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Functions4,150 in github.com/Adamdad/hash3D

⨍ Functions 4,150◇ Types & classes 914↳ Endpoints 2
↓ 5 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
gaussiandreamer-hash3d/DeepCache/sdxl/pipeline_utils.py:753
↓ 5 callersMethoddevice
r""" Returns: `torch.device`: The torch device on which the pipeline is located.
threestudio-hash3d/DeepCache/sdxl/pipeline_utils.py:753
↓ 5 callersMethoddo_update_step_end
(self, epoch: int, global_step: int)
threestudio-hash3d/threestudio/utils/base.py:38
↓ 5 callersMethodexport
(self, *args, **kwargs)
gaussiandreamer-hash3d/threestudio/models/geometry/base.py:50
↓ 5 callersMethodforward_density
(self, points: Float[Tensor, "*N Di"])
threestudio-hash3d/threestudio/models/geometry/volume_grid.py:148
↓ 5 callersMethodforward_sdf
(self, points: Float[Tensor, "*N Di"])
gaussiandreamer-hash3d/threestudio/models/geometry/implicit_sdf.py:335
↓ 5 callersMethodforward_sdf
(self, points: Float[Tensor, "*N Di"])
threestudio-hash3d/threestudio/models/geometry/implicit_sdf.py:335
↓ 5 callersFunctionget_device
()
gaussiandreamer-hash3d/threestudio/utils/misc.py:28
↓ 5 callersFunctionget_device
()
threestudio-hash3d/threestudio/utils/misc.py:29
↓ 5 callersMethodget_img_embeds
(self, x)
dreamgaussian-hash3d/guidance/zero123_utils.py:57
↓ 5 callersFunctionget_mvp_matrix
( c2w: Float[Tensor, "B 4 4"], proj_mtx: Float[Tensor, "B 4 4"] )
gaussiandreamer-hash3d/threestudio/utils/ops.py:281
↓ 5 callersFunctionget_mvp_matrix
( c2w: Float[Tensor, "B 4 4"], proj_mtx: Float[Tensor, "B 4 4"] )
threestudio-hash3d/threestudio/utils/ops.py:284
↓ 5 callersFunctionget_rays
( directions: Float[Tensor, "... 3"], c2w: Float[Tensor, "... 4 4"], keepdim=False, noise_scal
gaussiandreamer-hash3d/threestudio/utils/ops.py:219
↓ 5 callersMethodget_text_embeddings
( self, prompt: Union[str, List[str]], negative_prompt: Union[str, List[str]] )
gaussiandreamer-hash3d/threestudio/models/prompt_processors/base.py:437
↓ 5 callersMethodget_text_embeddings_perp_neg
( self, elevation: Float[Tensor, "B"], azimuth: Float[Tensor, "B"], camera_dis
gaussiandreamer-hash3d/threestudio/models/prompt_processors/base.py:80
↓ 5 callersMethodget_unconditional_conditioning
( self, batch_size, null_label=None, image_size=512 )
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddpm.py:1649
↓ 5 callersFunctionisimage
(x)
threestudio-hash3d/extern/ldm_zero123/util.py:67
↓ 5 callersFunctionlinear
Create a linear module.
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/util.py:259
↓ 5 callersFunctionload_config
(*yamls: str, cli_args: list = [], from_string=False, **kwargs)
threestudio-hash3d/threestudio/utils/config.py:104
↓ 5 callersFunctionmake_divisible
(x, divisible_by=8)
gaussiandreamer-hash3d/threestudio/utils/GAN/mobilenet.py:78
↓ 5 callersFunctionmake_divisible
(x, divisible_by=8)
threestudio-hash3d/threestudio/utils/GAN/mobilenet.py:78
↓ 5 callersMethodmode
(self)
threestudio-hash3d/extern/ldm_zero123/modules/distributions/distributions.py:20
↓ 5 callersMethodquantize
(self, x, *args, **kwargs)
threestudio-hash3d/extern/ldm_zero123/models/autoencoder.py:545
↓ 5 callersMethodrasterize
( self, pos: Float[Tensor, "B Nv 4"], tri: Integer[Tensor, "Nf 3"], resolution
threestudio-hash3d/threestudio/utils/rasterize.py:30
↓ 5 callersMethodrender
(self)
dreamgaussian-hash3d/main2.py:667
↓ 5 callersMethodrender
(self)
dreamgaussian-hash3d/main2_hash.py:724
↓ 5 callersFunctionsafe_normalize
(x, eps=1e-20)
dreamgaussian-hash3d/mesh.py:15
↓ 5 callersFunctionscale_img_hwc
(x, size, mag='bilinear', min='bilinear')
dreamgaussian-hash3d/mesh_renderer.py:26
↓ 5 callersMethodset_attn_processor
r""" Sets the attention processor to use to compute attention. Parameters: processor (`dict` of `AttentionProcessor` or o
threestudio-hash3d/DeepCache/sd/unet_2d_condition.py:619
↓ 5 callersFunctionshave_segments
Removes segments. Positive values shave the first segments, negative shave the last segments.
