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Functions133 in github.com/SS-snap/Comfyui_SSsnap_pose-Remapping

⨍ Functions 133◇ Types & classes 21
↓ 6 callersFunctionget_model_type
(Nodesname, filename)
dwpose/util.py:454
↓ 6 callersFunctionguess_onnx_input_shape_dtype
(filename)
dwpose/util.py:423
↓ 6 callersFunctionis_model_torchscript
(model)
dwpose/util.py:451
↓ 5 callersFunctiondecompress_keypoints
( numbers: Optional[List[float]], )
dwpose/__init__.py:124
↓ 4 callersFunctioncompress_keypoints
(keypoints: Union[List[Keypoint], None])
dwpose/__init__.py:162
↓ 4 callersFunctioncustom_hf_download
(pretrained_model_or_path, filename, cache_dir=temp_dir, ckpts_dir=annotator_ckpts_path, subfolder='', use_sym
tools.py:289
↓ 4 callersFunctionget_ort_providers
()
dwpose/util.py:440
↓ 3 callersMethodforward
Return a list of heatmaps.
dwpose/face.py:191
↓ 3 callersFunctionis_normalized
(keypoints: List[Optional[Keypoint]])
dwpose/util.py:71
↓ 3 callersFunctionmake_layers
(block, no_relu_layers)
dwpose/model.py:7
↓ 3 callersFunctionresize_image_with_pad
(input_image, resolution, upscale_method = "", skip_hwc3=False, mode='edge')
tools.py:155
↓ 2 callersFunctionHWC3
(x)
tools.py:63
↓ 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
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
dwpose/dw_onnx/cv_ox_pose.py:187
↓ 2 callersMethod_segment_length
(self, kps, i, j)
ratio_cau.py:80
↓ 2 callersMethod_to_kps_array
将各种可能的输入: - JSON 字符串 (dict 或 list of dict) - Python dict - list of frame-dicts - list of floats 或 lis
ratio_cau.py:34
↓ 2 callersFunctioncommon_input_validate
(input_image, output_type, **kwargs)
tools.py:175
↓ 2 callersFunctiondrawBetweenKeypointsList
(pose_img, keypoints, keypointPairsList, colorsList, scaleFactor)
dwpose/animalpose.py:30
↓ 2 callersFunctiondraw_poses
(poses: List[PoseResult], H, W, draw_body=True, draw_hand=True, draw_face=True, xinsr_stick_scaling=False)
dwpose/__init__.py:94
↓ 2 callersFunctionpad64
(x)
tools.py:150
↓ 2 callersFunctionremove_pad
(x)
tools.py:170
↓ 2 callersFunctionsafer_memory
(x)
tools.py:141
↓ 1 callersMethod__init__
(self, face_model_path, inference_size=None, gaussian_sigma=None,
dwpose/face.py:317
↓ 1 callersMethod__init__
(self)
dwpose/model.py:25
↓ 1 callersFunction_fix_aspect_ratio
Extend the scale to match the given aspect ratio. Args: scale (np.ndarray): The image scale (w, h) in shape (2, ) aspect_ratio (f
dwpose/dw_torchscript/jit_pose.py:153
↓ 1 callersFunction_fix_aspect_ratio
Extend the scale to match the given aspect ratio. Args: scale (np.ndarray): The image scale (w, h) in shape (2, ) aspect_ratio (f
dwpose/dw_onnx/cv_ox_pose.py:154
↓ 1 callersFunction_rotate_point
Rotate a point by an angle. Args: pt (np.ndarray): 2D point coordinates (x, y) in shape (2, ) angle_rad (float): rotation angle i
dwpose/dw_torchscript/jit_pose.py:171
↓ 1 callersFunction_rotate_point
Rotate a point by an angle. Args: pt (np.ndarray): 2D point coordinates (x, y) in shape (2, ) angle_rad (float): rotation angle i
dwpose/dw_onnx/cv_ox_pose.py:172
↓ 1 callersFunctionbbox_xyxy2cs
Transform the bbox format from (x,y,w,h) into (center, scale) Args: bbox (ndarray): Bounding box(es) in shape (4,) or (n, 4), formatted
dwpose/dw_torchscript/jit_pose.py:119
↓ 1 callersFunctionbbox_xyxy2cs
Transform the bbox format from (x,y,w,h) into (center, scale) Args: bbox (ndarray): Bounding box(es) in shape (4,) or (n, 4), formatted
dwpose/dw_onnx/cv_ox_pose.py:120
↓ 1 callersFunctionchunks
Yield successive n-sized chunks from lst.
