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grmchn-ComfyUI-ProportionCh…/utils/dwpose_core.py
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gear_machineandClaude 142f043a63 Fix import structure: resolve nodes.py/nodes/ directory naming conflict 
- Rename nodes/ directory to proportion_changer/ following ComfyUI conventions
- Update __init__.py to use simple relative imports instead of importlib.util
- Fix nodes.py imports to reference .proportion_changer instead of .nodes
- Resolve ImportError caused by Python module vs package name collision
- Follow established ComfyUI custom node patterns (similar to adv_control/)

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-17 05:44:00 +09:00

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"""
DWPose core functionality including detector, transformer update, and pose extraction
"""
import torch
import torch.nn as nn
import numpy as np
import copy
from tqdm import tqdm
import comfy.model_management as mm
from comfy.utils import ProgressBar
# Import the UniAnimate DWPose components
from ..unianimate.dwpose.wholebody import Wholebody
def update_transformer(transformer, state_dict):
concat_dim = 4
transformer.dwpose_embedding = nn.Sequential(
nn.Conv3d(3, concat_dim * 4, (3,3,3), stride=(1,1,1), padding=(1,1,1)),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, concat_dim * 4, (3,3,3), stride=(1,1,1), padding=(1,1,1)),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, concat_dim * 4, (3,3,3), stride=(1,1,1), padding=(1,1,1)),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, concat_dim * 4, (3,3,3), stride=(1,2,2), padding=(1,1,1)),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, concat_dim * 4, 3, stride=(2,2,2), padding=1),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, concat_dim * 4, 3, stride=(2,2,2), padding=1),
nn.SiLU(),
nn.Conv3d(concat_dim * 4, 5120, (1,2,2), stride=(1,2,2), padding=0))
randomref_dim = 20
transformer.randomref_embedding_pose = nn.Sequential(
nn.Conv2d(3, concat_dim * 4, 3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(concat_dim * 4, concat_dim * 4, 3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(concat_dim * 4, concat_dim * 4, 3, stride=1, padding=1),
nn.SiLU(),
nn.Conv2d(concat_dim * 4, concat_dim * 4, 3, stride=2, padding=1),
nn.SiLU(),
nn.Conv2d(concat_dim * 4, concat_dim * 4, 3, stride=2, padding=1),
nn.SiLU(),
nn.Conv2d(concat_dim * 4, randomref_dim, 3, stride=2, padding=1),
)
state_dict_new = {}
for key in list(state_dict.keys()):
if "dwpose_embedding" in key:
state_dict_new[key.split("dwpose_embedding.")[1]] = state_dict.pop(key)
transformer.dwpose_embedding.load_state_dict(state_dict_new, strict=True)
state_dict_new = {}
for key in list(state_dict.keys()):
if "randomref_embedding_pose" in key:
state_dict_new[key.split("randomref_embedding_pose.")[1]] = state_dict.pop(key)
transformer.randomref_embedding_pose.load_state_dict(state_dict_new,strict=True)
return transformer
class DWposeDetector:
def __init__(self, model_det, model_pose):
self.pose_estimation = Wholebody(model_det, model_pose)
def __call__(self, oriImg, score_threshold=0.3):
oriImg = oriImg.copy()
H, W, C = oriImg.shape
with torch.no_grad():
candidate, subset = self.pose_estimation(oriImg)
candidate = candidate[0][np.newaxis, :, :]
subset = subset[0][np.newaxis, :]
nums, keys, locs = candidate.shape
candidate[..., 0] /= float(W)
candidate[..., 1] /= float(H)
body = candidate[:,:18].copy()
body = body.reshape(nums*18, locs)
score = subset[:,:18].copy()
for i in range(len(score)):
for j in range(len(score[i])):
if score[i][j] > score_threshold:
score[i][j] = int(18*i+j)
else:
score[i][j] = -1
un_visible = subset<score_threshold
candidate[un_visible] = -1
bodyfoot_score = subset[:,:24].copy()
for i in range(len(bodyfoot_score)):
for j in range(len(bodyfoot_score[i])):
if bodyfoot_score[i][j] > score_threshold:
bodyfoot_score[i][j] = int(18*i+j)
else:
bodyfoot_score[i][j] = -1
if -1 not in bodyfoot_score[:,18] and -1 not in bodyfoot_score[:,19]:
bodyfoot_score[:,18] = np.array([18.])
