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Functions685 in github.com/3DAnimals/3DAnimals

⨍ Functions 685◇ Types & classes 122

↓ 1 callersMethodset_train_post_load

model/models/AnimalModel.py:173

↓ 1 callersFunctionshade

( gb_pos, gb_geometric_normal, gb_normal, gb_tangent, gb_tex_pos,

model/render/render.py:30

↓ 1 callersMethodsort_edges

(self, edges_ex2)

model/geometry/dmtet.py:59

↓ 1 callersMethodtest

Perform testing.

model/Trainer.py:129

↓ 1 callersFunctiontest_cubemap

model/render/renderutils/tests/test_cubemap.py:25

↓ 1 callersFunctiontest_frostbite

model/render/renderutils/tests/test_bsdf.py:179

↓ 1 callersFunctiontest_lambda_ggx

model/render/renderutils/tests/test_bsdf.py:109

↓ 1 callersFunctiontest_lambert

model/render/renderutils/tests/test_bsdf.py:157

↓ 1 callersFunctiontest_masking_smith

model/render/renderutils/tests/test_bsdf.py:132

↓ 1 callersFunctiontest_ndf_ggx

model/render/renderutils/tests/test_bsdf.py:85

↓ 1 callersFunctiontest_normal

model/render/renderutils/tests/test_bsdf.py:25

↓ 1 callersFunctiontest_pbr_specular

model/render/renderutils/tests/test_bsdf.py:207

↓ 1 callersFunctiontest_schlick

model/render/renderutils/tests/test_bsdf.py:59

↓ 1 callersFunctiontest_xfm_points

model/render/renderutils/tests/test_mesh.py:38

↓ 1 callersFunctiontest_xfm_vectors

model/render/renderutils/tests/test_mesh.py:58

↓ 1 callersFunctiontransfer_keypoints

(source_verts, source_verts_visibility, target_verts, source_kp)

evaluation/evaluate.py:461

↓ 1 callersFunctionuncrop_keypoints_with_box

kp are in [-1, 1] range

evaluation/evaluate.py:207

↓ 1 callersFunctionupdate_body_kinematic_chain

(kinematic_chain, leg_kinematic_chain, body_bone_idx, leg_bone_idxs, attach_legs_to_body=True)

model/geometry/skinning.py:40

↓ 1 callersFunctionupdate_config

run_4d_reconstruction.py:34

↓ 1 callersMethodupdate_metric

(self, name, keypoints_pred, source_visible)

evaluation/evaluate.py:438

↓ 1 callersFunctionvalidate_all_to_device

(batch, device)

visualization/visualize_results.py:604

↓ 1 callersFunctionvalidate_all_to_device

(batch, device)

visualization/visualize_results_fauna.py:637

↓ 1 callersFunctionvalidate_tensor_to_device

visualization/visualize_results.py:598

↓ 1 callersFunctionvalidate_tensor_to_device

visualization/visualize_results_fauna.py:631

↓ 1 callersFunctionvalidate_tensor_to_device

(x, device=None)

model/utils/misc.py:308

↓ 1 callersFunctionvisualize

( data_dir_test, predictions_test_dir, vis_dir, source_name, target_name, source_kp,

evaluation/evaluate.py:240

↓ 1 callersFunctionwrite_obj

(folder, fname, mesh, idx, save_material=True, feat=None, resolution=[256, 256])

model/render/obj.py:128

FunctionPYBIND11_MODULE

model/render/renderutils/c_src/torch_bindings.cpp:1034

(self, pos_nx3, sdf_n, tet_fx4)

model/geometry/dmtet.py:104

Method__contains__

model/render/material.py:33

Method__delitem__

model/render/material.py:43

Method__getitem__

model/dataset/SequenceDataset.py:64

Method__getitem__

model/dataset/SequenceDataset.py:114

Method__getitem__

model/dataset/ImageDataset.py:73

Method__getitem__

model/dataset/FaunaDataset.py:160

Method__getitem__

model/dataset/SingleSequenceDataset.py:60

Method__getitem__

model/dataset/SingleSequenceDataset.py:113

Method__getitem__

model/render/material.py:36

(self, direction, amb, diff)

visualization/visualize_results.py:60

(self, direction, amb, diff)

visualization/visualize_results_fauna.py:61

(self, cfg: TrainerConfig, model)

model/Trainer.py:54

model/utils/meters.py:10

(self, inertia=0.9)

model/utils/meters.py:28

model/utils/meters.py:49

model/utils/meters.py:99

(self, frame_dim=0, smooth_type=None, loss_type="l2")

model/utils/smooth_loss.py:6

(self, project, config=None, local_dir=None, **kwargs)

model/utils/wandb_writer.py:13

(self, cin, cout, nf=256, activation=None)

model/networks/encoders.py:70

(self, cout, pretrained=False)

model/networks/encoders.py:93

(self, cout, pretrained=False)

model/networks/encoders.py:110

(self, pretrained=True)

