MCPcopy Create free account

hub / github.com/MyNiuuu/AniCrafter / functions

Functions5,947 in github.com/MyNiuuu/AniCrafter

⨍ Functions 5,947◇ Types & classes 1,261↳ Endpoints 36
↓ 7 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vit_moe.py:62
↓ 7 callersMethod__init__
(self, in_channels, stem_channels, out_channels,
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/litehrnet.py:225
↓ 7 callersMethod__init__
(self, use_target_weight=False, loss_weight=1.)
engine/pose_estimation/third-party/ViTPose/mmpose/models/losses/regression_loss.py:243
↓ 7 callersMethod__init__
(self)
engine/BiRefNet/loss.py:43
↓ 7 callersFunction_prepare_data
(pred: np.ndarray, gt: np.ndarray)
engine/BiRefNet/evaluation/metrics.py:131
↓ 7 callersMethod_report_metric
Keypoint evaluation. Args: res_file (str): Json file stored prediction results. metrics (str | list[str]): Metric to
engine/pose_estimation/third-party/ViTPose/mmpose/datasets/datasets/hand/interhand3d_dataset.py:374
↓ 7 callersFunctionbatch_rigid_transform
Applies a batch of rigid transformations to the joints Parameters ---------- rot_mats : torch.tensor BxNx3x3 Tensor of rotat
LHM/models/rendering/smplx/smplx/lbs.py:362
↓ 7 callersFunctionbuild_dataloader
Build PyTorch DataLoader. In distributed training, each GPU/process has a dataloader. In non-distributed training, there is only one dataload
engine/pose_estimation/third-party/ViTPose/mmpose/datasets/builder.py:90
↓ 7 callersFunctionbuild_optimizers
Build multiple optimizers from configs. If `cfgs` contains several dicts for optimizers, then a dict for each constructed optimizers will be
engine/pose_estimation/third-party/ViTPose/mmpose/core/optimizer/builder.py:8
↓ 7 callersFunctionchannel_shuffle
Channel Shuffle operation. This function enables cross-group information flow for multiple groups convolution layers. Args: x (T
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/utils/channel_shuffle.py:5
↓ 7 callersMethodcreate_camera
(self, R=None, T=None)
engine/pose_estimation/pose_utils/render.py:152
↓ 7 callersFunctiondigit_version
(version_str)
engine/pose_estimation/third-party/ViTPose/mmpose/__init__.py:7
↓ 7 callersMethodencode_prompt
(self, prompt, clip_skip=1, positive=True)
diffsynth/pipelines/sd_image.py:81
↓ 7 callersFunctionflow_warp
Warp an image or a feature map with optical flow. Args: x (Tensor): Tensor with size (n, c, h, w). flow (Tensor): Tensor with s
ProPainter/model/modules/flow_loss_utils.py:6
↓ 7 callersFunctionget_affine_transform
Get the affine transform matrix, given the center/scale/rot/output_size. Args: center (np.ndarray[2, ]): Center of the bounding box (x, y
engine/pose_estimation/third-party/ViTPose/mmpose/core/post_processing/post_transforms.py:197
↓ 7 callersFunctionget_expansion
Get the expansion of a residual block. The block expansion will be obtained by the following order: 1. If ``expansion`` is given, just retur
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vipnas_resnet.py:175
↓ 7 callersFunctioninference_bottom_up_pose_model
Inference a single image with a bottom-up pose model. Note: - num_people: P - num_keypoints: K - bbox height: H -
engine/pose_estimation/third-party/ViTPose/mmpose/apis/inference.py:553
↓ 7 callersMethodinit_weights
Initialize model weights.