else:
bodyfoot_score[:,18] = np.array([-1.])
if -1 not in bodyfoot_score[:,21] and -1 not in bodyfoot_score[:,22]:
bodyfoot_score[:,19] = np.array([19.])
else:
bodyfoot_score[:,19] = np.array([-1.])
bodyfoot_score = bodyfoot_score[:, :20]
bodyfoot = candidate[:,:24].copy()
for i in range(nums):
if -1 not in bodyfoot[i][18] and -1 not in bodyfoot[i][19]:
bodyfoot[i][18] = (bodyfoot[i][18]+bodyfoot[i][19])/2
else:
bodyfoot[i][18] = np.array([-1., -1.])
if -1 not in bodyfoot[i][21] and -1 not in bodyfoot[i][22]:
bodyfoot[i][19] = (bodyfoot[i][21]+bodyfoot[i][22])/2
else:
bodyfoot[i][19] = np.array([-1., -1.])
bodyfoot = bodyfoot[:,:20,:]
bodyfoot = bodyfoot.reshape(nums*20, locs)
foot = candidate[:,18:24]
faces = candidate[:,24:92]
hands = candidate[:,92:113]
hands = np.vstack([hands, candidate[:,113:]])
# bodies = dict(candidate=body, subset=score)
bodies = dict(candidate=bodyfoot, subset=bodyfoot_score)
pose = dict(bodies=bodies, hands=hands, faces=faces)
# return draw_pose(pose, H, W)
return pose
def draw_pose(pose, H, W, stick_width=4,draw_body=True, draw_hands=True, draw_feet=True,
body_keypoint_size=4, hand_keypoint_size=4, draw_head=True):
from ..unianimate.dwpose.util import draw_body_and_foot, draw_handpose, draw_facepose
bodies = pose['bodies']
faces = pose['faces']
hands = pose['hands']
candidate = bodies['candidate']
subset = bodies['subset']
canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8)
canvas = draw_body_and_foot(canvas, candidate, subset, draw_body=draw_body, stick_width=stick_width, draw_feet=draw_feet, draw_head=draw_head, body_keypoint_size=body_keypoint_size)
canvas = draw_handpose(canvas, hands, draw_hands=draw_hands, hand_keypoint_size=hand_keypoint_size)
canvas_without_face = copy.deepcopy(canvas)
canvas = draw_facepose(canvas, faces)
return canvas_without_face, canvas
def pose_extract(pose_images, ref_image, dwpose_model, height, width, score_threshold, stick_width,
draw_body=True, draw_hands=True, hand_keypoint_size=4, draw_feet=True,
body_keypoint_size=4, handle_not_detected="repeat", draw_head=True):
results_vis = []
comfy_pbar = ProgressBar(len(pose_images))
if ref_image is not None:
try:
pose_ref = dwpose_model(ref_image.squeeze(0), score_threshold=score_threshold)
except:
raise ValueError("No pose detected in reference image")
prev_pose = None
for img in tqdm(pose_images, desc="Pose Extraction", unit="image", total=len(pose_images)):
try:
pose = dwpose_model(img, score_threshold=score_threshold)
if handle_not_detected == "repeat":
prev_pose = pose
except:
if prev_pose is not None:
pose = prev_pose
else:
pose = np.zeros_like(img)
results_vis.append(pose)
comfy_pbar.update(1)
bodies = results_vis[0]['bodies']
faces = results_vis[0]['faces']
hands = results_vis[0]['hands']
candidate = bodies['candidate']
if ref_image is not None:
ref_bodies = pose_ref['bodies']
ref_faces = pose_ref['faces']
ref_hands = pose_ref['hands']
ref_candidate = ref_bodies['candidate']
ref_2_x = ref_candidate[2][0]
ref_2_y = ref_candidate[2][1]
ref_5_x = ref_candidate[5][0]
ref_5_y = ref_candidate[5][1]
ref_8_x = ref_candidate[8][0]
ref_8_y = ref_candidate[8][1]
ref_11_x = ref_candidate[11][0]
ref_11_y = ref_candidate[11][1]
ref_center1 = 0.5*(ref_candidate[2]+ref_candidate[5])
ref_center2 = 0.5*(ref_candidate[8]+ref_candidate[11])
zero_2_x = candidate[2][0]
zero_2_y = candidate[2][1]
zero_5_x = candidate[5][0]
zero_5_y = candidate[5][1]
zero_8_x = candidate[8][0]
zero_8_y = candidate[8][1]
zero_11_x = candidate[11][0]
zero_11_y = candidate[11][1]
zero_center1 = 0.5*(candidate[2]+candidate[5])
zero_center2 = 0.5*(candidate[8]+candidate[11])
x_ratio = (ref_5_x-ref_2_x)/(zero_5_x-zero_2_x)
y_ratio = (ref_center2[1]-ref_center1[1])/(zero_center2[1]-zero_center1[1])
results_vis[0]['bodies']['candidate'][:,0] *= x_ratio
results_vis[0]['bodies']['candidate'][:,1] *= y_ratio
results_vis[0]['faces'][:,:,0] *= x_ratio
results_vis[0]['faces'][:,:,1] *= y_ratio
results_vis[0]['hands'][:,:,0] *= x_ratio
results_vis[0]['hands'][:,:,1] *= y_ratio
########neck########
l_neck_ref = ((ref_candidate[0][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[0][1] - ref_candidate[1][1]) ** 2) ** 0.5
l_neck_0 = ((candidate[0][0] - candidate[1][0]) ** 2 + (candidate[0][1] - candidate[1][1]) ** 2) ** 0.5
neck_ratio = l_neck_ref / l_neck_0
x_offset_neck = (candidate[1][0]-candidate[0][0])*(1.-neck_ratio)
y_offset_neck = (candidate[1][1]-candidate[0][1])*(1.-neck_ratio)
results_vis[0]['bodies']['candidate'][0,0] += x_offset_neck
results_vis[0]['bodies']['candidate'][0,1] += y_offset_neck
results_vis[0]['bodies']['candidate'][14,0] += x_offset_neck
results_vis[0]['bodies']['candidate'][14,1] += y_offset_neck
results_vis[0]['bodies']['candidate'][15,0] += x_offset_neck
results_vis[0]['bodies']['candidate'][15,1] += y_offset_neck
results_vis[0]['bodies']['candidate'][16,0] += x_offset_neck
results_vis[0]['bodies']['candidate'][16,1] += y_offset_neck
results_vis[0]['bodies']['candidate'][17,0] += x_offset_neck
results_vis[0]['bodies']['candidate'][17,1] += y_offset_neck
########shoulder2########
l_shoulder2_ref = ((ref_candidate[2][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[2][1] - ref_candidate[1][1]) ** 2) ** 0.5
l_shoulder2_0 = ((candidate[2][0] - candidate[1][0]) ** 2 + (candidate[2][1] - candidate[1][1]) ** 2) ** 0.5
shoulder2_ratio = l_shoulder2_ref / l_shoulder2_0
x_offset_shoulder2 = (candidate[1][0]-candidate[2][0])*(1.-shoulder2_ratio)
y_offset_shoulder2 = (candidate[1][1]-candidate[2][1])*(1.-shoulder2_ratio)
results_vis[0]['bodies']['candidate'][2,0] += x_offset_shoulder2
results_vis[0]['bodies']['candidate'][2,1] += y_offset_shoulder2
