├── LICENSE ├── README.md ├── __init__.py ├── __version__.py ├── appendage_editor_nodes.py ├── assets ├── appendage_node.png ├── editor_example.jpg ├── editor_example_1.png ├── editor_example_2.png └── editor_example_3.jpg ├── js ├── editor_textDisplay.js ├── openpose_editor.js └── ui │ ├── OpenposeEditor.html │ └── assets │ ├── antd.dark-4fd6fdfe.css │ ├── index-22cc811d.css │ └── index-cd1939ba.js ├── openpose_editor_nodes.py ├── pyproject.toml ├── requirements.txt └── util.py /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |
2 | 3 | # ComfyUI ultimate openpose editor 4 | 5 |
6 | 7 |

8 | 9 |

10 | 11 | This is an improved version of [ComfyUI-openpose-editor](https://github.com/huchenlei/ComfyUI-openpose-editor) 12 | in ComfyUI, enable input and output with flexible choices. Much more convenient and easier to use. It integrates the render function which you also can intall it separately from my [ultimate-openpose-render](https://github.com/westNeighbor/ComfyUI-ultimate-openpose-render) repo or search in the Custom Nodes Manager 13 | 14 | If you like the project, please give me a star! ⭐ 15 | 16 | ## Installation 17 | 18 | - Manually install (**Recommend**), go to ComfyUI `/custom_nodes` directory 19 | ```bash 20 | git clone https://github.com/westNeighbor/ComfyUI-ultimate-openpose-editor 21 | cd ./ComfyUI-ultimate-openpose-editor 22 | pip install -r requirements.txt # if you use portable version, see below 23 | ``` 24 | if you use portable version, install requirement accordingly, for example, I have portable in my E: disk 25 | ```bash 26 | E:/ComfyUI_windows_portable/python_embeded/python.exe -m pip install -r requirements.txt 27 | ``` 28 | - You can install through the `Manager -> Custom Nodes Manger` search method, but probably you will meet problem to open the editor cause the **Manager** change the folder name, check the folder name after installation and change the folder name in file **_./js/openpose_editor.js_** in line 110 to the actual folder name in your computer. 29 | 30 | For example, if you have folder name **_westNeighbor_ComfyUI-ultimate-openpose-editor_** after installed, you need to change 31 | ```bash 32 | src: "extensions/ComfyUI-ultimate-openpose-editor/ui/OpenposeEditor.html", 33 | ``` 34 | to 35 | ```bash 36 | src: "extensions/westNeighbor_ComfyUI-ultimate-openpose-editor/ui/OpenposeEditor.html", 37 | ``` 38 | 39 | - Restart ComfyUI 40 | 41 | ## Usage 42 | - Insert node by `Right Click -> ultimate-openpose -> Openpose Editor Node` 43 | - `Right Click` on the node and select the `Open in Openpose Editor` to do the editting 44 |

45 | 46 |

47 | - send back after editting 48 |

49 | 50 |

51 | - `ESC` key to close, need to focus on the window first by clicking on the outer area of the editor window. 52 | 53 | ## Features 54 | The node is very functional and rich features to fit all your needs. 55 | - It is totally local running, no internet requiring like the [ComfyUI-openpose-editor](https://github.com/huchenlei/ComfyUI-openpose-editor) 56 | - It can handle all kinds of situations 57 | 58 | - It can go without any input, you can get an empty image or add poses of persons in the editor ui. 59 | 60 | - It can accept POSE\_KEYPOINTS or poses in json format as input. 61 | 62 | - To edit poses, right click the node, and open the editor through `Open in Openpose Editor` menu. The send back poses will be shown in the pose json input area. Be ware that the edit priority is **POSE\_KEYPOINT > POSE\_JSON** 63 | 64 | - It can output pose images, or POSE\_KEYPOINTS or the json poses. Be ware that the output priority is **POSE\_JSON > POSE\_KEYPOINT** 65 | 66 | - It integrates the render options too, so you can use it as an render node too, or check my [ultimate-openpose-render](https://github.com/westNeighbor/ComfyUI-ultimate-openpose-render) node. 67 | 68 |

69 | 70 |

71 | 72 | - Quick options to scale part or overall of the poses. You also can scale specific person(pose) by set the `only_scale_pose_index` to the one you want to scale, set a number out of the index range to scale all poses. **Note: the index is not necessary natural order (e.g. from left to right). ** 73 | 74 | ## New Node 75 | A new procedure editting node [AppendageEditorNode](https://github.com/westNeighbor/ComfyUI-ultimate-openpose-editor/pull/10) is added. 76 |

77 | 78 |

79 | - **Precise body part editing** for OpenPose keypoints with granular control over: 80 | - Arms: `left/right_upper_arm`, `left/right_forearm`, `left/right_full_arm` 81 | - Legs: `left/right_upper_leg`, `left/right_lower_leg`, `left/right_full_leg` 82 | - Hands/Feet: `left/right_hand`, `left/right_foot` 83 | - Torso: `torso`, `shoulders` 84 | - **Transform controls**: scale, rotation, x/y offset with animation support 85 | - **Scaling modes**: 86 | - `bidirectional_scale=True`: scales in all directions from pivot 87 | - `bidirectional_scale=False`: scales only away from body (prevents adjacent part interference) 88 | - **Multi-person support** with configurable person index 89 | - **Animation-friendly** with list parameter handling and mismatch behaviors 90 | 91 | One can chain N Appendage Editors together, and then render the final result. 92 | 93 | 94 | ## Credits 95 | - https://github.com/huchenlei/ComfyUI-openpose-editor 96 | -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | from .openpose_editor_nodes import OpenposeEditorNode 2 | from .appendage_editor_nodes import AppendageEditorNode 3 | 4 | 5 | WEB_DIRECTORY = "js" 6 | 7 | NODE_CLASS_MAPPINGS = { 8 | "OpenposeEditorNode": OpenposeEditorNode, 9 | "AppendageEditorNode": AppendageEditorNode, 10 | } 11 | 12 | NODE_DISPLAY_NAME_MAPPINGS = { 13 | "OpenposeEditorNode": "Openpose Editor Node", 14 | "AppendageEditorNode": "Appendage Editor", 15 | } 16 | 17 | __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS", "WEB_DIRECTORY"] 18 | -------------------------------------------------------------------------------- /__version__.py: -------------------------------------------------------------------------------- 1 | VERSION = '1.1.0' 2 | -------------------------------------------------------------------------------- /appendage_editor_nodes.py: -------------------------------------------------------------------------------- 1 | import json 2 | import copy 3 | import math 4 | import torch 5 | import numpy as np 6 | from .util import scale 7 | 8 | class AppendageEditorNode: 9 | @staticmethod 10 | def normalize_scale_parameter(scale_param, target_length, behavior): 11 | """ 12 | Normalize a scale parameter to a list of the target length. 