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Functions4,192 in github.com/Fannovel16/comfyui_controlnet_aux

↓ 3 callersMethodscatter
(self, inputs, kwargs, device_ids)
src/custom_mmpkg/custom_mmcv/parallel/distributed_deprecated.py:52
↓ 3 callersMethodseek
(self, idx)
src/custom_mesh_graphormer/utils/tsv_file.py:66
↓ 3 callersMethodshow_result
Draw `result` over `img`. Args: img (str or Tensor): The image to be displayed. result (Tensor): The semantic segment
src/custom_mmpkg/custom_mmseg/models/segmentors/base.py:208
↓ 3 callersMethodsingle_forward
(self, img, i, j, h, w)
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/data.py:444
↓ 3 callersMethodsingle_forward
Args: img (PIL Image or Tensor): Image to be cropped and resized. Returns: PIL Image or Tensor: Randomly cro
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/data.py:488
↓ 3 callersFunctionsingle_head_full_attention
(q, k, v)
src/custom_controlnet_aux/unimatch/unimatch/attention.py:8
↓ 3 callersFunctionsingle_head_split_window_attention
(q, k, v, num_splits=1, with_shi
src/custom_controlnet_aux/unimatch/unimatch/attention.py:45
↓ 3 callersFunctionsplit_feature_1d
(feature, num_splits=2, )
src/custom_controlnet_aux/unimatch/unimatch/utils.py:155
↓ 3 callersFunctionswin_b
Constructs a swin_base architecture from `Swin Transformer: Hierarchical Vision Transformer using Shifted Windows <https://arxiv.org/pdf/2103
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/swin_transformer.py:612
↓ 3 callersMethodtext
(self)
src/custom_mmpkg/custom_mmcv/utils/config.py:403
↓ 3 callersMethodto
(self, device)
src/custom_controlnet_aux/uniformer/__init__.py:30
↓ 3 callersMethodto
(self, device)
src/custom_controlnet_aux/densepose/__init__.py:31
↓ 3 callersMethodto
(self, device)
src/custom_controlnet_aux/teed/__init__.py:31
↓ 3 callersMethodtokenize_coordinates
Express 2d coordinates with one number. Example: assume self.no_tokens = 16, then no_sections = 4: 0 0 0 0 0 0 #
src/custom_controlnet_aux/diffusion_edge/taming/data/conditional_builder/objects_center_points.py:41
↓ 3 callersMethodtranspose_for_scores
(self, x)
src/custom_mesh_graphormer/modeling/bert/modeling_graphormer.py:44
↓ 3 callersFunctiontrunc_normal_
r"""Fills the input Tensor with values drawn from a truncated normal distribution. The values are effectively drawn from the normal distributi
src/custom_mmpkg/custom_mmseg/models/utils/weight_init.py:48
↓ 3 callersFunctionvertices_loss
Compute per-vertex loss if vertex annotations are available.
src/custom_mesh_graphormer/tools/run_gphmer_bodymesh.py:140
↓ 3 callersFunctionvis_surface_normal
Visualize surface normal. Transfer surface normal value from [-1, 1] to [0, 255] Aargs: normal (torch.tensor, [h, w, 3]): surface nor
src/custom_controlnet_aux/metric3d/mono/utils/visualization.py:122
↓ 3 callersMethodvisualize
(self, image_bgr, mask, matrix, bbox_xywh)
src/custom_controlnet_aux/densepose/densepose.py:154
↓ 3 callersFunctionvisualize_reconstruction_no_text
Overlays gt_kp and pred_kp on img. Draws vert with text. Renderer is an instance of SMPLRenderer.
