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Functions2,992 in github.com/brycedrennan/imaginAIry

⨍ Functions 2,992◇ Types & classes 731↳ Endpoints 37
Methodapply_masks
(self, mask_cache)
imaginairy/enhancers/bool_masker.py:57
Methodapply_masks
(self, mask_cache)
imaginairy/enhancers/bool_masker.py:90
Methodapply_masks
(self, mask_cache)
imaginairy/enhancers/bool_masker.py:134
Functionapply_min_size
Rezise the sample to ensure the given size. Keeps aspect ratio. Args: sample (dict): sample size (tuple): image size Re
imaginairy/modules/midas/midas/transforms.py:9
Methodapply_model
(self, *args, **kwargs)
imaginairy/samplers/kdiff.py:28
Methodaspect_ratio
(self)
imaginairy/schema.py:760
Functionassert_ndarray_uint8_255_hwc
(img)
imaginairy/img_processors/densepose.py:298
Functionattention_forward
Modification of timm.models.beit.py: Attention.forward to support arbitrary window sizes.
imaginairy/modules/midas/midas/backbones/beit.py:78
Methodauto_attach
(self, target: fl.Chain, exclude: list[str] | None = None)
imaginairy/vendored/refiners/fluxion/adapters/lora.py:87
Methodauto_attach
(self, target: Chain, exclude: list[str] | None = None)
imaginairy/vendored/refiners/fluxion/adapters/lora.py:126
Methodauto_attach
(self, target: Chain, exclude: list[str] | None = None)
imaginairy/vendored/refiners/fluxion/adapters/lora.py:204
Methodbackward
(ctx, *output_grads)
imaginairy/modules/diffusion/util.py:167
Methodbackward
(ctx, *output_grads)
imaginairy/modules/sgm/diffusionmodules/util.py:113
Methodbackward
(ctx, *output_grads)
imaginairy/modules/sgm/diffusionmodules/util.py:180
Methodbackward
(ctx, *grads)
imaginairy/vendored/blip/blip_retrieval.py:349
Methodbatched_detect_faces
Arguments: frames: a list of PIL.Image, or np.array(shape=[n, h, w, c], type=np.uint8, BGR format). c
imaginairy/vendored/facexlib/detection/retinaface.py:304
Functionbeit_forward_features
Modification of timm.models.beit.py: Beit.forward_features to support arbitrary window sizes.
imaginairy/modules/midas/midas/backbones/beit.py:138
Functionbetas_for_alpha_bar
Create a beta schedule that discretizes the given alpha_t_bar function, which defines the cumulative product of (1-beta) over time from t = [
imaginairy/modules/diffusion/util.py:113
Functionblip_decoder
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip.py:216
Functionblip_feature_extractor
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip.py:224
Functionblip_itm
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip_itm.py:84
Functionblip_nlvr
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip_nlvr.py:79
Functionblip_pretrain
(**kwargs)
imaginairy/vendored/blip/blip_pretrain.py:314
Functionblip_retrieval
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip_retrieval.py:310
Functionblip_vqa
(pretrained="", **kwargs)
imaginairy/vendored/blip/blip_vqa.py:220
Functionblock_forward
Modification of timm.models.beit.py: Block.forward to support arbitrary window sizes. See https://github.com/isl-org/MiDaS/pull/234
imaginairy/modules/midas/midas/backbones/beit.py:113
Functionbuild_read_buffer
(img, montage, read_buffer, videogen)
imaginairy/enhancers/video_interpolation/rife/interpolate.py:203
Methodcalculate_text_conditioning_kwargs
( self, positive_prompts: List[WeightedPrompt], negative_prompts: List[WeightedPrompt]
imaginairy/modules/refiners_sd.py:401
Methodcalculate_text_conditioning_kwargs
( self, positive_prompts: List[WeightedPrompt], negative_prompts: List[WeightedPrompt]
imaginairy/modules/refiners_sd.py:508
Methodcallback
(data)
imaginairy/samplers/kdiff.py:133
Methodcb
(context)
imaginairy/utils/log_utils.py:240
Functioncenter_size
Convert prior_boxes to (cx, cy, w, h) representation for comparison to center-size form ground truth data. Args: boxes: (tensor) poin
imaginairy/vendored/facexlib/detection/retinaface_utils.py:65
Functioncheck_nan_path
(path: str, device)
imaginairy/weight_management/translation.py:89
Functioncheck_torch_working
Check that torch is working.
