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Functions239 in github.com/AiuniAI/Unique3D

⨍ Functions 239◇ Types & classes 26
↓ 7 callersFunctionget_cameras_list
(azim_list, device, focal=2/1.35, dist=1.1)
scripts/project_mesh.py:313
↓ 7 callersFunctionrecursive_add_processors
(name: str, module: torch.nn.Module)
custum_3d_diffusion/custum_modules/attention_processors.py:161
↓ 5 callersFunctionload_config
(fields, config, extras=None)
custum_3d_diffusion/trainings/utils.py:9
↓ 5 callersFunctionmake_image_grid
(images, rows=None, cols=None, resize=None)
app/utils.py:87
↓ 5 callersMethodregister_to_config
(self, **kwargs)
custum_3d_diffusion/custum_modules/unifield_processor.py:173
↓ 5 callersMethodrender
(self, vertices: torch.Tensor, #V,3 float normals: torch.Tensor, #V,3 float in [-1,
mesh_reconstruction/render.py:37
↓ 5 callersFunctionrgba_to_rgb
(rgba: Image.Image, bkgd="WHITE")
app/utils.py:47
↓ 5 callersFunctionsimple_remove
Only works for normal
app/utils.py:29
↓ 4 callersFunctioncalc_edges
returns Tuple of - edges E,2 long, 0 for unused, lower vertex index first - face_to_edge F,3 long - (optional) edge_to_face shape=E,[
mesh_reconstruction/remesh.py:25
↓ 4 callersMethoddo_crosspond_attention
(self, hidden_states: torch.FloatTensor, other_states: torch.FloatTensor)
custum_3d_diffusion/custum_modules/attention_processors.py:60
↓ 4 callersFunctionintegrate_gradient_field
( gradient_field: np.ndarray, axis: int, mask: np.ndarray )
scripts/normal_to_height_map.py:29
↓ 4 callersFunctionrun_sr_fast
(source_pils, scale=4)
scripts/refine_lr_to_sr.py:31
↓ 4 callersFunctionsplit_image
inverse function of make_image_grid
app/utils.py:58
↓ 4 callersMethodstep
(self)
mesh_reconstruction/opt.py:126
↓ 3 callersMethod__init__
( self, chained_proc, enabled=False, name=None, mode='extract',
custum_3d_diffusion/custum_modules/attention_processors.py:21
↓ 3 callersFunctioncalc_vertex_normals
( vertices:torch.Tensor, #V,3 first vertex may be unreferenced faces:torch.Tensor, #F,3 long,
mesh_reconstruction/remesh.py:93
↓ 3 callersMethodconstruct_pipeline
(self, shared_modules, unet)
custum_3d_diffusion/trainings/base.py:132
↓ 3 callersFunctionlerp_unbiased
lerp with adam's bias correction
mesh_reconstruction/opt.py:52
↓ 3 callersFunctionmake_star_cameras_orthographic
(az_count,pol_count,distance:float=10.,r=None,image_size=[512,512],device='cuda')
mesh_reconstruction/func.py:108
↓ 3 callersFunctionmultiview_color_projection
Projects color from a given image onto a 3D mesh. Args: meshes (pytorch3d.structures.Meshes): The 3D mesh object, only one mesh.