gaussiandreamer-hash3d/scripts/convert_zero123_to_diffusers.py:206
↓ 5 callersFunctionshave_segments
Removes segments. Positive values shave the first segments, negative shave the last segments.
threestudio-hash3d/scripts/convert_zero123_to_diffusers.py:206
↓ 4 callersMethodC
(self, value: Any)
gaussiandreamer-hash3d/threestudio/systems/base.py:88
↓ 4 callersFunctionSH2RGB
(sh)
gaussiandreamer-hash3d/gaussiansplatting/utils/sh_utils.py:117
↓ 4 callersMethod__init__
( self, in_features: int, out_features: int, rank: int = 4, network_al
dreamgaussian-hash3d/DeepCache/sd/lora.py:194
↓ 4 callersMethod__init__
( self, in_features: int, out_features: int, rank: int = 4, network_al
gaussiandreamer-hash3d/DeepCache/sd/lora.py:194
↓ 4 callersMethod__init__
( self, num_features, logdet=False, affine=True, allow_reverse_init=False )
gaussiandreamer-hash3d/threestudio/utils/GAN/discriminator.py:13
↓ 4 callersMethod__init__
(self)
gaussiandreamer-hash3d/gaussiansplatting/lpipsPyTorch/modules/networks.py:89
↓ 4 callersMethod__init__
( self, in_features: int, out_features: int, rank: int = 4, network_al
threestudio-hash3d/DeepCache/sd/lora.py:194
↓ 4 callersMethod__init__
(self, pnet_type="vgg", pnet_rand=False, use_gpu=True)
threestudio-hash3d/extern/ldm_zero123/modules/evaluate/evaluate_perceptualsim.py:230
↓ 4 callersMethod__init__
( self, num_features, logdet=False, affine=True, allow_reverse_init=False )
threestudio-hash3d/threestudio/utils/GAN/discriminator.py:13
↓ 4 callersMethod_save_rgb_image
( self, filename, img, data_format, data_range, name: Optional
gaussiandreamer-hash3d/threestudio/utils/saving.py:111
↓ 4 callersMethod_save_rgb_image
( self, filename, img, data_format, data_range, name: Optional
threestudio-hash3d/threestudio/utils/saving.py:111
↓ 4 callersFunctionadd_Gaussian_noise
(img, noise_level1=2, noise_level2=25)
threestudio-hash3d/extern/ldm_zero123/modules/image_degradation/bsrgan.py:389
↓ 4 callersFunctionadd_JPEG_noise
(img)
threestudio-hash3d/extern/ldm_zero123/modules/image_degradation/bsrgan_light.py:453
↓ 4 callersFunctionadopt_weight
(weight, global_step, threshold=0, value=0.0)
threestudio-hash3d/extern/ldm_zero123/modules/losses/vqperceptual.py:20
↓ 4 callersMethodantialias
( self, color: Float[Tensor, "B H W C"], rast: Float[Tensor, "B H W 4"], pos:
threestudio-hash3d/threestudio/utils/rasterize.py:49
↓ 4 callersMethodbackground
(self)
gaussiandreamer-hash3d/threestudio/models/renderers/base.py:62
↓ 4 callersFunctioncalculate_weights_indices
( in_length, out_length, scale, kernel, kernel_width, antialiasing )
threestudio-hash3d/extern/ldm_zero123/modules/image_degradation/utils_image.py:769
↓ 4 callersFunctionclamp
(v, T=0.0001)
threestudio-hash3d/threestudio/utils/ops.py:443
↓ 4 callersMethodcompute_hash_index
Computes the hash index for a given key. Args: key (torch.Tensor): Key tensor of the form [c1, c2, c3, t]. Retu
dreamgaussian-hash3d/guidance/utils.py:43
↓ 4 callersMethodcompute_top_k
(self, logits, labels, k, reduction="mean")
threestudio-hash3d/extern/ldm_zero123/models/diffusion/classifier.py:181
↓ 4 callersMethodcopy_to