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vipnas_resnet.py:548
↓ 7 callersMethodinit_weights
(self, pretrained=None)
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vipnas_mbv3.py:137
↓ 7 callersFunctioninit_weights_on_device
(device = torch.device("meta"), include_buffers :bool = False)
diffsynth/models/utils.py:7
↓ 7 callersFunctionkeypoints_from_heatmaps
Get final keypoint predictions from heatmaps and transform them back to the image. Note: - batch size: N - num keypoints: K
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/top_down_eval.py:474
↓ 7 callersMethodname
(self)
LHM/models/rendering/smplx/smplx/body_models.py:295
↓ 7 callersMethodpatchify
(self, hidden_states)
diffsynth/models/flux_dit.py:295
↓ 7 callersMethodregister_input_buffer
Register an input buffer, so that Node can automatically check if data is ready, fetch data from the buffers and format the inputs to
engine/pose_estimation/third-party/ViTPose/tools/webcam/webcam_apis/nodes/node.py:119
↓ 7 callersMethodstep
(self)
LHM/utils/profiler.py:29
↓ 7 callersMethodtiled_forward
(self, hidden_states, timestep, prompt_emb, pooled_prompt_emb, tile_size=128, tile_stride=64)
diffsynth/models/sd3_dit.py:339
↓ 7 callersMethodtrain
(self, mode=True)
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vipnas_mbv3.py:173
↓ 7 callersMethodtranspose_for_scores
(self, x)
diffsynth/extensions/ImageQualityMetric/BLIP/med.py:130
↓ 7 callersMethodunpatchify
(self, hidden_states, height, width)
diffsynth/models/cog_dit.py:230
↓ 6 callersMethod__init__
( self, in_channels: int, out_channels: int, kernel_size: int = 3, str
diffsynth/models/cog_vae.py:58
↓ 6 callersMethod__init__
(self, add_positional_conv=None)
diffsynth/models/svd_unet.py:239
↓ 6 callersMethod__init__
( self, patch_size=(2, 2), in_chans=4, embed_dim=1408, bias=True,
diffsynth/models/hunyuan_dit.py:177
↓ 6 callersMethod__init__
(self, input_channel, output_channel, kernel_size=3,
ProPainter/model/propainter.py:236
↓ 6 callersMethod__init__
(self, hidden_dim=128, input_dim=192+128)
ProPainter/RAFT/update.py:17
↓ 6 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vit.py:62
↓ 6 callersMethod__init__
(self, in_channels, out_channels, num_steps=4,
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/rsn.py:35
↓ 6 callersMethod__init__
(self, unit_channels=256, num_stages=4, num_units=4,
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/mspn.py:421
↓ 6 callersMethod__init__
( self, in_features, hidden_features=None, out_features=None, act_laye
engine/BiRefNet/models/backbones/swin_v1.py:23
↓ 6 callersFunction_make_dinov2_model_name
(arch_name: str, patch_size: int, num_register_tokens: int = 0)
LHM/models/encoders/dinov2/hub/utils.py:17
↓ 6 callersFunction_make_dinov2_model_name
(arch_name: str, patch_size: int, num_register_tokens: int = 0)
engine/pose_estimation/dinov2/dinov2/hub/utils.py:17
↓ 6 callersFunction_to_tuple
(x, dim=2)
diffsynth/models/hunyuan_video_dit.py:11
↓ 6 callersMethodadd_summary
Add tensorboard summary.
ProPainter/core/trainer.py:197
↓ 6 callersFunctionaffine_transform
Apply an affine transformation to the points. Args: pt (np.ndarray): a 2 dimensional point to be transformed trans_mat (np.ndarra
engine/pose_estimation/third-party/ViTPose/mmpose/core/post_processing/post_transforms.py:255
↓ 6 callersFunctionaggregate_stage_flip
Inference the model to get multi-stage outputs (heatmaps & tags), and resize them to base sizes. Args: feature_maps (list[Tensor]): f
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/bottom_up_eval.py:165
↓ 6 callersFunctionattention
(q, k, v)
diffsynth/models/hunyuan_video_dit.py:387
↓ 6 callersFunctionbatch_rodrigues
Calculates the rotation matrices for a batch of rotation vectors Parameters ---------- rot_vecs: torch.tensor Nx3
LHM/models/rendering/smplx/transfer_model/utils/pose_utils.py:62
↓ 6 callersMethodbuild_remapping_table
(self, frames_guide, frames_style, patch_match_engine, batch_size, desc="")
diffsynth/extensions/FastBlend/runners/fast.py:34
↓ 6 callersFunctioncheck_is_instance
(model, module_class)
diffsynth/models/wan_video_vae.py:11
↓ 6 callersMethodconstrain_to_multiple_of
(self, x, min_val=0, max_val=None)
LHM/models/encoders/dpt_util/transform.py:50
↓ 6 callersMethoddecode
(self, z, scale)
diffsynth/models/wan_video_vae.py:552
↓ 6 callersMethoddecode_video
(self, latents, tiled=False, tile_size=64, tile_stride=32)
diffsynth/pipelines/sd_video.py:125
↓ 6 callersMethodencode_image
(self, image, num_frames, height, width)
diffsynth/pipelines/wan_video.py:156
↓ 6 callersMethodestimate_nnf
(self, source_guide, target_guide, source_style)
diffsynth/extensions/FastBlend/patch_match.py:282
↓ 6 callersFunctionflow_to_image
Converts a flow to an RGB image. Args: flow (Tensor): Flow of shape (N, 2, H, W) or (2, H, W) and dtype torch.float. Returns:
ProPainter/RAFT/utils/flow_viz_pt.py:6
↓ 6 callersMethodforward_bidirect_flow
Args: masked_flows_bi: [masked_flows_f, masked_flows_b] | (b t-1 2 h w), (b t-1 2 h w) masks: b t 1 h w
ProPainter/model/recurrent_flow_completion.py:312
↓ 6 callersMethodfrom_model_manager
(model_manager: ModelManager)
diffsynth/prompters/omost.py:259
↓ 6 callersMethodgenerate
( self, image, text=None, seq_len=30, max_seq_len=77, temperat
diffsynth/extensions/ImageQualityMetric/open_clip/coca_model.py:167
↓ 6 callersFunctionis_norm
Check if is one of the norms.