results_vis[0]['bodies']['candidate'][3,0] += x_offset_shoulder2
results_vis[0]['bodies']['candidate'][3,1] += y_offset_shoulder2
results_vis[0]['bodies']['candidate'][4,0] += x_offset_shoulder2
results_vis[0]['bodies']['candidate'][4,1] += y_offset_shoulder2
results_vis[0]['hands'][1,:,0] += x_offset_shoulder2
results_vis[0]['hands'][1,:,1] += y_offset_shoulder2
########shoulder5########
l_shoulder5_ref = ((ref_candidate[5][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[5][1] - ref_candidate[1][1]) ** 2) ** 0.5
l_shoulder5_0 = ((candidate[5][0] - candidate[1][0]) ** 2 + (candidate[5][1] - candidate[1][1]) ** 2) ** 0.5
shoulder5_ratio = l_shoulder5_ref / l_shoulder5_0
x_offset_shoulder5 = (candidate[1][0]-candidate[5][0])*(1.-shoulder5_ratio)
y_offset_shoulder5 = (candidate[1][1]-candidate[5][1])*(1.-shoulder5_ratio)
results_vis[0]['bodies']['candidate'][5,0] += x_offset_shoulder5
results_vis[0]['bodies']['candidate'][5,1] += y_offset_shoulder5
results_vis[0]['bodies']['candidate'][6,0] += x_offset_shoulder5
results_vis[0]['bodies']['candidate'][6,1] += y_offset_shoulder5
results_vis[0]['bodies']['candidate'][7,0] += x_offset_shoulder5
results_vis[0]['bodies']['candidate'][7,1] += y_offset_shoulder5
results_vis[0]['hands'][0,:,0] += x_offset_shoulder5
results_vis[0]['hands'][0,:,1] += y_offset_shoulder5
########arm3########
l_arm3_ref = ((ref_candidate[3][0] - ref_candidate[2][0]) ** 2 + (ref_candidate[3][1] - ref_candidate[2][1]) ** 2) ** 0.5
l_arm3_0 = ((candidate[3][0] - candidate[2][0]) ** 2 + (candidate[3][1] - candidate[2][1]) ** 2) ** 0.5
arm3_ratio = l_arm3_ref / l_arm3_0
x_offset_arm3 = (candidate[2][0]-candidate[3][0])*(1.-arm3_ratio)
y_offset_arm3 = (candidate[2][1]-candidate[3][1])*(1.-arm3_ratio)
results_vis[0]['bodies']['candidate'][3,0] += x_offset_arm3
results_vis[0]['bodies']['candidate'][3,1] += y_offset_arm3
results_vis[0]['bodies']['candidate'][4,0] += x_offset_arm3
results_vis[0]['bodies']['candidate'][4,1] += y_offset_arm3
results_vis[0]['hands'][1,:,0] += x_offset_arm3
results_vis[0]['hands'][1,:,1] += y_offset_arm3
########arm4########
l_arm4_ref = ((ref_candidate[4][0] - ref_candidate[3][0]) ** 2 + (ref_candidate[4][1] - ref_candidate[3][1]) ** 2) ** 0.5
l_arm4_0 = ((candidate[4][0] - candidate[3][0]) ** 2 + (candidate[4][1] - candidate[3][1]) ** 2) ** 0.5
arm4_ratio = l_arm4_ref / l_arm4_0
x_offset_arm4 = (candidate[3][0]-candidate[4][0])*(1.-arm4_ratio)
y_offset_arm4 = (candidate[3][1]-candidate[4][1])*(1.-arm4_ratio)
results_vis[0]['bodies']['candidate'][4,0] += x_offset_arm4
results_vis[0]['bodies']['candidate'][4,1] += y_offset_arm4
results_vis[0]['hands'][1,:,0] += x_offset_arm4
results_vis[0]['hands'][1,:,1] += y_offset_arm4
########arm6########