(self, model)
threestudio-hash3d/extern/ldm_zero123/modules/ema.py:52
↓ 4 callersMethoddecode_latents
( self, latents: Float[Tensor, "B 4 H W"], latent_height: int = 64, latent_wid
gaussiandreamer-hash3d/threestudio/models/guidance/stable_diffusion_guidance_cache.py:334
↓ 4 callersMethoddecode_latents
( self, latents: Float[Tensor, "B 4 H W"], latent_height: int = 64, latent_wid
gaussiandreamer-hash3d/threestudio/models/guidance/stable_diffusion_guidance.py:170
↓ 4 callersMethoddecode_latents
( self, latents: Float[Tensor, "B 4 H W"], latent_height: int = 64, latent_wid
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_guidance_cache.py:334
↓ 4 callersFunctiondot
(x, y)
gaussiandreamer-hash3d/threestudio/utils/ops.py:15
↓ 4 callersMethodenable_attention_slicing
r""" Enable sliced attention computation. When this option is enabled, the attention module splits the input tensor in slices to compu
gaussiandreamer-hash3d/DeepCache/sd/pipeline_utils.py:1783
↓ 4 callersMethodencode
( self, x0, c, t_enc, use_original_steps=False, return_interme
threestudio-hash3d/extern/ldm_zero123/models/diffusion/ddim.py:362
↓ 4 callersMethodencode_image
(self, image)
eval_clip_sim.py:19
↓ 4 callersMethodencode_imgs
(self, imgs)
dreamgaussian-hash3d/guidance/imagedream_utils.py:221
↓ 4 callersMethodencode_text
(self, prompt)
dreamgaussian-hash3d/guidance/mvdream_utils.py:50
↓ 4 callersMethodencode_text
(self, prompt)
dreamgaussian-hash3d/guidance/imagedream_utils.py:62
↓ 4 callersMethodextract_mesh
(self, path, density_thresh=1, resolution=128, decimate_target=1e5)
dreamgaussian-hash3d/gs_renderer.py:296
↓ 4 callersMethodflush
(self)
gaussiandreamer-hash3d/gaussiansplatting/utils/general_utils.py:125
↓ 4 callersMethodforward
(self, img1, img2, mask=None)
threestudio-hash3d/extern/ldm_zero123/modules/evaluate/ssim.py:84
↓ 4 callersMethodforward_unet
( self, latents: Float[Tensor, "..."], t: Float[Tensor, "..."], encoder_hidden
gaussiandreamer-hash3d/threestudio/models/guidance/deep_floyd_guidance.py:113
↓ 4 callersMethodforward_unet
( self, unet: UNet2DConditionModel, latents: Float[Tensor, "..."], t: Int[Tens
threestudio-hash3d/threestudio/models/guidance/stable_diffusion_unified_guidance.py:284
↓ 4 callersMethodforward_unet
( self, latents: Float[Tensor, "..."], t: Float[Tensor, "..."], encoder_hidden
threestudio-hash3d/threestudio/models/guidance/deep_floyd_guidance.py:113
↓ 4 callersFunctionfov2focal
(fov, pixels)
gaussiandreamer-hash3d/gaussiansplatting/utils/graphics_utils.py:95
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
gaussiandreamer-hash3d/threestudio/data/image.py:320
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
gaussiandreamer-hash3d/threestudio/data/multiview.py:400
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
gaussiandreamer-hash3d/threestudio/data/uncond.py:551
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
gaussiandreamer-hash3d/threestudio/data/co3d.py:691
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
threestudio-hash3d/threestudio/data/image.py:331
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