imaginairy/utils/__init__.py:199
Functionchunk_latent
(tensor, chunk_size=64, overlap_size=8)
imaginairy/modules/autoencoder.py:610
Functionclear_write_buffer
(png_out, write_buffer)
imaginairy/enhancers/video_interpolation/rife/interpolate.py:191
Methodclip_image_encoder
(self)
imaginairy/vendored/refiners/foundationals/latent_diffusion/image_prompt.py:378
Functionclip_load_untrained
(version)
imaginairy/vendored/clipseg/__init__.py:354
Methodclip_tokenizer_parent
(self)
imaginairy/vendored/refiners/foundationals/clip/concepts.py:132
Methodcollect_execution_order_hook
(layer: nn.Module, *_: Any)
imaginairy/vendored/refiners/fluxion/model_converter.py:536
Functioncolorize_cmd
Colorize images using AI. Doesn't work very well yet.
imaginairy/cli/colorize.py:33
Methodcompute_attention_scores
(self, query: Tensor, key: Tensor, value: Tensor)
imaginairy/vendored/refiners/foundationals/latent_diffusion/self_attention_guidance.py:42
Functioncompute_attention_scores_logged
( self, query: Tensor, key: Tensor, value: Tensor )
imaginairy/modules/refiners_sd.py:899
Methodcompute_averaged_unconditioned_x
(self, x: Tensor, unguided_unconditioned_x: Tensor)
imaginairy/vendored/refiners/foundationals/latent_diffusion/reference_only_control.py:56
Methodcompute_clip_text_embedding
(self, text: str, negative_text: str | None = None)
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_xl/model.py:44
Methodcompute_clip_text_embedding
(self, text: str, negative_text: str = "")
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_1/model.py:47
Methodcompute_condition_features
(self, condition: Tensor)
imaginairy/vendored/refiners/foundationals/latent_diffusion/t2i_adapter.py:201
Methodcompute_image_embedding
(self, image: Image.Image)
imaginairy/vendored/refiners/foundationals/segment_anything/model.py:44
Functioncompute_increased_bbox
(bbox, increase_area, preserve_aspect=True)
imaginairy/vendored/facexlib/utils/face_utils.py:6
Methodcompute_self_attention_guidance
( self, x: Tensor, noise: Tensor, step: int, *, clip_text_embe
imaginairy/modules/refiners_sd.py:463
Methodcompute_self_attention_guidance
( self, x: Tensor, noise: Tensor, step: int, *, clip_text_embe
imaginairy/modules/refiners_sd.py:627
Methodcompute_self_attention_guidance
( self, x: Tensor, noise: Tensor, step: int, *, clip_text_embe
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_xl/model.py:119
Methodcompute_self_attention_guidance
( self, x: Tensor, noise: Tensor, step: int, *, clip_text_embedding: Tensor, **kwargs: Tensor )
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_1/model.py:78
Methodcompute_self_attention_guidance
( self, x: Tensor, noise: Tensor, step: int, *, clip_text_embedding: Tensor, **kwargs: Tensor )
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_1/model.py:156
Methodcompute_sinusoidal_embedding
(self, x: Int[Tensor, "*batch 1"])
imaginairy/vendored/refiners/foundationals/latent_diffusion/range_adapter.py:42
Methodcompute_sinusoidal_embedding
(self, x: Tensor)
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_xl/unet.py:52
Methodconcatenate_embeddings
( self, text_embedding_l: Tensor, text_embedding_with_pooling: tuple[Tensor, Tensor] )
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_xl/text_encoder.py:80
Methodconfigure_optimizers
(self)
imaginairy/modules/autoencoder.py:396
Methodconfigure_optimizers
(self)
imaginairy/modules/diffusion/ddpm.py:707
Methodconfigure_optimizers
(self)
imaginairy/modules/diffusion/ddpm.py:1665
Methodconfigure_optimizers
(self)
imaginairy/modules/sgm/diffusion.py:234
Methodconfigure_optimizers
(self)
imaginairy/modules/sgm/autoencoder.py:108
Methodconfigure_optimizers
(self)
imaginairy/modules/sgm/autoencoder.py:376
Functionconv_bn
(in_planes, out_planes, kernel_size=3, stride=1, padding=1, dilation=1)
imaginairy/enhancers/video_interpolation/rife/IFNet_HDv3.py:25
Functionconvert_module_to_f16
(_)
imaginairy/modules/diffusion/openaimodel.py:26
Functionconvert_module_to_f32
(_)
imaginairy/modules/diffusion/openaimodel.py:30
Methodconvert_to_fp16
Convert the torso of the model to float16.
