_image_with_bbox
(image, bbox=None, long_size=1024)
libcom/os_insert/source/ldm/data/open_images.py:220
↓ 1 callersMethodreset_noise_accs
(self)
libcom/os_insert/source/ldm/models/diffusion/classifier.py:202
↓ 1 callersFunctionretrieve_timesteps
r""" Calls the scheduler's `set_timesteps` method and retrieves timesteps from the scheduler after the call. Handles custom timesteps. Any kwa
diffusers_osinsert/_patched_pipeline_flux_fill.py:94
↓ 1 callersFunctionreverse_clip_tensor
(tensor, img_size=(256,256))
libcom/os_insert/source/ldm/data/open_images.py:298
↓ 1 callersFunctionrun_insertanything
Single-image InsertAnything inference following the original diptych pipeline.
libcom/os_insert/source/insertanything_infer.py:404
↓ 1 callersMethodsample
(self, cond, batch_size=16, return_intermediates=False, x_T=None, verbose=True, timesteps=None,
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:1144
↓ 1 callersMethodsample_augmented_data
(self, source_np, bbox, mask, fg_img, fg_mask)
libcom/os_insert/source/ldm/data/open_images.py:393
↓ 1 callersMethodschedule
(self, n, **kwargs)
libcom/os_insert/source/ldm/lr_scheduler.py:17
↓ 1 callersMethodschedule
(self, n, **kwargs)
libcom/os_insert/source/ldm/lr_scheduler.py:59
↓ 1 callersFunctionsynset2idx
(path_to_yaml="data/index_synset.yaml")
libcom/os_insert/source/ldm/data/imagenet.py:20
↓ 1 callersFunctiontensor2images
(images, max_images=4, clamp=True, target_size=(256, 256))
libcom/os_insert/source/ldm/models/diffusion/ddpm.py:1341
↓ 1 callersFunctiontest_fos_dataset
()
libcom/os_insert/source/ldm/data/open_images.py:582
↓ 1 callersMethodwrite_logs
(self, loss, logits, targets)
libcom/os_insert/source/ldm/models/diffusion/classifier.py:162
↓ 1 callersFunctionzero_module
Zero out the parameters of a module and return it.
libcom/os_insert/source/ldm/modules/attention.py:67
Method__call__
Run a single OSInsert inference. Parameters ---------- background_path: Path to the background image. for
libcom/os_insert/os_insert.py:137
Method__call__
( self, *, source_image: str | Path | np.ndarray | Image.Image, mask_image: st
libcom/os_insert/source/insertanything_infer.py:199
Method__call__
(self, n, **kwargs)
libcom/os_insert/source/ldm/lr_scheduler.py:32
Method__call__
(self, n, **kwargs)
libcom/os_insert/source/ldm/lr_scheduler.py:77
Method__call__
(self, bg_img, bbox, bg_mask, fg_img, fg_mask)
libcom/os_insert/source/ldm/data/open_images.py:140
Method__call__
Patched FluxFillPipeline forward. This local copy extends the upstream FluxFillPipeline to support a two-phase mask schedule during d
diffusers_osinsert/_patched_pipeline_flux_fill.py:622
Method__getitem__
(self, i)
libcom/os_insert/source/ldm/data/imagenet.py:42
Method__getitem__
(self, i)
libcom/os_insert/source/ldm/data/imagenet.py:339
Method__getitem__
(self, i)
libcom/os_insert/source/ldm/data/lsun.py:39
Method__getitem__
(self, idx)
libcom/os_insert/source/ldm/data/datamodule.py:34
Method__getitem__
(self, index)
libcom/os_insert/source/ldm/data/open_images.py:427
Method__getitem__
(self, index)
libcom/os_insert/source/ldm/data/open_images.py:478
Method__getitem__
(self, index)
libcom/os_insert/source/ldm/data/open_images.py:550
Method__init__
( self, model_dir: str | Path, device: str = "cuda:0", *, eager_aggres
libcom/os_insert/os_insert.py:59
Method__init__
( self, *, model_dir: str | Path | None = None, flux_fill_path: str | Path | N
libcom/os_insert/source/insertanything_infer.py:176
Method__init__
(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0)
libcom/os_insert/source/ldm/lr_scheduler.py:8
Method__init__
(self, warm_up_steps, f_min, f_max, f_start, cycle_lengths, verbosity_interval=0)
libcom/os_insert/source/ldm/lr_scheduler.py:41
Method__init__
(self, model, decay=0.9999, use_num_upates=True)
libcom/os_insert/source/ldm/modules/ema.py:6
Method__init__
(self, dim, max_seq_len)
libcom/os_insert/source/ldm/modules/x_transformer.py:26
Method__init__
(self, dim)
libcom/os_insert/source/ldm/modules/x_transformer.py:40
Method__init__
(self, fn)
libcom/os_insert/source/ldm/modules/x_transformer.py:129
Method__init__
(self, dim, eps=1e-5)
libcom/os_insert/source/ldm/modules/x_transformer.py:140
Method__init__
(self, dim, eps=1e-8)
libcom/os_insert/source/ldm/modules/x_transformer.py:152
Method__init__
(self, dim)
libcom/os_insert/source/ldm/modules/x_transformer.py:169
Method__init__
(self, dim_in, dim_out)
libcom/os_insert/source/ldm/modules/x_transformer.py:185
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)