src/custom_mesh_graphormer/utils/renderer.py:466
↓ 2 callersMethodBOOLEAN
(default=True)
utils.py:119
↓ 2 callersMethodDice_Loss
(self, pred, label)
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/ddm_const_sde.py:703
↓ 2 callersFunctionHWC3
(x)
src/custom_controlnet_aux/zoe/transformers.py:12
↓ 2 callersFunctionUpsample
(dim, dim_out = None)
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/mask_cond_unet.py:340
↓ 2 callersMethod__exit__
(self, type, value, traceback)
src/custom_mmpkg/custom_mmcv/utils/timer.py:53
↓ 2 callersMethod__init__
(self, kernel_size, group_size, scale_factor)
src/custom_mmpkg/custom_mmcv/ops/carafe.py:194
↓ 2 callersMethod__init__
(self, output_size, spatial_scale=1.0, sampling_ratio=0,
src/custom_mmpkg/custom_mmcv/ops/deform_roi_pool.py:94
↓ 2 callersMethod__init__
(self, depth, num_stages=4, strides=(1, 2, 2, 2),
src/custom_mmpkg/custom_mmcv/cnn/resnet.py:210
↓ 2 callersMethod__init__
(self, ocr_channels, scale=1, **kwargs)
src/custom_mmpkg/custom_mmseg/models/decode_heads/ocr_head.py:97
↓ 2 callersMethod__init__
(self, in_channels, channels)
src/custom_mmpkg/custom_mmseg/models/decode_heads/da_head.py:20
↓ 2 callersMethod__init__
( self, in_channels, features=256, use_bn=False, out_channels=[256
src/custom_controlnet_aux/depth_anything_v2/dpt.py:39
↓ 2 callersMethod__init__
(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bia
src/custom_controlnet_aux/normalbae/nets/submodules/submodules.py:47
↓ 2 callersMethod__init__
(self, netNetwork)
src/custom_controlnet_aux/hed/__init__.py:59
↓ 2 callersMethod__init__
(self, block, layers, num_classes=1000, zero_init_residual=False, groups=1, width_per_group=6
src/custom_controlnet_aux/leres/leres/Resnext_torch.py:121
↓ 2 callersMethod__init__
(self, block, layers, num_classes=1000)
src/custom_controlnet_aux/leres/leres/Resnet.py:96
↓ 2 callersMethod__init__
(self, dim, drop_path=0., layer_scale_init_value=1e-6)
src/custom_controlnet_aux/metric3d/mono/model/backbones/ConvNeXt.py:17
↓ 2 callersMethod__init__
(self, d_model=128, nhead=1, no_ffn=False,
src/custom_controlnet_aux/unimatch/unimatch/transformer.py:10
↓ 2 callersMethod__init__
( self, embedding_dim: int, num_heads: int, downsample_rate: int = 1, )
src/custom_controlnet_aux/sam/modeling/transformer.py:191
↓ 2 callersMethod__init__
( self, block: Type[Union[BasicBlock, Bottleneck]], layers: List[int], num_cla
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/resnet.py:167
↓ 2 callersMethod__init__
(self, *args, **kwargs)
src/custom_controlnet_aux/diffusion_edge/taming/data/custom.py:10
↓ 2 callersMethod__init__
(self, size=256, random_crop=False, interpolation="bicubic")
src/custom_controlnet_aux/diffusion_edge/taming/data/coco.py:13
↓ 2 callersFunction_allreduce_coalesced
(tensors, world_size, bucket_size_mb=-1)
src/custom_mmpkg/custom_mmcv/runner/dist_utils.py:145
↓ 2 callersFunction_any
Since built-in ``any`` works only when the element of iterable is not iterable, implement the function.
src/custom_mmpkg/custom_mmcv/utils/testing.py:25
↓ 2 callersMethod_build_input_conv
(self, channel, conv_cfg, norm_cfg)
src/custom_mmpkg/custom_mmcv/ops/merge_cells.py:78
↓ 2 callersMethod_computeCoefficients
(self, p)
src/custom_controlnet_aux/tile/guided_filter.py:172
↓ 2 callersMethod_computeOutput
(self, ab, I)
src/custom_controlnet_aux/tile/guided_filter.py:182
↓ 2 callersMethod_dist_broadcast_coalesced
(self, tensors, buffer_size)
src/custom_mmpkg/custom_mmcv/parallel/distributed_deprecated.py:29
↓ 2 callersMethod_do_evaluate
perform evaluation and save ckpt.
src/custom_mmpkg/custom_mmcv/runner/hooks/evaluation.py:269
↓ 2 callersFunction_downSample
(I, scale=4, shape=None)
src/custom_controlnet_aux/tile/guided_filter.py:34
↓ 2 callersMethod_dump_log
(self, log_dict, runner)
src/custom_mmpkg/custom_mmcv/runner/hooks/logger/text.py:185
↓ 2 callersMethod_ensure_tsv_opened
(self)
src/custom_mesh_graphormer/utils/tsv_file.py:99
↓ 2 callersMethod_filterGray
(self, p_sub, shape_original)
src/custom_controlnet_aux/tile/guided_filter.py:94
↓ 2 callersMethod_filterGray
(self, p)
src/custom_controlnet_aux/tile/guided_filter.py:143
↓ 2 callersMethod_freeze_stages
Freeze stages param and norm stats.