dwpose/__init__.py:119
↓ 1 callersFunctioncreate_keypoint
(x, y, c)
dwpose/__init__.py:132
↓ 1 callersFunctiondecode
Modulate simcc distribution with Gaussian. Args: simcc_x (np.ndarray[K, Wx]): model predicted simcc in x. simcc_y (np.ndarray[K,
dwpose/dw_torchscript/jit_pose.py:337
↓ 1 callersFunctiondecode
Modulate simcc distribution with Gaussian. Args: simcc_x (np.ndarray[K, Wx]): model predicted simcc in x. simcc_y (np.ndarray[K,
dwpose/dw_onnx/cv_ox_pose.py:338
↓ 1 callersFunctiondecode_json_as_poses
( pose_json: dict, )
dwpose/__init__.py:112
↓ 1 callersFunctiondecode_json_to_batch
(json_batch, canvas_size=(512,768))
test.py:15
↓ 1 callersFunctiondemo_postprocess
(outputs, img_size, p6=False)
dwpose/dw_torchscript/jit_det.py:57
↓ 1 callersFunctiondemo_postprocess
(outputs, img_size, p6=False)
dwpose/dw_onnx/cv_ox_det.py:56
↓ 1 callersMethoddetect_poses
(self, oriImg)
dwpose/__init__.py:228
↓ 1 callersFunctiondrawBetweenKeypoints
(pose_img, keypoints, indexes, color, scaleFactor)
dwpose/animalpose.py:17
↓ 1 callersFunctiondraw_animalpose
(canvas: np.ndarray, keypoints: list[Keypoint])
dwpose/__init__.py:38
↓ 1 callersFunctionencode_poses_as_dict
Encode the pose as a dict following openpose JSON output format: https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/02_outp
dwpose/__init__.py:158
↓ 1 callersMethodformat_body_result
Format the body results from the candidate and subset arrays into a list of BodyResult objects. Args: candidate
dwpose/body.py:215
↓ 1 callersMethodformat_result
(keypoints_info: Optional[np.ndarray])
dwpose/wholebody.py:139
↓ 1 callersFunctionget_simcc_maximum
Get maximum response location and value from simcc representations. Note: instance number: N num_keypoints: K heatmap hei
dwpose/dw_torchscript/jit_pose.py:292
↓ 1 callersFunctionget_simcc_maximum
Get maximum response location and value from simcc representations. Note: instance number: N num_keypoints: K heatmap hei
dwpose/dw_onnx/cv_ox_pose.py:293
↓ 1 callersFunctionget_upscale_method
(method_str)
tools.py:146
↓ 1 callersFunctionget_warp_matrix
Calculate the affine transformation matrix that can warp the bbox area in the input image to the output size. Args: center (np.ndarra
dwpose/dw_torchscript/jit_pose.py:205
↓ 1 callersFunctionget_warp_matrix
Calculate the affine transformation matrix that can warp the bbox area in the input image to the output size. Args: center (np.ndarra
dwpose/dw_onnx/cv_ox_pose.py:206
↓ 1 callersFunctioninference
Inference DWPose model implemented in TorchScript. Args: model : TorchScript Model. img : Input image in shape. Returns:
dwpose/dw_torchscript/jit_pose.py:51
↓ 1 callersFunctioninference
Inference DWPose model. Processing all image segments at once to take advantage of GPU's parallelism ability if onnxruntime is installed Args:
dwpose/dw_onnx/cv_ox_pose.py:51
↓ 1 callersMethodmove_branch
(kp, parent, child, scale, subtree)
frame_cau.py:45
↓ 1 callersFunctionmulticlass_nms
Multiclass NMS implemented in Numpy. Class-aware version.
dwpose/dw_torchscript/jit_det.py:34
↓ 1 callersFunctionmulticlass_nms
Multiclass NMS implemented in Numpy. Class-aware version.
dwpose/dw_onnx/cv_ox_det.py:33
↓ 1 callersFunctionnms
Single class NMS implemented in Numpy.
dwpose/dw_torchscript/jit_det.py:5
↓ 1 callersFunctionnms
Single class NMS implemented in Numpy.