engine/pose_estimation/third-party/ViTPose/tests/test_backbones/test_shufflenet_v2.py:18
↓ 6 callersFunctionkeypoint_3d_pck
Calculate the Percentage of Correct Keypoints (3DPCK) w. or w/o rigid alignment. Paper ref: `Monocular 3D Human Pose Estimation In The Wild U
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/pose3d_eval.py:58
↓ 6 callersFunctionkeypoint_epe
Calculate the end-point error. Note: - batch_size: N - num_keypoints: K Args: pred (np.ndarray[N, K, 2]): Predicted
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/top_down_eval.py:273
↓ 6 callersFunctionlength_sq
(x)
ProPainter/model/modules/flow_loss_utils.py:62
↓ 6 callersFunctionmake_divisible
Make divisible function. This function rounds the channel number down to the nearest value that can be divisible by the divisor. Args:
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/utils/make_divisible.py:2
↓ 6 callersFunctionmodel_fn_wan_video
( dit: WanModel, x: torch.Tensor, timestep: torch.Tensor, context: torch.Tensor, clip_feat
diffsynth/pipelines/wan_video_v2v_combine.py:89
↓ 6 callersMethodprocess_window_sum
(self, frames_guide, blending_table, patch_match_engine, window_size, batch_size, desc="")
diffsynth/extensions/FastBlend/runners/fast.py:77
↓ 6 callersMethodregister_event
Register an event. All events used in the node need to be registered in __init__(). If a callable handler is given, a thread will be create
engine/pose_estimation/third-party/ViTPose/tools/webcam/webcam_apis/nodes/node.py:163
↓ 6 callersMethodregister_output_buffer
Register one or multiple output buffers, so that the Node can automatically send the output of the `process` method to these buffers.
engine/pose_estimation/third-party/ViTPose/tools/webcam/webcam_apis/nodes/node.py:145
↓ 6 callersMethodremapping_table_to_blending_table
(self, table)
diffsynth/extensions/FastBlend/runners/fast.py:56
↓ 6 callersFunctionresize_image_keepaspect_np
similar to ImageOps.contain(img_pil, (img_size, img_size)) # keep the same aspect ratio
LHM/runners/infer/utils.py:101
↓ 6 callersMethodrun
(self, frames_guide, frames_style, batch_size, window_size, ebsynth_config)
diffsynth/extensions/FastBlend/__init__.py:26
↓ 6 callersFunctionsearch_for_images
(folder)
diffsynth/extensions/FastBlend/data.py:65
↓ 6 callersMethodset
(self, event_name: str = None, is_keyboard: bool = False)
engine/pose_estimation/third-party/ViTPose/tools/webcam/webcam_apis/utils/event.py:20
↓ 6 callersFunctionsetup_multi_processes
Setup multi-processing environment variables.
engine/pose_estimation/third-party/ViTPose/mmpose/utils/setup_env.py:10
↓ 6 callersMethodstate_dict_converter
()
diffsynth/models/sd3_dit.py:381
↓ 6 callersMethodtrain
Convert the model into training mode.