scripts/project_mesh.py:224
↓ 3 callersFunctionrotate
(matrix: np.ndarray, angle: float)
scripts/normal_to_height_map.py:66
↓ 3 callersFunctionto_py3d_mesh
(vertices, faces, normals=None)
scripts/utils.py:84
↓ 3 callersMethodunet_update
(self)
custum_3d_diffusion/trainings/base.py:78
↓ 2 callersMethod_split_vertices_etc
(self)
mesh_reconstruction/opt.py:112
↓ 2 callersFunctionadd_extra_processor
(model: torch.nn.Module, enable_filter=lambda x:True, **kwargs)
custum_3d_diffusion/custum_modules/attention_processors.py:156
↓ 2 callersMethodbatched_validation_forward
(self, pipeline, **pipeline_call_kwargs)
custum_3d_diffusion/trainings/base.py:143
↓ 2 callersFunctionbuild_mesh
(normal_pil, rgb_pil, is_back=False, clamp_min=-1, scale=0.3, init_type="std", offset=0)
scripts/mesh_init.py:82
↓ 2 callersFunctioncalc_edge_length
( vertices:torch.Tensor, #V,3 first may be dummy edges:torch.Tensor, #E,2 long, lower vertex i
mesh_reconstruction/remesh.py:65
↓ 2 callersFunctioncalc_face_normals
n | c0 corners ordered counterclockwise when / \ looking onto surface (in neg normal direction) c1--
mesh_reconstruction/remesh.py:74
↓ 2 callersFunctionchange_switch
(model: torch.nn.Module, switch_name="default_switch", enabled_proc="default")
custum_3d_diffusion/custum_modules/attention_processors.py:335
↓ 2 callersMethodchoose_module
(self, enabled_proc)
custum_3d_diffusion/custum_modules/attention_processors.py:298
↓ 2 callersFunctionconvert
(a)
mesh_reconstruction/func.py:8
↓ 2 callersFunctionfrom_py3d_mesh
(mesh)
scripts/utils.py:95
↓ 2 callersFunctiongeo_reconstruct
(rgb_pils, normal_pils, front_pil, do_refine=False, predict_normal=True, expansion_weight=0.1, init_type="std"
scripts/multiview_inference.py:63
↓ 2 callersFunctionget_HW
(resolution)
custum_3d_diffusion/trainings/image2mvimage_trainer.py:14
↓ 2 callersFunctionget_HW
(resolution)
custum_3d_diffusion/trainings/image2image_trainer.py:11
↓ 2 callersMethodinit_models
(self)
app/all_models.py:19
↓ 2 callersFunctioninit_target
(img_pils, new_bkgd=(0., 0., 0.), device="cuda")
scripts/utils.py:302
↓ 2 callersMethodis_train_finished
(self, current_step)
custum_3d_diffusion/trainings/base.py:84
↓ 2 callersFunctionload_controlnet
(controlnet_path, torch_dtype=torch.float16)
scripts/sd_model_zoo.py:55
↓ 2 callersFunctionload_pipeline
(config_path, ckpt_path, pipeline_filter=lambda x: True, weight_dtype = torch.bfloat16)
app/custom_models/utils.py:51
↓ 2 callersFunctionmeshlab_mesh_to_py3dmesh
(mesh: pymeshlab.Mesh)
scripts/utils.py:58
↓ 2 callersFunctionmodel_from_ckpt_or_pretrained
(ckpt_or_pretrained, model_cls, original_config_file='ckpt/v1-inference.yaml', torch_dtype=torch.float16, **kw
scripts/sd_model_zoo.py:32
↓ 2 callersMethodpipeline_forward
For inference time forward.