13 | 14 | Args: 15 | scale_param: Either a single float or list of floats 16 | target_length: Desired length of output list 17 | behavior: "truncate", "loop", or "repeat" 18 | 19 | Returns: 20 | List of floats with length determined by behavior 21 | """ 22 | # Convert single value to list 23 | if not isinstance(scale_param, (list, tuple)): 24 | scale_list = [scale_param] 25 | else: 26 | scale_list = list(scale_param) 27 | 28 | if len(scale_list) == target_length: 29 | return scale_list 30 | 31 | if behavior == "truncate": 32 | return scale_list[:target_length] 33 | elif behavior == "loop": 34 | if len(scale_list) == 0: 35 | return [1.0] * target_length 36 | result = [] 37 | for i in range(target_length): 38 | result.append(scale_list[i % len(scale_list)]) 39 | return result 40 | elif behavior == "repeat": 41 | if len(scale_list) == 0: 42 | return [1.0] * target_length 43 | if len(scale_list) >= target_length: 44 | return scale_list[:target_length] 45 | else: 46 | result = scale_list[:] 47 | last_value = scale_list[-1] 48 | while len(result) < target_length: 49 | result.append(last_value) 50 | return result 51 | else: 52 | raise ValueError(f"Unknown behavior: {behavior}") 53 | 54 | @staticmethod 55 | def determine_output_length(scale_params, pose_count, behavior): 56 | """ 57 | Determine the output length based on scale parameters and behavior. 58 | """ 59 | # Get all list lengths 60 | lengths = [pose_count] 61 | for param in scale_params: 62 | if isinstance(param, (list, tuple)): 63 | lengths.append(len(param)) 64 | 65 | if behavior == "truncate": 66 | return min(lengths) 67 | else: # loop or repeat 68 | return max(lengths) 69 | 70 | @classmethod 71 | def INPUT_TYPES(s): 72 | return { 73 | "required": { 74 | "POSE_KEYPOINT": ("POSE_KEYPOINT",), 75 | "appendage_type": ([ 76 | "left_upper_arm", "left_forearm", "left_full_arm", 77 | "right_upper_arm", "right_forearm", "right_full_arm", 78 | "left_upper_leg", "left_lower_leg", "left_full_leg", 79 | "right_upper_leg", "right_lower_leg", "right_full_leg", 80 | "left_hand", "right_hand", "left_foot", "right_foot", 81 | "torso", "shoulders" 82 | ], { 83 | "default": "left_upper_arm" 84 | }), 85 | }, 86 | "optional": { 87 | "scale": ("FLOAT", { 88 | "default": 1.0, 89 | "min": 0.0, 90 | "max": 10.0, 91 | "step": 0.05 92 | }), 93 | "x_offset": ("FLOAT", { 94 | "default": 0.0, 95 | "min": -2.0, 96 | "max": 2.0, 97 | "step": 0.01 98 | }), 99 | "y_offset": ("FLOAT", { 100 | "default": 0.0, 101 | "min": -2.0, 102 | "max": 2.0, 103 | "step": 0.01 104 | }), 105 | "rotation": ("FLOAT", { 106 | "default": 0.0, 107 | "min": -180.0, 108 | "max": 180.0, 109 | "step": 1.0 110 | }), 111 | "bidirectional_scale": ("BOOLEAN", { 112 | "default": False, 113 | "tooltip": "If true, scales in both directions from pivot. If false, only scales away from body to prevent cannibalizing adjacent parts." 114 | }), 115 | "person_index": ("INT", { 116 | "default": -1, 117 | "min": -1, 118 | "max": 100, 119 | "tooltip": "Person to edit (-1 for all people)" 120 | }), 121 | "list_mismatch_behavior": (["truncate", "loop", "repeat"], {"default": "loop", "tooltip": "Truncate: Truncate the list to the shortest length. Loop: Loop the list to the longest length. Repeat: Repeat the list to the longest length."}), 122 | }, 123 | } 124 | 125 | RETURN_NAMES = ("POSE_KEYPOINT",) 126 | RETURN_TYPES = ("POSE_KEYPOINT",) 127 | FUNCTION = "edit_appendage" 128 | CATEGORY = "ultimate-openpose" 129 | 130 | def edit_appendage(self, POSE_KEYPOINT, appendage_type, scale=1.0, x_offset=0.0, y_offset=0.0, rotation=0.0, bidirectional_scale=False, person_index=-1, list_mismatch_behavior="loop"): 131 | if POSE_KEYPOINT is None: 132 | return (None,) 133 | 134 | # Deep copy to avoid modifying the original 135 | pose_data = copy.deepcopy(POSE_KEYPOINT) 136 | if not isinstance(pose_data, list): 137 | pose_data = [pose_data] 138 | 139 | pose_count = len(pose_data) 140 | 141 | # Normalize scale parameters to handle lists vs single floats using the original node's methods 142 | scale_params = [scale, x_offset, y_offset, rotation] 143 | output_length = determine_output_length(scale_params, pose_count, list_mismatch_behavior) 144 | 145 | scale_list = normalize_scale_parameter(scale, output_length, list_mismatch_behavior) 146 | x_offset_list = normalize_scale_parameter(x_offset, output_length, list_mismatch_behavior) 147 | y_offset_list = normalize_scale_parameter(y_offset, output_length, list_mismatch_behavior) 148 | rotation_list = normalize_scale_parameter(rotation, output_length, list_mismatch_behavior) 149 | 150 | # Process each frame with its corresponding parameter values 151 | output_pose_data = [] 152 | 153 | for i in range(output_length): 154 | # Get the pose data for this index 155 | pose_idx = i if i < pose_count else pose_count - 1 156 | if list_mismatch_behavior == "loop" and pose_count > 0: 157 | pose_idx = i % pose_count 158 | 159 | # Get current frame and parameter values 160 | current_frame = copy.deepcopy(pose_data[pose_idx]) 161 | current_scale = scale_list[i] 162 | current_x_offset = x_offset_list[i] 163 | current_y_offset = y_offset_list[i] 164 | current_rotation = rotation_list[i] 165 | 166 | # Apply transformations to this frame 167 | if 'people' in current_frame: 168 | people_to_edit = range(len(current_frame['people'])) if person_index == -1 else [person_index] 169 | 170 | for person_idx in people_to_edit: 171 | if person_idx >= len(current_frame['people']): 172 | continue 173 | 174 | person = current_frame['people'][person_idx] 175 | 176 | if appendage_type in ["left_hand", "right_hand"]: 177 | self._edit_hand_appendage(person, appendage_type, current_scale, current_x_offset, current_y_offset, current_rotation, bidirectional_scale) 178 | else: 179 | self._edit_body_appendage(person, appendage_type, current_scale, current_x_offset, current_y_offset, current_rotation, bidirectional_scale) 180 | 181 | output_pose_data.append(current_frame) 182 | 183 | return (output_pose_data,) 184 | 185 | def _edit_hand_appendage(self, person, appendage_type, scale_factor, x_offset, y_offset, rotation, bidirectional_scale): 186 | """Edit hand appendages using hand keypoints.""" 187 | keypoint_field = "hand_left_keypoints_2d" if appendage_type == "left_hand" else "hand_right_keypoints_2d" 188 | 189 | if keypoint_field not in person or not person[keypoint_field]: 190 | return 191 | 192 | keypoints = person[keypoint_field] 193 | 194 | # Use wrist (first point) as pivot for hands 195 | if len(keypoints) >= 3 and keypoints[2] > 0: 196 | pivot = [keypoints[0], keypoints[1]] 197 | else: 198 | # Calculate center of mass if wrist not available 199 | pivot = self._calculate_center_of_mass(keypoints) 200 | if pivot is None: 201 | return 202 | 203 | # Apply transformations 204 | new_keypoints = self._apply_transformations(keypoints, scale_factor, x_offset, y_offset, rotation, pivot, bidirectional_scale) 205 | person[keypoint_field] = new_keypoints 206 | 207 | def _edit_body_appendage(self, person, appendage_type, scale_factor, x_offset, y_offset, rotation, bidirectional_scale): 208 | """Edit body appendages (arms, legs, feet) using body pose keypoints.""" 