l_arm6_ref = ((ref_candidate[6][0] - ref_candidate[5][0]) ** 2 + (ref_candidate[6][1] - ref_candidate[5][1]) ** 2) ** 0.5
l_arm6_0 = ((candidate[6][0] - candidate[5][0]) ** 2 + (candidate[6][1] - candidate[5][1]) ** 2) ** 0.5
arm6_ratio = l_arm6_ref / l_arm6_0
x_offset_arm6 = (candidate[5][0]-candidate[6][0])*(1.-arm6_ratio)
y_offset_arm6 = (candidate[5][1]-candidate[6][1])*(1.-arm6_ratio)
results_vis[0]['bodies']['candidate'][6,0] += x_offset_arm6
results_vis[0]['bodies']['candidate'][6,1] += y_offset_arm6
results_vis[0]['bodies']['candidate'][7,0] += x_offset_arm6
results_vis[0]['bodies']['candidate'][7,1] += y_offset_arm6
results_vis[0]['hands'][0,:,0] += x_offset_arm6
results_vis[0]['hands'][0,:,1] += y_offset_arm6
########arm7########
l_arm7_ref = ((ref_candidate[7][0] - ref_candidate[6][0]) ** 2 + (ref_candidate[7][1] - ref_candidate[6][1]) ** 2) ** 0.5
l_arm7_0 = ((candidate[7][0] - candidate[6][0]) ** 2 + (candidate[7][1] - candidate[6][1]) ** 2) ** 0.5
arm7_ratio = l_arm7_ref / l_arm7_0
x_offset_arm7 = (candidate[6][0]-candidate[7][0])*(1.-arm7_ratio)
y_offset_arm7 = (candidate[6][1]-candidate[7][1])*(1.-arm7_ratio)
results_vis[0]['bodies']['candidate'][7,0] += x_offset_arm7
results_vis[0]['bodies']['candidate'][7,1] += y_offset_arm7
results_vis[0]['hands'][0,:,0] += x_offset_arm7
results_vis[0]['hands'][0,:,1] += y_offset_arm7
########head14########
l_head14_ref = ((ref_candidate[14][0] - ref_candidate[0][0]) ** 2 + (ref_candidate[14][1] - ref_candidate[0][1]) ** 2) ** 0.5
l_head14_0 = ((candidate[14][0] - candidate[0][0]) ** 2 + (candidate[14][1] - candidate[0][1]) ** 2) ** 0.5
head14_ratio = l_head14_ref / l_head14_0
x_offset_head14 = (candidate[0][0]-candidate[14][0])*(1.-head14_ratio)
y_offset_head14 = (candidate[0][1]-candidate[14][1])*(1.-head14_ratio)
results_vis[0]['bodies']['candidate'][14,0] += x_offset_head14
results_vis[0]['bodies']['candidate'][14,1] += y_offset_head14
results_vis[0]['bodies']['candidate'][16,0] += x_offset_head14
results_vis[0]['bodies']['candidate'][16,1] += y_offset_head14
########head15########
l_head15_ref = ((ref_candidate[15][0] - ref_candidate[0][0]) ** 2 + (ref_candidate[15][1] - ref_candidate[0][1]) ** 2) ** 0.5
l_head15_0 = ((candidate[15][0] - candidate[0][0]) ** 2 + (candidate[15][1] - candidate[0][1]) ** 2) ** 0.5
head15_ratio = l_head15_ref / l_head15_0
x_offset_head15 = (candidate[0][0]-candidate[15][0])*(1.-head15_ratio)
y_offset_head15 = (candidate[0][1]-candidate[15][1])*(1.-head15_ratio)
results_vis[0]['bodies']['candidate'][15,0] += x_offset_head15
results_vis[0]['bodies']['candidate'][15,1] += y_offset_head15
results_vis[0]['bodies']['candidate'][17,0] += x_offset_head15
results_vis[0]['bodies']['candidate'][17,1] += y_offset_head15
########head16########
l_head16_ref = ((ref_candidate[16][0] - ref_candidate[14][0]) ** 2 + (ref_candidate[16][1] - ref_candidate[14][1]) ** 2) ** 0.5