src/custom_mmpkg/custom_mmseg/models/backbones/resnet.py:581
↓ 2 callersFunction_get_3rd_point
To calculate the affine matrix, three pairs of points are required. This function is used to get the 3rd point, given 2D points a & b. The 3r
src/custom_controlnet_aux/dwpose/dw_torchscript/jit_pose.py:186
↓ 2 callersFunction_get_3rd_point
To calculate the affine matrix, three pairs of points are required. This function is used to get the 3rd point, given 2D points a & b. The 3r
src/custom_controlnet_aux/dwpose/dw_onnx/cv_ox_pose.py:187
↓ 2 callersMethod_get_coarse_point_feats
Sample from fine grained features. Args: prev_output (list[Tensor]): Prediction of previous decode head. points (Tens
src/custom_mmpkg/custom_mmseg/models/decode_heads/point_head.py:148
↓ 2 callersMethod_get_fine_grained_point_feats
Sample from fine grained features. Args: x (list[Tensor]): Feature pyramid from by neck or backbone. points (Tensor):
src/custom_mmpkg/custom_mmseg/models/decode_heads/point_head.py:124
↓ 2 callersFunction_get_mmcv_home
()
src/custom_mmpkg/custom_mmcv/runner/checkpoint.py:30
↓ 2 callersFunction_get_mmcv_home
()
src/custom_controlnet_aux/uniformer/mmcv_custom/checkpoint.py:30
↓ 2 callersMethod_get_real_position
(self)
src/custom_mmpkg/custom_mmcv/video/io.py:124
↓ 2 callersMethod_get_weight
(self, weight)
src/custom_mmpkg/custom_mmcv/cnn/bricks/conv_ws.py:101
↓ 2 callersMethod_init_old_api
Initialize the old MediaPipe API.
src/custom_controlnet_aux/mediapipe_face/mediapipe_face_common.py:126
↓ 2 callersMethod_init_rule
Initialize rule, key_indicator, comparison_func, and best score. Here is the rule to determine which rule is used for key indicator w
src/custom_mmpkg/custom_mmcv/runner/hooks/evaluation.py:153
↓ 2 callersFunction_initialize
(module, cfg, wholemodule=False)
src/custom_mmpkg/custom_mmcv/cnn/utils/weight_init.py:511
↓ 2 callersFunction_jpegflag
(flag='color', channel_order='bgr')
src/custom_mmpkg/custom_mmcv/image/io.py:69
↓ 2 callersMethod_load_from_state_dict
Override default load function. AWS overrides the function _load_from_state_dict to recover weight_gamma and weight_beta if they are
src/custom_mmpkg/custom_mmcv/cnn/bricks/conv_ws.py:114
↓ 2 callersMethod_make_layer
(self, block, inplanes, planes, blocks, stride=1)
src/custom_mesh_graphormer/modeling/hrnet/hrnet_cls_net_gridfeat.py:398
↓ 2 callersMethod_make_layer
(self, block, inplanes, planes, blocks, stride=1)
src/custom_mesh_graphormer/modeling/hrnet/hrnet_cls_net.py:398
↓ 2 callersMethod_merge_a_into_b
merge dict ``a`` into dict ``b`` (non-inplace). Values in ``a`` will overwrite ``b``. ``b`` is copied first to avoid in-place modific
src/custom_mmpkg/custom_mmcv/utils/config.py:274
↓ 2 callersMethod_open
Open the current base file with the (original) mode and encoding. Return the resulting stream.
src/custom_mesh_graphormer/utils/logger.py:58
↓ 2 callersFunction_pillow2array
Convert a pillow image to numpy array. Args: img (:obj:`PIL.Image.Image`): The image loaded using PIL flag (str): Flags specifyin
src/custom_mmpkg/custom_mmcv/image/io.py:85
↓ 2 callersMethod_process_old_api
Process image using old MediaPipe API.
src/custom_controlnet_aux/mediapipe_face/mediapipe_face_common.py:159
↓ 2 callersMethod_register_backend
(cls, name, backend, force=False, prefixes=None)
src/custom_mmpkg/custom_mmcv/fileio/file_client.py:886
↓ 2 callersMethod_register_scheme
(cls, prefixes, loader, force=False)
src/custom_mmpkg/custom_mmcv/runner/checkpoint.py:168
↓ 2 callersMethod_resize
(self, x, size)
src/custom_mmpkg/custom_mmcv/ops/merge_cells.py:92
↓ 2 callersMethod_save_checkpoint
Save the current checkpoint and delete unwanted checkpoint.