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/vipnas_resnet.py:581
↓ 6 callersFunctiontransform_preds
Get final keypoint predictions from heatmaps and apply scaling and translation to map them back to the image. Note: num_keypoints: K
engine/pose_estimation/third-party/ViTPose/mmpose/core/post_processing/post_transforms.py:150
↓ 6 callersMethodtransform_to_posed_verts_from_neutral_pose
Transform the mean 3D vertices to posed vertices from the neutral pose. mean_3d (torch.Tensor): Mean 3D vertices with shape [B*N
LHM/models/rendering/smpl_x.py:934
↓ 6 callersMethodvae_output_to_image
(self, vae_output)
diffsynth/pipelines/base.py:39
↓ 5 callersMethod__init__
( self, w2c, intrinsic, FoVx, FoVy, height, width,
LHM/models/rendering/gs_renderer.py:103
↓ 5 callersMethod__init__
(self, fn)
diffsynth/extensions/ImageQualityMetric/trainer/models/cross_modeling.py:31
↓ 5 callersMethod__init__
(self, dim, eps=1e-6)
diffsynth/models/wan_video_text_encoder.py:24
↓ 5 callersMethod__init__
(self, input_channel, output_channel, kernel_size=3,
ProPainter/model/recurrent_flow_completion.py:128
↓ 5 callersMethod__init__
(self, channel, hidden, kernel_size, stride, padding)
ProPainter/model/modules/sparse_transformer.py:35
↓ 5 callersMethod__init__
(self, input_channels, output_channels, mid_channels=32)
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/v2v_net.py:227
↓ 5 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None
engine/pose_estimation/third-party/ViTPose/mmpose/models/backbones/hrformer.py:277
↓ 5 callersFunction_demo_inputs
Create a superset of inputs needed to run backbone. Args: input_shape (tuple): input batch dimensions. Default: (1, 3, 64, 64
engine/pose_estimation/third-party/ViTPose/tests/test_necks/test_posewarper_neck.py:131
↓ 5 callersFunction_demo_inputs
Create a superset of inputs needed to run head. Args: input_shape (tuple): input batch dimensions. Default: (1, 1024, 1).
engine/pose_estimation/third-party/ViTPose/tests/test_models/test_temporal_regression_head.py:93
↓ 5 callersMethod_get_db
Load dataset.
engine/pose_estimation/third-party/ViTPose/mmpose/datasets/datasets/top_down/topdown_mhp_dataset.py:102
↓ 5 callersMethod_get_keyboard_event_name
(key)
engine/pose_estimation/third-party/ViTPose/tools/webcam/webcam_apis/utils/event.py:48
↓ 5 callersFunction_get_max_preds
Get keypoint predictions from score maps. Note: batch_size: N num_keypoints: K heatmap height: H heatmap width: W
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/top_down_eval.py:63
↓ 5 callersMethod_load_coco_keypoint_annotations
Ground truth bbox and keypoints.
engine/pose_estimation/third-party/ViTPose/mmpose/datasets/datasets/top_down/topdown_coco_dataset.py:107
↓ 5 callersFunction_ntuple
(n)
diffsynth/extensions/ImageQualityMetric/open_clip/utils.py:48
↓ 5 callersMethodaverage
Get the average value of current window.
engine/pose_estimation/third-party/ViTPose/mmpose/utils/timer.py:26
↓ 5 callersFunctionblend_shapes
Calculates the per vertex displacement due to the blend shapes Parameters ---------- betas : torch.tensor Bx(num_betas) Blend sh
LHM/models/rendering/smplx/smplx/lbs.py:288
↓ 5 callersFunctionbuild_optimizer
(cfg, params_groups)
engine/pose_estimation/dinov2/dinov2/train/train.py:61
↓ 5 callersFunctionclosest_name
(input_str, options)
diffsynth/prompters/omost.py:98
↓ 5 callersMethodcombine_flow
(self, masked_flows_bi, pred_flows_bi, masks)
ProPainter/model/recurrent_flow_completion.py:340
↓ 5 callersFunctioncompute_jitter
Compute jitter for the input tensor
engine/pose_estimation/smplify.py:33
↓ 5 callersFunctioncompute_similarity_transform
Computes a similarity transform (sR, t) that takes a set of 3D points source_points (N x 3) closest to a set of 3D points target_points, where R
engine/pose_estimation/third-party/ViTPose/mmpose/core/evaluation/mesh_eval.py:9
↓ 5 callersMethodcontrol_noise_via_local_prompts
(self, prompt_emb_global, prompt_emb_locals, masks, mask_scales, inference_callback, special_kwargs=None, spec
diffsynth/pipelines/base.py:66
↓ 5 callersFunctionconvert_coco_to_output
(coco, is_wholebody=False)
engine/pose_estimation/third-party/ViTPose/tests/test_backward_compatibility/test_dataset_info_compatibility/test_bottom_up_dataset_compatibility.py:11
← previousnext →201–300 of 5,947, ranked by callers