209 | if 'pose_keypoints_2d' not in person or not person['pose_keypoints_2d']: 210 | return 211 | 212 | keypoints = person['pose_keypoints_2d'] 213 | 214 | # Get keypoint indices for the specific appendage 215 | appendage_indices, pivot_index = self._get_appendage_indices(appendage_type) 216 | if not appendage_indices: 217 | return 218 | 219 | # Calculate pivot point for the appendage 220 | pivot = self._calculate_appendage_pivot(keypoints, appendage_indices, pivot_index) 221 | if pivot is None: 222 | return 223 | 224 | # Apply transformations only to the appendage keypoints 225 | new_keypoints = keypoints[:] 226 | 227 | for i in range(0, len(keypoints), 3): 228 | keypoint_idx = i // 3 229 | if keypoint_idx in appendage_indices and len(keypoints) > i+2: 230 | x, y, conf = keypoints[i], keypoints[i+1], keypoints[i+2] 231 | 232 | if conf > 0: 233 | # Apply rotation 234 | if rotation != 0.0: 235 | rad = math.radians(rotation) 236 | cos_r, sin_r = math.cos(rad), math.sin(rad) 237 | rel_x, rel_y = x - pivot[0], y - pivot[1] 238 | x = rel_x * cos_r - rel_y * sin_r + pivot[0] 239 | y = rel_x * sin_r + rel_y * cos_r + pivot[1] 240 | 241 | # Apply scaling with directional control 242 | if scale_factor != 1.0: 243 | if bidirectional_scale: 244 | scaled_point = scale([x, y], scale_factor, pivot) 245 | x, y = scaled_point[0], scaled_point[1] 246 | else: 247 | # Unidirectional scaling - only scale away from body 248 | x, y = self._apply_unidirectional_scale([x, y], scale_factor, pivot, keypoint_idx, pivot_index) 249 | 250 | # Apply offset 251 | x += x_offset 252 | y += y_offset 253 | 254 | new_keypoints[i] = x 255 | new_keypoints[i+1] = y 256 | 257 | person['pose_keypoints_2d'] = new_keypoints 258 | 259 | def _get_appendage_indices(self, appendage_type): 260 | """Get OpenPose keypoint indices for specific appendages and their pivot points.""" 261 | # COCO 18-keypoint format (0-based) used by ComfyUI ControlNet Aux OpenPose Pose node: 262 | # 0: Nose, 1: Neck, 2: RShoulder, 3: RElbow, 4: RWrist, 5: LShoulder, 6: LElbow, 7: LWrist, 263 | # 8: RHip, 9: RKnee, 10: RAnkle, 11: LHip, 12: LKnee, 13: LAnkle, 14: REye, 15: LEye, 16: REar, 17: LEar 264 | 265 | appendage_map = { 266 | # Arms - COCO format 267 | "left_upper_arm": ([5, 6], 5), # LShoulder, LElbow (pivot: shoulder) 268 | "left_forearm": ([6, 7], 6), # LElbow, LWrist (pivot: elbow) 269 | "left_full_arm": ([5, 6, 7], 5), # LShoulder, LElbow, LWrist (pivot: shoulder) 270 | "right_upper_arm": ([2, 3], 2), # RShoulder, RElbow (pivot: shoulder) 271 | "right_forearm": ([3, 4], 3), # RElbow, RWrist (pivot: elbow) 272 | "right_full_arm": ([2, 3, 4], 2), # RShoulder, RElbow, RWrist (pivot: shoulder) 273 | 274 | # Legs - COCO format (FIXED!) 275 | "left_upper_leg": ([11, 12], 11), # LHip, LKnee (pivot: hip) 276 | "left_lower_leg": ([12, 13], 12), # LKnee, LAnkle (pivot: knee) - FIXED: was [13,14] which was LAnkle,REye! 277 | "left_full_leg": ([11, 12, 13], 11), # LHip, LKnee, LAnkle (pivot: hip) 278 | "right_upper_leg": ([8, 9], 8), # RHip, RKnee (pivot: hip) 279 | "right_lower_leg": ([9, 10], 9), # RKnee, RAnkle (pivot: knee) 280 | "right_full_leg": ([8, 9, 10], 8), # RHip, RKnee, RAnkle (pivot: hip) 281 | 282 | # Feet - COCO format (no foot keypoints in COCO, use ankle only) 283 | "left_foot": ([13], 13), # LAnkle only (pivot: ankle) 284 | "right_foot": ([10], 10), # RAnkle only (pivot: ankle) 285 | 286 | # Torso and Shoulders - COCO format 287 | "torso": ([1, 2, 5, 8, 11], 1), # Neck, RShoulder, LShoulder, RHip, LHip (pivot: neck) 288 | "shoulders": ([2, 5], 1), # RShoulder, LShoulder (pivot: neck) 289 | } 290 | 291 | result = appendage_map.get(appendage_type, ([], None)) 292 | return result[0], result[1] 293 | 294 | def _calculate_appendage_pivot(self, keypoints, appendage_indices, pivot_index): 295 | """Calculate pivot point for body appendage using specified pivot index.""" 296 | if pivot_index is not None: 297 | # Use specific pivot point (e.g., shoulder for upper arm, elbow for forearm) 298 | i = pivot_index * 3 299 | if len(keypoints) > i+2 and keypoints[i+2] > 0: 300 | return [keypoints[i], keypoints[i+1]] 301 | 302 | # Fallback to center of mass if pivot point not available 303 | valid_points = [] 304 | for idx in appendage_indices: 305 | i = idx * 3 306 | if len(keypoints) > i+2 and keypoints[i+2] > 0: 307 | valid_points.append([keypoints[i], keypoints[i+1]]) 308 | 309 | if not valid_points: 310 | return None 311 | 312 | pivot_x = sum(p[0] for p in valid_points) / len(valid_points) 313 | pivot_y = sum(p[1] for p in valid_points) / len(valid_points) 314 | return [pivot_x, pivot_y] 315 | 316 | def _apply_unidirectional_scale(self, point, scale_factor, pivot, keypoint_idx, pivot_index): 317 | """Apply scaling only in the direction away from the body/pivot.""" 318 | x, y = point 319 | 320 | if keypoint_idx == pivot_index: 321 | # Don't scale the pivot point itself 322 | return x, y 323 | 324 | # Calculate direction vector from pivot to point 325 | dx = x - pivot[0] 326 | dy = y - pivot[1] 327 | 328 | # Scale only the distance, keeping direction 329 | distance = math.sqrt(dx*dx + dy*dy) 330 | if distance > 0: 331 | new_distance = distance * scale_factor 332 | scale_ratio = new_distance / distance 333 | 334 | new_x = pivot[0] + dx * scale_ratio 335 | new_y = pivot[1] + dy * scale_ratio 336 | return new_x, new_y 337 | 338 | return x, y 339 | 340 | def _calculate_center_of_mass(self, keypoints): 341 | """Calculate center of mass from valid keypoints.""" 342 | valid_points = [] 343 | for i in range(0, len(keypoints), 3): 344 | if len(keypoints) > i+2 and keypoints[i+2] > 0: 345 | valid_points.append([keypoints[i], keypoints[i+1]]) 346 | 347 | if not valid_points: 348 | return None 349 | 350 | pivot_x = sum(p[0] for p in valid_points) / len(valid_points) 351 | pivot_y = sum(p[1] for p in valid_points) / len(valid_points) 352 | return [pivot_x, pivot_y] 353 | 354 | def _apply_transformations(self, keypoints, scale_factor, x_offset, y_offset, rotation, pivot, bidirectional_scale): 355 | """Apply transformations to all keypoints.""" 356 | new_keypoints = [] 357 | for i in range(0, len(keypoints), 3): 358 | if len(keypoints) > i+2: 359 | x, y, conf = keypoints[i], keypoints[i+1], keypoints[i+2] 360 | 361 | if conf > 0: 362 | # Apply rotation 363 | if rotation != 0.0: 364 | rad = math.radians(rotation) 365 | cos_r, sin_r = math.cos(rad), math.sin(rad) 366 | rel_x, rel_y = x - pivot[0], y - pivot[1] 367 | x = rel_x * cos_r - rel_y * sin_r + pivot[0] 368 | y = rel_x * sin_r + rel_y * cos_r + pivot[1] 369 | 370 | # Apply scaling 371 | if scale_factor != 1.0: 372 | if bidirectional_scale: 373 | scaled_point = scale([x, y], scale_factor, pivot) 374 | x, y = scaled_point[0], scaled_point[1] 375 | else: 376 | # For hands, use unidirectional scaling from wrist 377 | x, y = self._apply_unidirectional_scale([x, y], scale_factor, pivot, i//3, 0) 378 | 379 | # Apply offset 380 | x += x_offset 381 | y += y_offset 382 | 383 | new_keypoints.extend([x, y, conf]) 384 | 385 | return new_keypoints 386 | -------------------------------------------------------------------------------- /assets/appendage_node.