src/custom_mmpkg/custom_mmcv/runner/hooks/checkpoint.py:119
↓ 2 callersMethod_save_ckpt
Save the best checkpoint. It will compare the score according to the compare function, write related information (best score, best ch
src/custom_mmpkg/custom_mmcv/runner/hooks/evaluation.py:314
↓ 2 callersFunction_scale_size
Rescale a size by a ratio. Args: size (tuple[int]): (w, h). scale (float | tuple(float)): Scaling factor. Returns: t
src/custom_mmpkg/custom_mmcv/image/geometric.py:16
↓ 2 callersMethod_should_evaluate
Judge whether to perform evaluation. Here is the rule to judge whether to perform evaluation: 1. It will not perform evaluation durin
src/custom_mmpkg/custom_mmcv/runner/hooks/evaluation.py:279
↓ 2 callersMethod_swap_ema_parameters
Swap the parameter of model with parameter in ema_buffer.
src/custom_mmpkg/custom_mmcv/runner/hooks/ema.py:83
↓ 2 callersFunction_totensor
(img, bgr2rgb, float32)
src/custom_controlnet_aux/pidi/model.py:28
↓ 2 callersFunctionact_quantization
(b, signed=False)
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/quantization.py:56
↓ 2 callersFunctionadditional_parameters_string
(annotation: Annotation, short: bool = True)
src/custom_controlnet_aux/diffusion_edge/taming/data/conditional_builder/utils.py:65
↓ 2 callersMethodafter_epoch
(self, runner)
src/custom_mmpkg/custom_mmcv/runner/hooks/hook.py:22
↓ 2 callersMethodafter_iter
(self, runner)
src/custom_mmpkg/custom_mmcv/runner/hooks/hook.py:28
↓ 2 callersFunctionallreduce_grads
Allreduce gradients. Args: params (list[torch.Parameters]): List of parameters of a model coalesce (bool, optional): Whether allr
src/custom_mmpkg/custom_mmcv/runner/dist_utils.py:121
↓ 2 callersFunctionapply_gaussian_blur
(image_np, ksize=5, sigmaX=1.0)
src/custom_controlnet_aux/tile/__init__.py:29
↓ 2 callersMethodbackward
(ctx, grad_output)
src/custom_mesh_graphormer/modeling/_smpl.py:155
↓ 2 callersMethodbackward
(ctx, grad_output)
src/custom_controlnet_aux/diffusion_edge/denoising_diffusion_pytorch/quantization.py:25
↓ 2 callersFunctionbatched_mask_to_box
Calculates boxes in XYXY format around masks. Return [0,0,0,0] for an empty mask. For input shape C1xC2x...xHxW, the output shape is C1xC2x..
src/custom_controlnet_aux/sam/utils/amg.py:303
↓ 2 callersFunctionbbox_clip
Clip bboxes to fit the image shape. Args: bboxes (ndarray): Shape (..., 4*k) img_shape (tuple[int]): (height, width) of the image
src/custom_mmpkg/custom_mmcv/image/geometric.py:342
↓ 2 callersMethodbefore_epoch
(self, runner)
src/custom_mmpkg/custom_mmcv/runner/hooks/hook.py:19
↓ 2 callersMethodbefore_iter
(self, runner)
src/custom_mmpkg/custom_mmcv/runner/hooks/hook.py:25
↓ 2 callersFunctionbgr2gray
Convert a BGR image to grayscale image. Args: img (ndarray): The input image. keepdim (bool): If False (by default), then return
src/custom_mmpkg/custom_mmcv/image/colorspace.py:22
↓ 2 callersFunctionbox_xyxy_to_xywh
(box_xyxy: torch.Tensor)
src/custom_controlnet_aux/sam/utils/amg.py:91
↓ 2 callersFunctionbuild_camera_model
Encode the camera intrinsic parameters (focal length and principle point) to a 4-channel map.
src/custom_controlnet_aux/metric3d/mono/utils/transform.py:372
↓ 2 callersFunctionbuild_dataloader
Build PyTorch DataLoader. In distributed training, each GPU/process has a dataloader. In non-distributed training, there is only one dataload
src/custom_mmpkg/custom_mmseg/datasets/builder.py:70
↓ 2 callersFunctionbuild_dataset
Build datasets.
src/custom_mmpkg/custom_mmseg/datasets/builder.py:53
↓ 2 callersFunctionbuild_dropout
Builder for drop out layers.
src/custom_mmpkg/custom_mmcv/cnn/bricks/drop.py:63
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