threestudio-hash3d/threestudio/data/multiview.py:408
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
threestudio-hash3d/threestudio/data/uncond.py:489
↓ 4 callersMethodgeneral_loader
(self, dataset, batch_size, collate_fn=None)
threestudio-hash3d/threestudio/data/co3d.py:691
↓ 4 callersMethodgenerate
( self, image, # image tensor [1, 3, H, W] in [0, 1] elevation=0, azimuth=0,
threestudio-hash3d/threestudio/models/guidance/zero123_guidance.py:435
↓ 4 callersMethodgeometry
(self)
threestudio-hash3d/threestudio/models/renderers/base.py:54
↓ 4 callersMethodgetTrainCameras
(self, scale=1.0)
gaussiandreamer-hash3d/gaussiansplatting/scene/__init__.py:89
↓ 4 callersMethodget_last_layer
(self)
threestudio-hash3d/extern/ldm_zero123/models/autoencoder.py:286
↓ 4 callersMethodget_last_layer
(self)
threestudio-hash3d/extern/ldm_zero123/models/autoencoder.py:505
↓ 4 callersFunctionget_stats
(stats)
threestudio-hash3d/extern/ldm_zero123/modules/evaluate/torch_frechet_video_distance.py:168
↓ 4 callersMethodget_text_embeds
(self, prompts, negative_prompts)
dreamgaussian-hash3d/guidance/mvdream_utils.py:44
↓ 4 callersMethodget_trilinear_feature
( self, points: Float[Tensor, "*N Di"], grid: Float[Tensor, "1 Df G1 G2 G3"] )
gaussiandreamer-hash3d/threestudio/models/geometry/volume_grid.py:65
↓ 4 callersMethodget_trilinear_feature
( self, points: Float[Tensor, "*N Di"], grid: Float[Tensor, "1 Df G1 G2 G3"] )
threestudio-hash3d/threestudio/models/geometry/volume_grid.py:65
↓ 4 callersFunctionhash_prompt
(model: str, prompt: str)
gaussiandreamer-hash3d/threestudio/models/prompt_processors/base.py:19
↓ 4 callersFunctionhash_prompt
(model: str, prompt: str)
threestudio-hash3d/threestudio/models/prompt_processors/base.py:19
↓ 4 callersMethodinitialize
(self, input=None, num_pts=5000, radius=0.5)
dreamgaussian-hash3d/gs_renderer.py:689
↓ 4 callersMethodinterpolate_one
( self, attr: Float[Tensor, "Nv C"], rast: Float[Tensor, "B H W 4"], tri: Inte
gaussiandreamer-hash3d/threestudio/utils/rasterize.py:70
↓ 4 callersMethodinterpolate_one
( self, attr: Float[Tensor, "Nv C"], rast: Float[Tensor, "B H W 4"], tri: Inte
threestudio-hash3d/threestudio/utils/rasterize.py:70
↓ 4 callersMethodlaplacian
(self)
threestudio-hash3d/threestudio/models/mesh.py:303
↓ 4 callersMethodload_from_cache
(self, prompt)
gaussiandreamer-hash3d/threestudio/models/prompt_processors/base.py:405
↓ 4 callersMethodload_from_cache
(self, prompt)
threestudio-hash3d/threestudio/models/prompt_processors/base.py:411
↓ 4 callersMethodmaterial
(self)
gaussiandreamer-hash3d/threestudio/models/renderers/base.py:58
↓ 4 callersFunctionnoise_like
(shape, device, repeat=False)
threestudio-hash3d/extern/ldm_zero123/modules/diffusionmodules/util.py:291
↓ 4 callersMethodorbit
(self, dx, dy)
dreamgaussian-hash3d/cam_utils.py:134
↓ 4 callersMethodpan
(self, dx, dy, dz=0)
dreamgaussian-hash3d/cam_utils.py:144
↓ 4 callersFunctionparse_optimizer
(config, model)
threestudio-hash3d/threestudio/systems/utils.py:34
↓ 4 callersMethodpreprocess
(self, x_img)
threestudio-hash3d/extern/ldm_zero123/guidance.py:16
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