dwpose/dw_onnx/cv_ox_det.py:4
↓ 1 callersFunctionpostprocess
Postprocess for DWPose model output. Args: outputs (np.ndarray): Output of RTMPose model. model_input_size (tuple): RTMPose model
dwpose/dw_torchscript/jit_pose.py:84
↓ 1 callersFunctionpostprocess
Postprocess for DWPose model output. Args: outputs (np.ndarray): Output of RTMPose model. model_input_size (tuple): RTMPose model
dwpose/dw_onnx/cv_ox_pose.py:85
↓ 1 callersFunctionpreprocess
(img, input_size, swap=(2, 0, 1))
dwpose/dw_torchscript/jit_det.py:79
↓ 1 callersFunctionpreprocess
Do preprocessing for DWPose model inference. Args: img (np.ndarray): Input image in shape. input_size (tuple): Input image size i
dwpose/dw_torchscript/jit_pose.py:7
↓ 1 callersFunctionpreprocess
Do preprocessing for DWPose model inference. Args: img (np.ndarray): Input image in shape. input_size (tuple): Input image size i
dwpose/dw_onnx/cv_ox_pose.py:6
↓ 1 callersFunctionpreprocess
(img, input_size, swap=(2, 0, 1))
dwpose/dw_onnx/cv_ox_yolo_nas.py:7
↓ 1 callersFunctionpreprocess
(img, input_size, swap=(2, 0, 1))
dwpose/dw_onnx/cv_ox_det.py:78
↓ 1 callersFunctionprint_tree
(startpath, indent='')
文件.py:3
↓ 1 callersFunctionsha256sum
(file_path)
tools.py:249
↓ 1 callersFunctiontop_down_affine
Get the bbox image as the model input by affine transform. Args: input_size (dict): The input size of the model. bbox_scale (dict
dwpose/dw_torchscript/jit_pose.py:259
↓ 1 callersFunctiontop_down_affine
Get the bbox image as the model input by affine transform. Args: input_size (dict): The input size of the model. bbox_scale (dict
dwpose/dw_onnx/cv_ox_pose.py:260
MethodINPUT_TYPES
(cls)
frame_cau.py:6
MethodINPUT_TYPES
(s)
render_kps.py:16
MethodINPUT_TYPES
(cls)
convertPoseToStandardFormat.py:5
MethodINPUT_TYPES
(cls)
ratio_cau.py:6
Method__call__
(self, oriImg)
wholebody.py:79
Method__call__
(self, oriImgRaw)
dwpose/hand.py:25
Method__call__
(self, oriImg)
dwpose/body.py:26
Method__call__
(self, oriImg)
dwpose/wholebody.py:79
Method__call__
(self, input_image, detect_resolution=512, include_body=True, include_hand=False, include_face=False, hand_and
dwpose/__init__.py:233
Method__call__
(self, input_image, detect_resolution=512, output_type="pil", image_and_json=False, upscale_method="INTER_CUBI
dwpose/__init__.py:286
Method__call__
(self, face_img)
dwpose/face.py:331
Method__call__
(self, oriImg)
dwpose/animalpose.py:194
Method__init__
(self, det_model_path: Optional[str] = None, pose_model_path: Optional[str] = None, torchscript_device="cuda")
wholebody.py:20
Method__init__
(self, model_path)
dwpose/hand.py:16
Method__init__
(self, model_path)
dwpose/body.py:17
Method__init__
(self, det_model_path: Optional[str] = None, pose_model_path: Optional[str] = None, torchscript_device="cuda")
dwpose/wholebody.py:20
Method__init__
(self, dw_pose_estimation)
dwpose/__init__.py:199
Method__init__
(self, animal_pose_estimation)
dwpose/__init__.py:263
Method__init__
(self)
dwpose/face.py:14
Method__init__
(self, det_model_path: Optional[str] = None, pose_model_path: Optional[str] = None, torchscript_device="cuda")
dwpose/animalpose.py:135
Method__init__
(self)
dwpose/model.py:144
Functionade_palette
ADE20K palette that maps each class to RGB values.
tools.py:206
Methodapply_scales
(self, frame_list, scales, ref_pose)
frame_cau.py:55
FunctioncalculateScaleFactor
(img, size, poseSpanX, poseSpanY)
dwpose/animalpose.py:106
Methodcalculate_scales
(self, ref_json, raw_json)
ratio_cau.py:87
Functioncheck_hash_from_torch_hub
(file_path, filename)
tools.py:259
Methodcompute_peaks_from_heatmaps
(self, heatmaps)
dwpose/face.py:347
Methodconvert
(self, raw_pose_data)
convertPoseToStandardFormat.py:17
Functioncustom_torch_download
Download PyTorch models using PyTorch 2.7's built-in download mechanism.
tools.py:265
FunctiondrawBetweenSetofKeypointLists
(pose_img, keypoints_set, keypointPairsList, colorsList, scaleFactor)
dwpose/animalpose.py:34
Functiondraw_animalposes
(animals: list[list[Keypoint]], H: int, W: int)
dwpose/__init__.py:31
Functiondraw_bodypose
Draw keypoints and limbs representing body pose on a given canvas. Args: canvas (np.ndarray): A 3D numpy array representing the canv
dwpose/util.py:82
Functiondraw_facepose
Draw keypoints representing face pose on a given canvas. Args: canvas (np.ndarray): A 3D numpy array representing the canvas (image)
dwpose/util.py:203
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