model/networks/encoders.py:120

(self, cout, which_vit='dino_vits8', pretrained=False, frozen=False, final_layer_type='none')

model/networks/encoders.py:149

Positional Embedding implementation (adapted from Pytorch3D). Given an input tensor `x` of shape [minibatch, ... , dim], the

model/networks/HarmonicEmbedding.py:8

(self, cin, cout, num_layers, nf=256,

model/networks/MLPs.py:35

(self, cin, cout, num_layers, nf=256,

model/networks/MLPs.py:105

(self, cin, cout, num_layers, nf=256, dropout=0, activation=None)

model/networks/MLPs.py:173

(self, in_features: int, out_features: int, bias: bool = True, device=None, dtype=None)

model/networks/MLPs.py:211

(self, in_dim=1, out_dim=1, n_feat=512, img_size=256, last_bias=False)

model/networks/discriminator_architecture.py:16

(self, net_type, feat_dim, posenc_dim, num_layers, nf, n_harmonic_functions=0, embedder_scalar=1, activation=N

model/networks/ArticulationNetwork.py:11

(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0.)

model/networks/ArticulationNetwork.py:72

(self, drop_prob=None)

model/networks/ArticulationNetwork.py:131

(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., dr

model/networks/ArticulationNetwork.py:140

(self, d_model, dropout=0.1, max_len=5000)

model/networks/MotionVAE.py:9

( self, njoints, nfeats, latent_dim=256, ff_size=1024, num_layers=4, num_heads=4, dropout=0.1, activat

model/networks/MotionVAE.py:77

( self, njoints, feat_dim, pos_dim, n_harmonic_functions=0, harmonic_omega0=1, latent_dim=256, z_token

model/networks/MotionVAE.py:131

(self, root, num_frames=2, skip_beginning=4, skip_end=4, min_seq_len=10, in_image_size=256, out_image_size=256

model/dataset/SequenceDataset.py:69

(self, root, in_image_size=256, out_image_size=256, shuffle=False, load_background=False, random_xflip=False,

model/dataset/ImageDataset.py:13

(self, root, in_image_size=256, out_image_size=256, shuffle=False, load_background=False, random_xflip=False,

model/dataset/FaunaDataset.py:42

(self, root, num_frames=2, skip_beginning=False, skip_end=False, in_image_size=256, load_keypoint=False,

model/dataset/SingleSequenceDataset.py:65

(self, grid_res, spatial_scale, num_layers=None, hidden_size=None, embedder_freq=None, embed_concat_pts=True,

model/geometry/dmtet.py:176

(self, mlp_in, mlp_layers, mlp_hidden_size, intensity_min_max=None)

model/render/light.py:170

(self, mat_dict)

model/render/material.py:26

(self, init, min_max=None)

model/render/texture.py:43

(self, v_pos=None, t_pos_idx=None, v_nrm=None,

model/render/mesh.py:22

(self, cfg: MagicPonyConfig)

model/models/MagicPony.py:14

(self, cfg: FaunaConfig)

model/models/Fauna.py:36

(self, cfg: AnimalModelConfig)

model/models/AnimalModel.py:100

(self, cfg: PonymationConfig)

model/models/Ponymation.py:20

(self, cfg: FaunaConfig)

model/models/Fauna4D.py:15

(self, cfg: FaunaInstancePredictorConfig)

model/predictors/InstancePredictorFauna.py:30

(self, cfg: BasePredictorBankConfig)

model/predictors/BasePredictorBank.py:46

(self, cfg: InstancePredictorConfig)

model/predictors/InstancePredictorBase.py:121

(self, cfg: InstancePredictorMotionVAEConfig)

model/predictors/InstancePredictorMotionVAE.py:29

(self, cfg: BasePredictorConfig)

model/predictors/BasePredictorBase.py:45

(self, cfg: BasePredictorBankConfig)

model/predictors/BasePredictorFauna4D.py:4

(self, cfg: FaunaInstancePredictorConfig)

model/predictors/InstancePredictorFauna4D.py:13

( self, data_dir, predictions_test_dir, vertices_postifx="_2d_projection_uv.tx

evaluation/evaluate.py:328

(self, acsm_annotations_root, pascal_category, **kwargs)

evaluation/evaluate.py:402

model/dataset/SequenceDataset.py:61

model/dataset/ImageDataset.py:67

model/dataset/FaunaDataset.py:157

model/dataset/SingleSequenceDataset.py:57

model/render/mesh.py:46

Method__setitem__

(self, key, val)

model/render/material.py:39

Method__setitem__

(self, keys, values)

model/predictors/InstancePredictorFauna4D.py:158

model/utils/meters.py:81

model/utils/meters.py:126

Function_fresnel_shlick

(f0, f90, cosTheta, use_python=False)

model/render/renderutils/ops.py:101

(model, input, output)

model/networks/encoders.py:186

model/geometry/dmtet.py:86

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