l_head16_0 = ((candidate[16][0] - candidate[14][0]) ** 2 + (candidate[16][1] - candidate[14][1]) ** 2) ** 0.5
head16_ratio = l_head16_ref / l_head16_0
x_offset_head16 = (candidate[14][0]-candidate[16][0])*(1.-head16_ratio)
y_offset_head16 = (candidate[14][1]-candidate[16][1])*(1.-head16_ratio)
results_vis[0]['bodies']['candidate'][16,0] += x_offset_head16
results_vis[0]['bodies']['candidate'][16,1] += y_offset_head16
########head17########
l_head17_ref = ((ref_candidate[17][0] - ref_candidate[15][0]) ** 2 + (ref_candidate[17][1] - ref_candidate[15][1]) ** 2) ** 0.5
l_head17_0 = ((candidate[17][0] - candidate[15][0]) ** 2 + (candidate[17][1] - candidate[15][1]) ** 2) ** 0.5
head17_ratio = l_head17_ref / l_head17_0
x_offset_head17 = (candidate[15][0]-candidate[17][0])*(1.-head17_ratio)
y_offset_head17 = (candidate[15][1]-candidate[17][1])*(1.-head17_ratio)
results_vis[0]['bodies']['candidate'][17,0] += x_offset_head17
results_vis[0]['bodies']['candidate'][17,1] += y_offset_head17
########MovingAverage########
########left leg########
l_ll1_ref = ((ref_candidate[8][0] - ref_candidate[9][0]) ** 2 + (ref_candidate[8][1] - ref_candidate[9][1]) ** 2) ** 0.5
l_ll1_0 = ((candidate[8][0] - candidate[9][0]) ** 2 + (candidate[8][1] - candidate[9][1]) ** 2) ** 0.5
ll1_ratio = l_ll1_ref / l_ll1_0
x_offset_ll1 = (candidate[9][0]-candidate[8][0])*(ll1_ratio-1.)
y_offset_ll1 = (candidate[9][1]-candidate[8][1])*(ll1_ratio-1.)
results_vis[0]['bodies']['candidate'][9,0] += x_offset_ll1
results_vis[0]['bodies']['candidate'][9,1] += y_offset_ll1
results_vis[0]['bodies']['candidate'][10,0] += x_offset_ll1
results_vis[0]['bodies']['candidate'][10,1] += y_offset_ll1
results_vis[0]['bodies']['candidate'][19,0] += x_offset_ll1
results_vis[0]['bodies']['candidate'][19,1] += y_offset_ll1
l_ll2_ref = ((ref_candidate[9][0] - ref_candidate[10][0]) ** 2 + (ref_candidate[9][1] - ref_candidate[10][1]) ** 2) ** 0.5
l_ll2_0 = ((candidate[9][0] - candidate[10][0]) ** 2 + (candidate[9][1] - candidate[10][1]) ** 2) ** 0.5
ll2_ratio = l_ll2_ref / l_ll2_0
x_offset_ll2 = (candidate[10][0]-candidate[9][0])*(ll2_ratio-1.)
y_offset_ll2 = (candidate[10][1]-candidate[9][1])*(ll2_ratio-1.)
results_vis[0]['bodies']['candidate'][10,0] += x_offset_ll2
results_vis[0]['bodies']['candidate'][10,1] += y_offset_ll2
results_vis[0]['bodies']['candidate'][19,0] += x_offset_ll2
results_vis[0]['bodies']['candidate'][19,1] += y_offset_ll2
########right leg########
l_rl1_ref = ((ref_candidate[11][0] - ref_candidate[12][0]) ** 2 + (ref_candidate[11][1] - ref_candidate[12][1]) ** 2) ** 0.5
l_rl1_0 = ((candidate[11][0] - candidate[12][0]) ** 2 + (candidate[11][1] - candidate[12][1]) ** 2) ** 0.5
rl1_ratio = l_rl1_ref / l_rl1_0
x_offset_rl1 = (candidate[12][0]-candidate[11][0])*(rl1_ratio-1.)