libcom/os_insert/source/ldm/modules/x_transformer.py:195
Method__init__
( self, dim, dim_head=DEFAULT_DIM_HEAD, heads=8, c
libcom/os_insert/source/ldm/modules/x_transformer.py:216
Method__init__
( self, dim, depth, heads=8, causal=False,
libcom/os_insert/source/ldm/modules/x_transformer.py:371
Method__init__
(self, **kwargs)
libcom/os_insert/source/ldm/modules/x_transformer.py:542
Method__init__
( self, *, num_tokens, max_seq_len, attn_layers,
libcom/os_insert/source/ldm/modules/x_transformer.py:549
Method__init__
(self, dim, dim_out=None, mult=4, glu=False, dropout=0.)
libcom/os_insert/source/ldm/modules/attention.py:48
Method__init__
(self, dim, heads=4, dim_head=32)
libcom/os_insert/source/ldm/modules/attention.py:81
Method__init__
(self, in_channels)
libcom/os_insert/source/ldm/modules/attention.py:100
Method__init__
(self, query_dim, context_dim=None, heads=8, dim_head=64, dropout=0.)
libcom/os_insert/source/ldm/modules/attention.py:153
Method__init__
(self, dim, n_heads, d_head, dropout=0., context_dim=None, gated_ff=True, checkpoint=True)
libcom/os_insert/source/ldm/modules/attention.py:197
Method__init__
(self, in_channels, n_heads, d_head, depth=1, dropout=0., context_dim=None)
libcom/os_insert/source/ldm/modules/attention.py:226
Method__init__
( self, spacial_dim: int, embed_dim: int, num_heads_channels: int, out
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:37
Method__init__
(self, channels, out_channels=None, ks=5)
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:123
Method__init__
(self, channels, use_conv, dims=2, out_channels=None,padding=1)
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:143
Method__init__
( self, channels, emb_channels, dropout, out_channels=None, us
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:179
Method__init__
( self, channels, emb_channels, dropout, out_channels=None, us
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:294
Method__init__
( self, channels, num_heads=1, num_head_channels=-1, use_checkpoint=Fa
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:400
Method__init__
(self, n_heads)
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:467
Method__init__
(self, n_heads)
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:499
Method__init__
( self, image_size, in_channels, model_channels, out_channels,
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:558
Method__init__
( self, image_size, in_channels, model_channels, out_channels,
libcom/os_insert/source/ldm/modules/diffusionmodules/openaimodel.py:898
Method__init__
(self, c_concat_config, c_crossattn_config)
libcom/os_insert/source/ldm/modules/diffusionmodules/util.py:253
Method__init__
(self, in_channels, with_conv)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:43
Method__init__
(self, in_channels, with_conv)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:61
Method__init__
(self, *, in_channels, out_channels=None, conv_shortcut=False, dropout, temb_channels=512)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:83
Method__init__
(self, in_channels)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:146
Method__init__
(self, in_channels)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:151
Method__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:369
Method__init__
(self, *, ch, out_ch, ch_mult=(1,2,4,8), num_res_blocks, attn_resolutions, dropout=0.0, resam
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:463
Method__init__
(self, in_channels, out_channels, *args, **kwargs)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:572
Method__init__
(self, in_channels, out_channels, ch, num_res_blocks, resolution, ch_mult=(2,2), dropout=0.0)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:608
Method__init__
(self, factor, in_channels, mid_channels, out_channels, depth=2)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:656
Method__init__
(self, in_channels, ch, resolution, out_ch, num_res_blocks, attn_resolutions, dropout=0.0, re
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:693
Method__init__
(self, z_channels, out_ch, resolution, num_res_blocks, attn_resolutions, ch, ch_mult=(1,2,4,8),
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:712
Method__init__
(self, in_size, out_size, in_channels, out_channels, ch_mult=2)
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:729
Method__init__
(self, in_channels=None, learned=False, mode="bilinear")
libcom/os_insert/source/ldm/modules/diffusionmodules/model.py:748
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