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/westNeighbor/ComfyUI-ultimate-openpose-editor/20b5b7e6e81f1d5c820841a3c3985b8a02f65df4/assets/appendage_node.png -------------------------------------------------------------------------------- /assets/editor_example.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/westNeighbor/ComfyUI-ultimate-openpose-editor/20b5b7e6e81f1d5c820841a3c3985b8a02f65df4/assets/editor_example.jpg -------------------------------------------------------------------------------- /assets/editor_example_1.png: -------------------------------------------------------------------------------- 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-------------------------------------------------------------------------------- 1 | import { app } from "../../../scripts/app.js"; 2 | import { ComfyWidgets } from "../../../scripts/widgets.js"; 3 | 4 | // Displays input text on a node 5 | app.registerExtension({ 6 | name: "EditOpenposeText", 7 | async beforeRegisterNodeDef(nodeType, nodeData, app) { 8 | if (nodeData.name === "OpenposeEditorNode") { 9 | function populate(text) { 10 | let removed = 0; 11 | if (this.widgets) { 12 | for (let i = 8; i < this.widgets.length; i++) { 13 | if (this.widgets[i].name === "display_only") { 14 | this.widgets[i].onRemove?.(); 15 | removed++; 16 | } 17 | } 18 | this.widgets.length = this.widgets.length - removed; 19 | } 20 | 21 | if (this.inputs?.[0].link || this.inputs?.[this.inputs.length-1].widget) { 22 | const v = [...text]; 23 | if (!v[0]) { 24 | v.shift(); 25 | } 26 | for (const list of v) { 27 | // const w = this.widgets[0]; 28 | // w.value = list; 29 | // if (this.inputs?.[this.inputs.length-1].widget) { 30 | 31 | const w = ComfyWidgets["STRING"](this, "display_only", ["STRING", { multiline: true }], app).widget; 32 | w.inputEl.readOnly = true; 33 | w.inputEl.style.opacity = 0.6; 34 | w.value = list; 35 | 36 | //} 37 | } 38 | } 39 | 40 | requestAnimationFrame(() => { 41 | const sz = this.computeSize(); 42 | if (sz[0] < this.size[0]) { 43 | sz[0] = this.size[0]; 44 | } 45 | if (sz[1] < this.size[1]) { 46 | sz[1] = this.size[1]; 47 | } 48 | this.onResize?.(sz); 49 | app.graph.setDirtyCanvas(true, false); 50 | }); 51 | } 52 | 53 | // When the node is executed we will be sent the input text, display this in the widget 54 | const onExecuted = nodeType.prototype.onExecuted; 55 | nodeType.prototype.onExecuted = function (message) { 56 | onExecuted?.apply(this, arguments); 57 | populate.call(this, message.POSE_JSON); 58 | }; 59 | 60 | const onConfigure = nodeType.prototype.onConfigure; 61 | nodeType.prototype.onConfigure = function () { 62 | onConfigure?.apply(this, arguments); 63 | if (this.widgets_values?.length) { 64 | // populate.call(this, this.widgets_values.slice(+this.widgets_values.length > 1)); 65 | } 66 | }; 67 | } 68 | }, 69 | }); 70 | -------------------------------------------------------------------------------- /js/openpose_editor.js: -------------------------------------------------------------------------------- 1 | import { app } from "../../scripts/app.js"; 2 | import { ComfyDialog, $el } from "../../scripts/ui.js"; 3 | import { ComfyApp } from "../../scripts/app.js"; 4 | 5 | 6 | function addMenuHandler(nodeType, cb) { 7 | const getOpts = nodeType.prototype.getExtraMenuOptions; 8 | nodeType.prototype.getExtraMenuOptions = function () { 9 | const r = getOpts.apply(this, arguments); 10 | cb.apply(this, arguments); 11 | return r; 12 | }; 13 | } 14 | 15 | class OpenposeEditorDialog extends ComfyDialog { 16 | static timeout = 5000; 17 | static instance = null; 18 | 19 | static getInstance() { 20 | if (!OpenposeEditorDialog.instance) { 21 | OpenposeEditorDialog.instance = new OpenposeEditorDialog(); 22 | } 23 | 24 | return OpenposeEditorDialog.instance; 25 | } 26 | 27 | constructor() { 28 | super(); 29 | this.element = $el("div.comfy-modal", { 30 | parent: document.body, 31 | style: { 32 | width: "80vw", 33 | height: "80vh", 34 | }, 35 | }, [ 36 | $el("div.comfy-modal-content", { 37 | style: { 38 | width: "100%", 39 | height: "100%", 40 | }, 41 | }, this.createButtons()), 42 | ]); 43 | this.is_layout_created = false; 44 | 45 | window.addEventListener("message", (event) => { 46 | if (event.source !== this.iframeElement.contentWindow) { 47 | return; 48 | } 49 | 50 | const message = event.data; 51 | if (message.modalId === 0) { 52 | const targetNode = ComfyApp.clipspace_return_node; 53 | const textAreaElement = targetNode.widgets[14].element; 54 | textAreaElement.value = JSON.stringify(event.data.poses); 55 | ComfyApp.onClipspaceEditorClosed(); 56 | this.close(); 57 | } 58 | }); 59 | } 60 | 61 | createButtons() { 62 | const closeBtn = $el("button", { 63 | type: "button", 64 | textContent: "Close", 65 | onclick: () => this.close(), 66 | }); 67 | return [ 68 | closeBtn, 69 | ]; 70 | } 71 | 72 | close() { 73 | super.close(); 74 | } 75 | 76 | async show() { 77 | if (!this.is_layout_created) { 78 | this.createLayout(); 79 | this.is_layout_created = true; 80 | await this.waitIframeReady(); 81 | } 82 | 83 | const targetNode = ComfyApp.clipspace_return_node; 84 | if (targetNode.inputs?.[0].link || targetNode.inputs?.[targetNode.inputs.length-1].widget){ 85 | const textAreaElement = targetNode.widgets[15].element; 86 | this.element.style.display = "flex"; 87 | this.setCanvasJSONString(textAreaElement.value.replace(/'/g, '"')); 88 | } else { 89 | const textAreaElement = targetNode.widgets[14].element; 90 | this.element.style.display = "flex"; 91 | if (textAreaElement.value === "") { 92 | let resolution_x = targetNode.widgets[3].value; 93 | let resolution_y = Math.floor(768*(resolution_x*1.0/512)); 94 | if (resolution_x < 64){ 95 | resolution_x = 512; 96 | resolution_y = 768; 97 | } 98 | 99 | let pose = `[{"people": [{"pose_keypoints_2d": [], "face_keypoints_2d": [], "hand_left_keypoints_2d": [], "hand_right_keypoints_2d": []}], "canvas_height": ${resolution_y}, "canvas_width": ${resolution_x}}]`; 100 | this.setCanvasJSONString(pose); 101 | } else { 102 | this.setCanvasJSONString(textAreaElement.value.replace(/'/g, '"')); 103 | } 104 | } 105 | } 106 | 107 | createLayout() { 108 | this.iframeElement = $el("iframe", { 109 | // Change to for local dev 110 | src: "extensions/ComfyUI-ultimate-openpose-editor/ui/OpenposeEditor.html", 111 | style: { 112 | width: "100%", 113 | height: "100%", 114 | border: "none", 115 | }, 116 | }); 117 | const modalContent = this.element.querySelector(".comfy-modal-content"); 118 | while (modalContent.firstChild) { 119 | modalContent.removeChild(modalContent.firstChild); 120 | } 121 | modalContent.appendChild(this.iframeElement); 122 | } 123 | 124 | waitIframeReady() { 125 | return new Promise((resolve, reject) => { 126 | const receiveMessage = (event) => { 127 | if (event.source !