custum_3d_diffusion/trainings/base.py:136
↓ 2 callersMethodpost_process
(self)
scripts/upsampler.py:147
↓ 2 callersMethodpre_process
Pre-process, such as pre-pad and mod pad, so that the images can be divisible
scripts/upsampler.py:53
↓ 2 callersMethodprocess
(self)
scripts/upsampler.py:78
↓ 2 callersFunctionreconstruct_stage1
(pils: List[Image.Image], steps=100, vertices=None, faces=None, start_edge_len=0.15, end_edge_len=0.005, decay
mesh_reconstruction/recon.py:12
↓ 2 callersMethodremesh
(self, flip:bool=True, poisson=False)
mesh_reconstruction/opt.py:181
↓ 2 callersFunctionrotate_normalmap_by_angle
rotate along y-axis normal_map: np.array, shape=(H, W, 3) in [-1, 1] angle: float, in degree
scripts/utils.py:98
↓ 2 callersFunctionrun_mvprediction
(input_image: Image.Image, remove_bg=True, guidance_scale=1.5, seed=1145)
app/custom_models/mvimg_prediction.py:33
↓ 2 callersFunctionsave_glb_and_video
(save_mesh_prefix: str, meshes: Meshes, with_timestamp=True, dist=3.5, azim_offset=180, resolution=512, fov_in
scripts/utils.py:243
↓ 2 callersMethodset_class_labels
(self, class_labels: torch.Tensor)
custum_3d_diffusion/custum_modules/unifield_processor.py:135
↓ 2 callersFunctionswitch_extra_processor
(model, enable_filter=lambda x:True)
custum_3d_diffusion/custum_modules/attention_processors.py:182
↓ 2 callersFunctionswitch_multiview_processor
(model, enable_filter=lambda x:True)
custum_3d_diffusion/custum_modules/attention_processors.py:256
↓ 2 callersFunctiontensor
(*args, **kwargs)
scripts/project_mesh.py:62
↓ 2 callersFunctiontensor
(*args, **kwargs)
mesh_reconstruction/render.py:9
↓ 2 callersMethodtile_process
It will first crop input images to tiles, and then process each tile. Finally, all the processed tiles are merged into one images. Mo
scripts/upsampler.py:82
↓ 2 callersMethodupdate_config
(self, attn_config: AttnConfig)
custum_3d_diffusion/custum_modules/unifield_processor.py:85
↓ 2 callersMethodzero_grad
(self)
mesh_reconstruction/opt.py:122
↓ 1 callersMethod_encode_image
(self, image, device, num_images_per_prompt, do_classifier_free_guidance)
custum_3d_diffusion/custum_pipeline/unifield_pipeline_img2mvimg.py:74
↓ 1 callersMethod_encode_image
(self, image, device, num_images_per_prompt, do_classifier_free_guidance)
custum_3d_diffusion/custum_pipeline/unifield_pipeline_img2img.py:74
↓ 1 callersFunction_orthographic
(r, device, l=None, t=None, b=None, n=1.0, f=50.0, flip_y=True)
mesh_reconstruction/func.py:63
↓ 1 callersFunction_projection
see https://blog.csdn.net/wodownload2/article/details/85069240/
mesh_reconstruction/func.py:43
↓ 1 callersFunction_translation
(x, y, z, device)
mesh_reconstruction/func.py:37
↓ 1 callersFunction_warmup
(glctx, device=None)
scripts/project_mesh.py:59
↓ 1 callersFunction_warmup
(glctx, device=None)
mesh_reconstruction/render.py:6
↓ 1 callersFunctionadd_multiview_processor
(model: torch.nn.Module, enable_filter=lambda x:True, **kwargs)
custum_3d_diffusion/custum_modules/attention_processors.py:233
↓ 1 callersFunctionadd_switch
(model: torch.nn.Module, module_filter=lambda x:True, switch_dict_fn=lambda x: {"default": x}, switch_name="de
custum_3d_diffusion/custum_modules/attention_processors.py:310
↓ 1 callersFunctionalign_with_alpha_bbox
(source_img, target_img, final_size=1024)
scripts/project_mesh.py:337
↓ 1 callersFunctioncalc_face_collapses
( vertices:torch.Tensor, #V,3 first unused faces:torch.Tensor, #F,3 long, 0 for unused
mesh_reconstruction/remesh.py:246