imaginairy/modules/diffusion/openaimodel.py:796
Methodconvert_to_fp32
Convert the torso of the model to float32.
imaginairy/modules/diffusion/openaimodel.py:804
Functioncosine_distance_float32
In some environments we need to distance to be in float32 but it was coming as BFloat16.
imaginairy/utils/safety.py:133
Methodcould_convert
(self, source_weights)
imaginairy/weight_management/conversion.py:70
Methodcount_flops
(model, _x, y)
imaginairy/modules/diffusion/openaimodel.py:391
Methodcount_flops
(model, _x, y)
imaginairy/modules/diffusion/openaimodel.py:425
Functioncreate_canny_edges
(img: "Tensor")
imaginairy/img_processors/control_modes.py:10
Methodcreate_custom_forward
(module)
imaginairy/vendored/blip/nlvr_encoder.py:530
Methodcreate_custom_forward
(module)
imaginairy/vendored/blip/med.py:483
Functioncreate_densepose_map
(img_t: "Tensor")
imaginairy/img_processors/control_modes.py:142
Functioncreate_hed_edges
(img_t: "Tensor")
imaginairy/img_processors/control_modes.py:109
Functioncreate_normal_map
(img: "Tensor")
imaginairy/img_processors/control_modes.py:95
Functioncreate_normal_map_pil_img
(img, device=get_device())
imaginairy/vendored/imaginairy_normal_map/model.py:29
Functioncreate_pose_map
(img_t: "Tensor")
imaginairy/img_processors/control_modes.py:132
Functioncrop_border
Crop borders of images. Args: imgs (list[ndarray] | ndarray): Images with shape (h, w, c). crop_border (int): Crop border for eac
imaginairy/vendored/basicsr/img_util.py:171
Methodcustom_forward
(*inputs)
imaginairy/vendored/blip/nlvr_encoder.py:531
Methodcustom_forward
(*inputs)
imaginairy/vendored/blip/med.py:484
Methoddebug_crop
(self, analyse_image, crop)
imaginairy/vendored/smart_crop.py:229
Methoddecode
(self, x)
imaginairy/modules/refiners_sd.py:713
Methoddecode
(self, x, *args, **kwargs)
imaginairy/modules/autoencoder.py:598
Methoddecode
(self, *args, **kwargs)
imaginairy/modules/sgm/autoencoder.py:101
Methoddecode
(self, z: torch.Tensor, **decoder_kwargs)
imaginairy/modules/sgm/autoencoder.py:503
Methoddecode
(self, x: Any, *args, **kwargs)
imaginairy/modules/sgm/autoencoder.py:573
Methoddecode_latents
(self, x: Tensor)
imaginairy/vendored/refiners/foundationals/latent_diffusion/auto_encoder.py:218
Functiondecorator
(fn)
imaginairy/utils/model_cache.py:372
Functiondefault_model_loaded
Just to make sure default weights are downloaded before the test runs
tests/conftest.py:121
Methoddefault_negative_prompt
(self)
imaginairy/schema.py:486
Methoddefault_time_ids
(self)
imaginairy/vendored/refiners/foundationals/latent_diffusion/stable_diffusion_xl/model.py:59
Functiondemo
(img_path)
imaginairy/img_processors/segformer_b2_clothes.py:214
Functiondensepose_chart_predictor_output_to_result
( boxes: torch.Tensor, coarse_segm: torch.Tensor, fine_segm, u, v )
imaginairy/img_processors/densepose.py:572
Functiondescribe_cmd
Generate text descriptions of images.
imaginairy/cli/describe.py:8
Functiondetect_cuda_tests
(request)
tests/conftest.py:142
Methoddevice
(self)
imaginairy/vendored/refiners/fluxion/layers/module.py:160
Methoddevice
(self)
imaginairy/vendored/refiners/fluxion/layers/basics.py:199
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