== this.iframeElement.contentWindow) { 128 | return; 129 | } 130 | if (event.data.ready) { 131 | window.removeEventListener("message", receiveMessage); 132 | clearTimeout(timeoutHandle); 133 | resolve(); 134 | } 135 | }; 136 | const timeoutHandle = setTimeout(() => { 137 | reject(new Error("Timeout")); 138 | }, OpenposeEditorDialog.timeout); 139 | 140 | window.addEventListener("message", receiveMessage); 141 | }); 142 | } 143 | 144 | setCanvasJSONString(jsonString) { 145 | this.iframeElement.contentWindow.postMessage({ 146 | modalId: 0, 147 | poses: JSON.parse(jsonString) 148 | }, "*"); 149 | } 150 | } 151 | 152 | app.registerExtension({ 153 | name: "OpenposeEditor", 154 | 155 | async beforeRegisterNodeDef(nodeType, nodeData) { 156 | if (nodeData.name === "OpenposeEditorNode") { 157 | addMenuHandler(nodeType, function (_, options) { 158 | options.unshift({ 159 | content: "Open in Openpose Editor", 160 | callback: () => { 161 | // `this` is the node instance 162 | ComfyApp.copyToClipspace(this); 163 | ComfyApp.clipspace_return_node = this; 164 | 165 | const dlg = OpenposeEditorDialog.getInstance(); 166 | dlg.show(); 167 | }, 168 | }); 169 | }); 170 | } 171 | } 172 | }); 173 | -------------------------------------------------------------------------------- /js/ui/OpenposeEditor.html: -------------------------------------------------------------------------------- 1 | 2 | 57 | 58 | 59 | Openpose Editor 60 | 61 | 62 | 63 | 64 |
ComfyUI-ULTIMATE-OPENPOSE-EDITOR
679
(SPACE / F) + Drag MouseHold key to pan the canvas
Mouse wheelZoom in/out
Right clickHide keypoint
Width
px
Height
px
88 | 89 | 93 | 94 | 95 | 96 | -------------------------------------------------------------------------------- /js/ui/assets/index-22cc811d.css: -------------------------------------------------------------------------------- 1 | .icon-switch[data-v-67f5f644]{cursor:pointer}.custom-svg[data-v-3df26ed3]{width:1rem;height:1rem;margin:3px}.custom-svg path[data-v-3df26ed3]{fill:var(--color-text);transition:fill .3s ease}.flipDisabled[data-v-1d917c1f]{opacity:50%}.hidden{opacity:50%;text-decoration:line-through}:root{--vt-c-white: #ffffff;--vt-c-white-soft: #f8f8f8;--vt-c-white-mute: #f2f2f2;--vt-c-black: #181818;--vt-c-black-soft: #222222;--vt-c-black-mute: #282828;--vt-c-indigo: #2c3e50;--vt-c-divider-light-1: rgba(60, 60, 60, .29);--vt-c-divider-light-2: rgba(60, 60, 60, .12);--vt-c-divider-dark-1: rgba(84, 84, 84, .65);--vt-c-divider-dark-2: rgba(84, 84, 84, .48);--vt-c-text-light-1: var(--vt-c-indigo);--vt-c-text-light-2: rgba(60, 60, 60, .66);--vt-c-text-dark-1: var(--vt-c-white);--vt-c-text-dark-2: rgba(235, 235, 235, .64)}:root{--color-background: var(--vt-c-white);--color-background-soft: var(--vt-c-white-soft);--color-background-mute: var(--vt-c-white-mute);--color-border: var(--vt-c-divider-light-2);--color-border-hover: var(--vt-c-divider-light-1);--color-heading: var(--vt-c-text-light-1);--color-text: var(--vt-c-text-light-1);--section-gap: 160px}body.dark-theme{--color-background: var(--vt-c-black);--color-background-soft: var(--vt-c-black-soft);--color-background-mute: var(--vt-c-black-mute);--color-border: var(--vt-c-divider-dark-2);--color-border-hover: var(--vt-c-divider-dark-1);--color-heading: var(--vt-c-text-dark-1);--color-text: var(--vt-c-text-dark-1)}@media (prefers-color-scheme: dark){:root{--color-background: var(--vt-c-black);--color-background-soft: var(--vt-c-black-soft);--color-background-mute: var(--vt-c-black-mute);--color-border: var(--vt-c-divider-dark-2);--color-border-hover: var(--vt-c-divider-dark-1);--color-heading: var(--vt-c-text-dark-1);--color-text: var(--vt-c-text-dark-2)}}*,*:before,*:after{box-sizing:border-box;margin:0;position:relative;font-weight:400}body{min-height:100vh;color:var(--color-text);background:var(--color-background);transition:color .5s,background-color .5s;line-height:1.6;font-family:Inter,-apple-system,BlinkMacSystemFont,Segoe UI,Roboto,Oxygen,Ubuntu,Cantarell,Fira Sans,Droid Sans,Helvetica Neue,sans-serif;font-size:15px;text-rendering:optimizeLegibility;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale}.visible-switch,.group-switch,.unjam-button,.lock-switch{padding:3px}.ant-collapse-header{align-items:center!important;justify-content:flex-start}.ant-list-item{justify-content:flex-start}.close-icon,.coords-group,.scale-ratio-input{margin-left:auto}.ant-col{padding:10px}.image-thumbnail{width:50px;height:50px;object-fit:cover;margin-right:8px}.uploaded-file-item>div{display:flex;justify-content:flex-start;align-items:center}.ant-space{margin-bottom:5px}li.keypoint-selected{background-color:#fdd;color:#b20000}.dark-theme li.keypoint-selected{color:#fdd;background-color:#5e0303}#control-panel{height:100vh;overflow-y:auto}#control-panel::-webkit-scrollbar{display:none}.ant-space{flex-wrap:wrap}.ant-input-number{max-width:100px} 2 | -------------------------------------------------------------------------------- /openpose_editor_nodes.py: -------------------------------------------------------------------------------- 1 | import json 2 | import torch 3 | import numpy as np 4 | from .util import draw_pose_json, draw_pose, extend_scalelist, pose_normalized 5 | 6 | OpenposeJSON = dict 7 | 8 | class OpenposeEditorNode: 9 | @classmethod 10 | def INPUT_TYPES(s): 11 | return { 12 | "optional": { 13 | "show_body": ("BOOLEAN", {"default": True}), 14 | "show_face": ("BOOLEAN", {"default": True}), 15 | "show_hands": ("BOOLEAN", {"default": True}), 16 | "resolution_x": ("INT", { 17 | "default": -1, 18 | "min": -1, 19 | "max": 12800, 20 | "tooltip": "Resolution X. -1 means use the original resolution." 21 | }), 22 | "pose_marker_size": ("INT", { 23 | "default": 4, 24 | "min": 0, 25 | "max": 100 26 | }), 27 | "face_marker_size": ("INT", { 28 | "default": 3, 29 | "min": 0, 30 | "max": 100 31 | }), 32 | "hand_marker_size": ("INT", { 33 | "default": 2, 34 | "min": 0, 35 | "max": 100 36 | }), 37 | "hands_scale": ("FLOAT", { 38 | "default": 1.0, 39 | "min": 0.0, 40 | "max": 10.0, 41 | "step": 0.05 42 | }), 43 | "body_scale": ("FLOAT", { 44 | "default": 1.0, 45 | "min": 0.0, 46 | "max": 10.0, 47 | "step": 0.05 48 | }), 49 | "head_scale": ("FLOAT", { 50 | "default": 1.0, 51 | "min": 0.0, 52 | "max": 10.0, 53 | "step": 0.05 54 | }), 55 | "overall_scale": ("FLOAT", { 56 | "default": 1.0, 57 | "min": 0.0, 58 | "max": 10.0, 59 | "step": 0.05 60 | }), 61 | "scalelist_behavior": (["poses", "images"], {"default": "poses", "tooltip": "When the scale input is a list, this determines how the scale list takes effect, the differences appear when there are multiple persons(poses) in one image."