↓ 1 callersFunctioncalc_face_ref_normals
calculate reference normals for face flip detection
mesh_reconstruction/remesh.py:109
↓ 1 callersFunctioncalc_w_over_h
(normal_pil)
scripts/mesh_init.py:66
↓ 1 callersFunctioncalculate_gradients
( normals: np.ndarray, mask: np.ndarray )
scripts/normal_to_height_map.py:10
↓ 1 callersFunctioncalculate_heights
( left_gradients: np.ndarray, top_gradients, mask: np.ndarray )
scripts/normal_to_height_map.py:48
↓ 1 callersFunctioncentered_crop
(image: np.ndarray, target_resolution: Tuple[int, int])
scripts/normal_to_height_map.py:100
↓ 1 callersFunctionchange_rgba_bg
(rgba: Image.Image, bkgd="WHITE")
app/utils.py:53
↓ 1 callersFunctioncollapse_edges
( vertices:torch.Tensor, #V,3 first unused faces:torch.Tensor, #F,3 long 0 for unused
mesh_reconstruction/remesh.py:202
↓ 1 callersFunctioncombine_heights
(*heights: np.ndarray)
scripts/normal_to_height_map.py:62
↓ 1 callersFunctioncomplete_unseen_vertex_color
meshes: the mesh with vertex color to be completed. valid_index: the index of the valid vertices, where valid means colors are fixed. [V, 1]
scripts/project_mesh.py:176
↓ 1 callersFunctionconcept_to_multiview_ui
(concurrency_id="wkl")
app/gradio_3dgen_steps.py:19
↓ 1 callersMethodconfigure
(self)
custum_3d_diffusion/trainings/base.py:98
↓ 1 callersFunctionconstruct_pix2pix_attention
(hidden_states_dim, norm_type="none")
custum_3d_diffusion/custum_modules/attention_processors.py:5
↓ 1 callersFunctiondepth_and_color_to_mesh
(rgb_BCHW, pred_HWC, valid_HWC=None, is_back=False)
scripts/mesh_init.py:26
↓ 1 callersFunctiondo_rotate
(rgba_normal, angle)
scripts/utils.py:142
↓ 1 callersMethoddo_validation
( self, shared_modules, unet, global_step, )
custum_3d_diffusion/trainings/base.py:146
↓ 1 callersMethodenable_xformers_memory_efficient_attention
(self)
custum_3d_diffusion/custum_modules/unifield_processor.py:144
↓ 1 callersMethodencode_latents
(self, image: Image.Image, device, dtype, height, width)
custum_3d_diffusion/custum_pipeline/unifield_pipeline_img2mvimg.py:65
↓ 1 callersMethodencode_latents
(self, image, device, dtype, height, width)
custum_3d_diffusion/custum_pipeline/unifield_pipeline_img2img.py:62
↓ 1 callersMethodenhance
(self, img, outscale=None, alpha_upsampler='realesrgan')
scripts/upsampler.py:159
↓ 1 callersFunctionerode_alpha
(img_list)
scripts/multiview_inference.py:50
↓ 1 callersFunctionestimate_height_map
( normal_map: np.ndarray, mask: Union[np.ndarray, None] = None, height_divisor: float = 1, tar
scripts/normal_to_height_map.py:167
↓ 1 callersFunctionexpand2square
(pil_img, background_color)
scripts/utils.py:268
↓ 1 callersFunctionfast_geo
(front_normal: Image.Image, back_normal: Image.Image, side_normal: Image.Image, clamp=0., init_type="std")
scripts/multiview_inference.py:16
↓ 1 callersFunctionfix_border_with_pymeshlab_fast
(meshes: Meshes, poissson_depth=6, simplification=0)
scripts/mesh_init.py:124
↓ 1 callersFunctionfix_vert_color_glb
(mesh_path)
scripts/utils.py:199
↓ 1 callersFunctionflip_edges
( vertices:torch.Tensor, #V,3 first unused faces:torch.Tensor, #F,3 long, first must be 0, 0 f
mesh_reconstruction/remesh.py:291
↓ 1 callersFunctionget_2view_cameras
(device, focal=2/1.35)
scripts/project_mesh.py:331
↓ 1 callersFunctionget_4view_cameras
(device, focal=2/1.35)
scripts/project_mesh.py:328
↓ 1 callersFunctionget_6view_cameras
(device, focal=2/1.35)
scripts/project_mesh.py:325
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