}), 62 | "match_scalelist_method": (["no extend", "loop extend", "clamp extend"], {"default": "loop extend", "tooltip": "Match the scale list to the input poses or images when the scale list length is shorter. No extend: Beyound the scale list will be 1.0. Loop: Loop the scale list to match the poses or images length. Clamp: Use the last scale value to extend the scale list."}), 63 | "only_scale_pose_index": ("INT", { 64 | "default": 99, 65 | "min": -100, 66 | "max": 100, 67 | "tooltip": "For multiple poses in one image, the scale will be only applied at desired index. If set to a number larger than the number of poses in the image, the scale will be applied to all poses. Negative number will apply to the pose from the end." 68 | }), 69 | "POSE_JSON": ("STRING", {"multiline": True}), 70 | "POSE_KEYPOINT": ("POSE_KEYPOINT",{"default": None}), 71 | }, 72 | } 73 | 74 | RETURN_NAMES = ("POSE_IMAGE", "POSE_KEYPOINT", "POSE_JSON") 75 | RETURN_TYPES = ("IMAGE", "POSE_KEYPOINT", "STRING") 76 | OUTPUT_NODE = True 77 | FUNCTION = "load_pose" 78 | CATEGORY = "ultimate-openpose" 79 | 80 | def load_pose(self, show_body, show_face, show_hands, resolution_x, pose_marker_size, face_marker_size, hand_marker_size, hands_scale, body_scale, head_scale, overall_scale, scalelist_behavior, match_scalelist_method, only_scale_pose_index, POSE_JSON: str, POSE_KEYPOINT=None) -> tuple[OpenposeJSON]: 81 | ''' 82 | priority output is: POSE_JSON > POSE_KEYPOINT 83 | priority edit is: POSE_KEYPOINT > POSE_JSON 84 | ''' 85 | if POSE_JSON: 86 | POSE_JSON = POSE_JSON.replace("'",'"').replace('None','[]') 87 | POSE_PASS = POSE_JSON 88 | if POSE_KEYPOINT is not None: 89 | POSE_PASS = json.dumps(POSE_KEYPOINT,indent=4).replace("'",'"').replace('None','[]') 90 | hands_scalelist, body_scalelist, head_scalelist, overall_scalelist = extend_scalelist( 91 | scalelist_behavior, POSE_PASS, hands_scale, body_scale, head_scale, overall_scale, 92 | match_scalelist_method, only_scale_pose_index) 93 | pose_imgs, POSE_PASS = draw_pose_json(POSE_PASS, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size, hands_scalelist, body_scalelist, head_scalelist, overall_scalelist) 94 | 95 | # parse the JSON 96 | hands_scalelist, body_scalelist, head_scalelist, overall_scalelist = extend_scalelist( 97 | scalelist_behavior, POSE_JSON, hands_scale, body_scale, head_scale, overall_scale, 98 | match_scalelist_method, only_scale_pose_index) 99 | pose_imgs, POSE_JSON_SCALED = draw_pose_json(POSE_JSON, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size, hands_scalelist, body_scalelist, head_scalelist, overall_scalelist) 100 | if pose_imgs: 101 | pose_imgs_np = np.array(pose_imgs).astype(np.float32) / 255 102 | return { 103 | "ui": {"POSE_JSON": [json.dumps(POSE_PASS, indent=4)]}, 104 | "result": (torch.from_numpy(pose_imgs_np), POSE_JSON_SCALED, json.dumps(POSE_JSON_SCALED,indent=4)) 105 | } 106 | elif POSE_KEYPOINT is not None: 107 | POSE_JSON = json.dumps(POSE_KEYPOINT,indent=4).replace("'",'"').replace('None','[]') 108 | hands_scalelist, body_scalelist, head_scalelist, overall_scalelist = extend_scalelist( 109 | scalelist_behavior, POSE_JSON, hands_scale, body_scale, head_scale, overall_scale, 110 | match_scalelist_method, only_scale_pose_index) 111 | normalized_pose_json = pose_normalized(POSE_JSON) 112 | pose_imgs, POSE_SCALED = draw_pose_json(normalized_pose_json, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size, hands_scalelist, body_scalelist, head_scalelist, overall_scalelist) 113 | if pose_imgs: 114 | pose_imgs_np = np.array(pose_imgs).astype(np.float32) / 255 115 | return { 116 | "ui": {"POSE_JSON": [json.dumps(POSE_SCALED, indent=4)]}, 117 | "result": (torch.from_numpy(pose_imgs_np), POSE_SCALED, json.dumps(POSE_SCALED, indent=4)) 118 | } 119 | 120 | # otherwise output blank images 121 | W=512 122 | H=768 123 | pose_draw = dict(bodies={'candidate':[], 'subset':[]}, faces=[], hands=[]) 124 | pose_out = dict(pose_keypoints_2d=[], face_keypoints_2d=[], hand_left_keypoints_2d=[], hand_right_keypoints_2d=[]) 125 | people=[dict(people=[pose_out], canvas_height=H, canvas_width=W)] 126 | 127 | W_scaled = resolution_x 128 | if resolution_x < 64: 129 | W_scaled = W 130 | H_scaled = int(H*(W_scaled*1.0/W)) 131 | pose_img = [draw_pose(pose_draw, H_scaled, W_scaled, pose_marker_size, face_marker_size, hand_marker_size)] 132 | pose_img_np = np.array(pose_img).astype(np.float32) / 255 133 | 134 | return { 135 | "ui": {"POSE_JSON": people}, 136 | "result": (torch.from_numpy(pose_img_np), people, json.dumps(people)) 137 | } 138 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "ComfyUI-ultimate-openpose-editor" 3 | description = "Enhanced features with flexible choice of inputs and outputs, fine control for pose plotting, freedom to composite poses and fast local pose editing. Both UI and procedural pose editting." 4 | version = "1.1.0" 5 | license = { file = "LICENSE"} 6 | dependencies = ["torch", "polygraphy", "numpy", "opencv-python", "matplotlib"] 7 | 8 | [project.urls] 9 | Repository = "https://github.com/westNeighbor/ComfyUI-ultimate-openpose-editor" 10 | # Used by Comfy Registry https://comfyregistry.org 11 | 12 | [tool.comfy] 13 | PublisherId = "west-neighbor" 14 | DisplayName = "ComfyUI-ultimate-openpose-editor" 15 | Icon = "" 16 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | polygraphy 2 | matplotlib 3 | numpy 4 | opencv-python 5 | torch 6 | -------------------------------------------------------------------------------- /util.py: -------------------------------------------------------------------------------- 1 | import math 2 | import json 3 | import numpy as np 4 | import matplotlib 5 | import cv2 6 | from comfy.utils import ProgressBar 7 | from typing import List, Dict 8 | 9 | eps = 0.01 10 | 11 | def extend_scalelist(scalelist_behavior, pose_json, hands_scale, body_scale, head_scale, overall_scale, match_scalelist_method, only_scale_pose_index) -> List[list]: 12 | if pose_json.startswith('{'): 13 | pose_json = '[{}]'.format(pose_json) 14 | poses = json.loads(pose_json) 15 | # initialize scale lists 16 | hands_scalelist, body_scalelist, head_scalelist, overall_scalelist = [], [], [], [] 17 | num_imgs = 0 18 | num_poses = 0 19 | scale_values = [hands_scale, body_scale, head_scale, overall_scale] 20 | scale_lists = [hands_scalelist, body_scalelist, head_scalelist, overall_scalelist] 21 | for img in poses: 22 | default_scale = 0.0 23 | default_num_person = 1 24 | if 'people' in img: 25 | default_scale = 1.0 26 | default_num_person = len(img['people']) 27 | subscales = [default_scale]*default_num_person 28 | if scalelist_behavior == 'poses': 29 | for i, scales in enumerate(scale_values): 30 | if isinstance(scales, (list, tuple)): 31 | if len(scales) >= num_poses + default_num_person: 32 | if only_scale_pose_index= -default_num_person: 33 | subscales[only_scale_pose_index] = scales[num_poses + only_scale_pose_index] 34 | else: 35 | subscales = scales[num_poses:num_poses + default_num_person] 36 | else: 37 | if match_scalelist_method == 'no extend': 38 | subscales = [default_scale]*default_num_person 39 | elif match_scalelist_method == 'loop extend': 40 | extend_scaleslist = scales*math.ceil((num_poses+default_num_person) / len(scales)) 41 | if only_scale_pose_index= -default_num_person: 42 | subscales[only_scale_pose_index] = extend_scaleslist[num_poses + only_scale_pose_index] 43 | else: 44 | subscales = extend_scaleslist[num_poses:num_poses + default_num_person] 45 | elif match_scalelist_method == 'clamp extend': 46 | if only_scale_pose_index= -default_num_person: 47 | subscales[only_scale_pose_index] = scales[-1] 48 | else: 49 | subscales = [scales[-1]] * default_num_person 50 | else: 51 | if only_scale_pose_index= -default_num_person: 52 | subscales[only_scale_pose_index] = scales 53 | else: 54 | subscales = [scales] * default_num_person 55 | 56 | scale_lists[i].append(subscales.copy()) 57 | else: 58 | for i, scales in enumerate(scale_values): 59 | if isinstance(scales, (list, tuple)): 60 | if len(scales) >= num_imgs + 1: 61 | if only_scale_pose_index= -default_num_person: 62 | subscales[only_scale_pose_index] = scales[num_imgs] 63 | else: 64 | subscales = scales[num_poses]*default_num_person 65 | else: 66 | if match_scalelist_method == 'no extend': 67 | subscales = [default_scale]*default_num_person 68 | elif match_scalelist_method == 'loop extend': 69 | extend_scaleslist = scales*math.ceil((num_imgs+1) / len(scales)) 70 | if only_scale_pose_index= -default_num_person: 71 | subscales[only_scale_pose_index] = extend_scaleslist[num_imgs] 72 | else: 73 | subscales = extend_scaleslist[num_imgs]*default_num_person 74 | elif match_scalelist_method == 'clamp extend': 75 | if only_scale_pose_index= -default_num_person: 76 | subscales[only_scale_pose_index] = scales[-1] 77 | else: 78 | subscales = [scales[-1]] * default_num_person 79 | else: 80 | if only_scale_pose_index= -default_num_person: 81 | subscales[only_scale_pose_index] = scales 82 | else: 83 | subscales = [scales] * default_num_person 84 | 85 | scale_lists[i].append(subscales.copy()) 86 | 87 | num_poses += default_num_person 88 | num_imgs += 1 89 | else: 90 | # if no people in image 91 | for i in range(len(scale_values)): 92 | scale_lists[i].append([default_scale]) 93 | 94 | return scale_lists 95 | 96 | def pose_normalized(pose_json): 97 | if pose_json.startswith('{'): 98 | pose_json = '[{}]'.format(pose_json) 99 | images = json.loads(pose_json) 100 | for image in images: 101 | if 'people' not in image: 102 | continue 103 | figures = image['people'] 104 | H = image['canvas_height'] 105 | W = image['canvas_width'] 106 | normalized = 0.0 107 | for figure in figures: 108 | if 'pose_keypoints_2d' in figure: 109 | body = figure['pose_keypoints_2d'] 110 | if body: 111 | normalized = max(body) 112 | if normalized > 2.0: 113 | break 114 | if 'face_keypoints_2d' in figure: 115 | face = figure['face_keypoints_2d'] 116 | if face: 117 | normalized = max(face) 118 | if normalized > 2.0: 119 | break 120 | if 'hand_left_keypoints_2d' in figure: 121 | lhand = figure['hand_left_keypoints_2d'] 122 | if lhand: 123 | normalized = max(lhand) 124 | if normalized > 2.0: 125 | break 126 | if 'hand_right_keypoints_2d' in figure: 127 | rhand = figure['hand_right_keypoints_2d'] 128 | if rhand: 129 | normalized = max(rhand) 130 | if normalized > 2.0: 131 | break 132 | if normalized > 2.0: 133 | for figure in figures: 134 | if 'pose_keypoints_2d' in figure: 135 | body = figure['pose_keypoints_2d'] 136 | for i in range(0, len(body), 3): 137 | body[i] = body[i] / float(W) 138 | body[i+1] = body[i+1] / float(H) 139 | if 'face_keypoints_2d' in figure: 140 | face = figure['face_keypoints_2d'] 141 | for i in range(0, len(face), 3): 142 | face[i] = face[i] / float(W) 143 | face[i+1] = face[i+1] / float(H) 144 | if 'hand_left_keypoints_2d' in figure: 145 | lhand = figure['hand_left_keypoints_2d'] 146 | for i in range(0, len(lhand), 3): 147 | lhand[i] = lhand[i] / float(W) 148 | lhand[i+1] = lhand[i+1] / float(H) 149 | if 'hand_right_keypoints_2d' in figure: 150 | rhand = figure['hand_right_keypoints_2d'] 151 | for i in range(0, len(rhand), 3): 152 | rhand[i] = rhand[i] / float(W) 153 | rhand[i+1] = rhand[i+1] / float(H) 154 | return json.dumps(images) 155 | 156 | def scale(point, scale_factor, pivot): 157 | return [(point[i] - pivot[i])*scale_factor + pivot[i] for i in range(len(point))] 158 | 159 | def draw_pose_json(pose_json, resolution_x, show_body, show_face, show_hands, pose_marker_size, face_marker_size, hand_marker_size, hands_scalelist, body_scalelist, head_scalelist, overall_scalelist): 160 | pose_imgs = [] 161 | pose_scaled = [] 162 | 163 | if pose_json: 164 | if pose_json.startswith('{'): 165 | pose_json = '[{}]'.format(pose_json) 166 | images = json.loads(pose_json) 167 | pbar = ProgressBar(len(images)) 168 | for img_idx, image in enumerate(images): 169 | if 'people' not in image: 170 | pbar.update(len(images)) 171 | return pose_imgs 172 | figures = image['people'] 173 | H = image['canvas_height'] 174 | W = image['canvas_width'] 175 | 176 | bodies = [] 177 | candidate = [] 178 | subset = [[]] 179 | faces = [] 180 | hands = [] 181 | 182 | openpose_json = [] 183 | for pose_idx, figure in enumerate(figures): 184 | body_scale = body_scalelist[img_idx][pose_idx] 185 | hands_scale = hands_scalelist[img_idx][pose_idx] 186 | head_scale = head_scalelist[img_idx][pose_idx] 187 | overall_scale = overall_scalelist[img_idx][pose_idx] 188 | body = [] 189 | face = [] 190 | lhand = [] 191 | rhand = [] 192 | if 'pose_keypoints_2d' in figure: 193 | body = figure['pose_keypoints_2d'] 194 | body_scaled = body.copy() 195 | if 'face_keypoints_2d' in figure: 196 | face = figure['face_keypoints_2d'] 197 | face_scaled = face.copy() 198 | if 'hand_left_keypoints_2d' in figure: 199 | lhand = figure['hand_left_keypoints_2d'] 200 | lhand_scaled = lhand.copy() 201 | if 'hand_right_keypoints_2d' in figure: 202 | rhand = figure['hand_right_keypoints_2d'] 203 | rhand_scaled = rhand.copy() 204 | 205 | face_offset = [0, 0] 206 | lhand_offset = [0, 0] 207 | rhand_offset = [0, 0] 208 | 209 | overall_pivot = [0.5, 0.5] 210 | lhand_pivot = [0.25, 0.5] 211 | rhand_pivot = [0.75, 0.5] 212 | face_pivot = [0.5, 0.5] 213 | 214 | if body: 215 | candidate_start_idx = len(candidate) 216 | 217 | for i in range(0,len(body),3): 218 | p_scaled = scale(body[i:i+2], body_scale, overall_pivot) 219 | p_scaled = scale(p_scaled, overall_scale, overall_pivot) 220 | body_scaled[i:i+2] = p_scaled 221 | candidate.append(p_scaled) 222 | 223 | figure_head_idx = candidate_start_idx 224 | if figure_head_idx < len(candidate): 225 | factor = 0.8 226 | face_offset = [(candidate[figure_head_idx][0] - body[0])*factor, (candidate[figure_head_idx][1] - body[1])*factor] 227 | face_pivot = candidate[figure_head_idx] 228 | 229 | wrist_left_idx = candidate_start_idx + 7 230 | wrist_right_idx = candidate_start_idx + 4 231 | 232 | if wrist_left_idx < len(candidate) and len(body) > 22: 233 | lhand_offset = [candidate[wrist_left_idx][0] - body[21], candidate[wrist_left_idx][1] - body[22]] 234 | lhand_pivot = candidate[wrist_left_idx] 235 | 236 | if wrist_right_idx < len(candidate) and len(body) > 13: 237 | rhand_offset = [candidate[wrist_right_idx][0] - body[12], candidate[wrist_right_idx][1] - body[13]] 238 | rhand_pivot = candidate[wrist_right_idx] 239 | 240 | if not subset[0]: 241 | subset[0].extend([candidate_start_idx+(i//3) if body[i+2]>0 else -1 for i in range(0,len(body),3)]) 242 | else: 243 | new_subset = [candidate_start_idx+(i//3) if body[i+2]>0 else -1 for i in range(0,len(body),3)] 244 | subset.append(new_subset) 245 | 246 | if face: 247 | f = [] 248 | for i in range(0,len(face),3): 249 | p = face[i:i+2] 250 | p_offset = [p[0] + face_offset[0], p[1] + face_offset[1]] 251 | p_scaled = scale(p_offset, head_scale, face_pivot) 252 | p_scaled = scale(p_scaled, overall_scale, overall_pivot) 253 | face_scaled[i:i+2] = p_scaled 254 | f.append(p_scaled) 255 | faces.append(f) 256 | 257 | if lhand: 258 | lh = [] 259 | for i in range(0, len(lhand), 3): 260 | p = lhand[i:i+2] 261 | p_offset = [p[0] + lhand_offset[0], p[1] + lhand_offset[1]] 262 | p_scaled = scale(p_offset, hands_scale, lhand_pivot) 263 | p_scaled = scale(p_scaled, overall_scale, overall_pivot) 264 | lhand_scaled[i:i+2] = p_scaled 265 | lh.append(p_scaled) 266 | hands.append(lh) 267 | 268 | if rhand: 269 | rh = [] 270 | for i in range(0, len(rhand), 3): 271 | p = rhand[i:i+2] 272 | p_offset = [p[0] + rhand_offset[0], p[1] + rhand_offset[1]] 273 | p_scaled = scale(p_offset, hands_scale, rhand_pivot) 274 | p_scaled = scale(p_scaled, overall_scale, overall_pivot) 275 | rhand_scaled[i:i+2] = p_scaled 276 | rh.append(p_scaled) 277 | hands.append(rh) 278 | openpose_json.append(dict(pose_keypoints_2d=body_scaled, face_keypoints_2d=face_scaled, hand_left_keypoints_2d=lhand_scaled, hand_right_keypoints_2d=rhand_scaled)) 279 | 280 | bodies = dict(candidate=candidate, subset=subset) 281 | pose = dict(bodies=bodies, faces=faces, hands=hands) 282 | pose = dict(bodies=bodies if show_body else {'candidate':[], 'subset':[]}, faces=faces if show_face else [], hands=hands if show_hands else []) 283 | 284 | W_scaled = resolution_x 285 | if resolution_x < 64: 286 | W_scaled = W 287 | H_scaled = int(H*(W_scaled*1.0/W)) 288 | openpose_json = { 289 | 'people': openpose_json, 290 | 'canvas_height': H_scaled, 291 | 'canvas_width': W_scaled, 292 | } 293 | 294 | pose_img = draw_pose(pose, H_scaled, W_scaled, pose_marker_size, face_marker_size, hand_marker_size) 295 | pose_imgs.append(pose_img) 296 | pose_scaled.append(openpose_json) 297 | pbar.update(1) 298 | 299 | return pose_imgs, pose_scaled 300 | 301 | def draw_pose(pose, H, W, pose_marker_size, face_marker_size, hand_marker_size): 302 | bodies = pose['bodies'] 303 | faces = pose['faces'] 304 | hands = pose['hands'] 305 | candidate = bodies['candidate'] 306 | subset = bodies['subset'] 307 | canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8) 308 | 309 | if len(candidate) > 0: 310 | canvas = draw_bodypose(canvas, candidate, subset, pose_marker_size) 311 | 312 | if len(hands) > 0: 313 | canvas = draw_handpose(canvas, hands, hand_marker_size) 314 | 315 | if len(faces) > 0: 316 | canvas = draw_facepose(canvas, faces, face_marker_size) 317 | 318 | return canvas 319 | 320 | def draw_bodypose(canvas, candidate, subset, pose_marker_size): 321 | H, W, C = canvas.shape 322 | candidate = np.array(candidate) 323 | subset = np.array(subset) 324 | 325 | # stickwidth = 4 326 | 327 | limbSeq = [[2, 3], [2, 6], [3, 4], [4, 5], [6, 7], [7, 8], [2, 9], [9, 10], \ 328 | [10, 11], [2, 12], [12, 13], [13, 14], [2, 1], [1, 15], [15, 17], \ 329 | [1, 16], [16, 18], [3, 17], [6, 18]] 330 | 331 | colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0], [255, 255, 0], [170, 255, 0], [85, 255, 0], [0, 255, 0], \ 332 | [0, 255, 85], [0, 255, 170], [0, 255, 255], [0, 170, 255], [0, 85, 255], [0, 0, 255], [85, 0, 255], \ 333 | [170, 0, 255], [255, 0, 255], [255, 0, 170], [255, 0, 85]] 334 | 335 | for i in range(17): 336 | for n in range(len(subset)): 337 | index = subset[n][np.array(limbSeq[i]) - 1] 338 | if -1 in index: 339 | continue 340 | Y = candidate[index.astype(int), 0] * float(W) 341 | X = candidate[index.astype(int), 1] * float(H) 342 | mX = np.mean(X) 343 | mY = np.mean(Y) 344 | length = ((X[0] - X[1]) ** 2 + (Y[0] - Y[1]) ** 2) ** 0.5 345 | angle = math.degrees(math.atan2(X[0] - X[1], Y[0] - Y[1])) 346 | polygon = cv2.ellipse2Poly((int(mY), int(mX)), (int(length / 2), pose_marker_size), int(angle), 0, 360, 1) 347 | cv2.fillConvexPoly(canvas, polygon, colors[i]) 348 | 349 | canvas = (canvas * 0.6).astype(np.uint8) 350 | 351 | for i in range(18): 352 | for n in range(len(subset)): 353 | index = int(subset[n][i]) 354 | if index == -1: 355 | continue 356 | x, y = candidate[index][0:2] 357 | x = int(x * W) 358 | y = int(y * H) 359 | cv2.circle(canvas, (int(x), int(y)), pose_marker_size, colors[i], thickness=-1) 360 | 361 | return canvas 362 | 363 | 364 | def draw_handpose(canvas, all_hand_peaks, hand_marker_size): 365 | H, W, C = canvas.shape 366 | 367 | edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \ 368 | [10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]] 369 | 370 | for peaks in all_hand_peaks: 371 | peaks = np.array(peaks) 372 | 373 | for ie, e in enumerate(edges): 374 | x1, y1 = peaks[e[0]] 375 | x2, y2 = peaks[e[1]] 376 | x1 = int(x1 * W) 377 | y1 = int(y1 * H) 378 | x2 = int(x2 * W) 379 | y2 = int(y2 * H) 380 | if x1 > eps and y1 > eps and x2 > eps and y2 > eps: 381 | cv2.line(canvas, (x1, y1), (x2, y2), matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * 255, thickness=1 if hand_marker_size == 0 else hand_marker_size) 382 | 383 | joint_size=0 384 | if hand_marker_size < 2: 385 | joint_size = hand_marker_size + 1 386 | else: 387 | joint_size = hand_marker_size + 2 388 | for i, keyponit in enumerate(peaks): 389 | x, y = keyponit 390 | x = int(x * W) 391 | y = int(y * H) 392 | if x > eps and y > eps: 393 | cv2.circle(canvas, (x, y), joint_size, (0, 0, 255), thickness=-1) 394 | return canvas 395 | 396 | 397 | def draw_facepose(canvas, all_lmks, face_marker_size): 398 | H, W, C = canvas.shape 399 | for lmks in all_lmks: 400 | lmks = np.array(lmks) 401 | for lmk in lmks: 402 | x, y = lmk 403 | x = int(x * W) 404 | y = int(y * H) 405 | if x > eps and y > eps: 406 | cv2.circle(canvas, (x, y), face_marker_size, (255, 255, 255), thickness=-1) 407 | return canvas 408 | --------------------------------------------------------------------------------