y_offset_rl1 = (candidate[12][1]-candidate[11][1])*(rl1_ratio-1.)
results_vis[0]['bodies']['candidate'][12,0] += x_offset_rl1
results_vis[0]['bodies']['candidate'][12,1] += y_offset_rl1
results_vis[0]['bodies']['candidate'][13,0] += x_offset_rl1
results_vis[0]['bodies']['candidate'][13,1] += y_offset_rl1
results_vis[0]['bodies']['candidate'][18,0] += x_offset_rl1
results_vis[0]['bodies']['candidate'][18,1] += y_offset_rl1
l_rl2_ref = ((ref_candidate[12][0] - ref_candidate[13][0]) ** 2 + (ref_candidate[12][1] - ref_candidate[13][1]) ** 2) ** 0.5
l_rl2_0 = ((candidate[12][0] - candidate[13][0]) ** 2 + (candidate[12][1] - candidate[13][1]) ** 2) ** 0.5
rl2_ratio = l_rl2_ref / l_rl2_0
x_offset_rl2 = (candidate[13][0]-candidate[12][0])*(rl2_ratio-1.)
y_offset_rl2 = (candidate[13][1]-candidate[12][1])*(rl2_ratio-1.)
results_vis[0]['bodies']['candidate'][13,0] += x_offset_rl2
results_vis[0]['bodies']['candidate'][13,1] += y_offset_rl2
results_vis[0]['bodies']['candidate'][18,0] += x_offset_rl2
results_vis[0]['bodies']['candidate'][18,1] += y_offset_rl2
offset = ref_candidate[1] - results_vis[0]['bodies']['candidate'][1]
results_vis[0]['bodies']['candidate'] += offset[np.newaxis, :]
results_vis[0]['faces'] += offset[np.newaxis, np.newaxis, :]
results_vis[0]['hands'] += offset[np.newaxis, np.newaxis, :]
for i in range(1, len(results_vis)):
results_vis[i]['bodies']['candidate'][:,0] *= x_ratio
results_vis[i]['bodies']['candidate'][:,1] *= y_ratio
results_vis[i]['faces'][:,:,0] *= x_ratio
results_vis[i]['faces'][:,:,1] *= y_ratio
results_vis[i]['hands'][:,:,0] *= x_ratio
results_vis[i]['hands'][:,:,1] *= y_ratio
########neck########
x_offset_neck = (results_vis[i]['bodies']['candidate'][1][0]-results_vis[i]['bodies']['candidate'][0][0])*(1.-neck_ratio)
y_offset_neck = (results_vis[i]['bodies']['candidate'][1][1]-results_vis[i]['bodies']['candidate'][0][1])*(1.-neck_ratio)
results_vis[i]['bodies']['candidate'][0,0] += x_offset_neck
results_vis[i]['bodies']['candidate'][0,1] += y_offset_neck
results_vis[i]['bodies']['candidate'][14,0] += x_offset_neck
results_vis[i]['bodies']['candidate'][14,1] += y_offset_neck
results_vis[i]['bodies']['candidate'][15,0] += x_offset_neck
results_vis[i]['bodies']['candidate'][15,1] += y_offset_neck
results_vis[i]['bodies']['candidate'][16,0] += x_offset_neck
results_vis[i]['bodies']['candidate'][16,1] += y_offset_neck
results_vis[i]['bodies']['candidate'][17,0] += x_offset_neck
results_vis[i]['bodies']['candidate'][17,1] += y_offset_neck
########shoulder2########
x_offset_shoulder2 = (results_vis[i]['bodies']['candidate'][1][0]-results_vis[i]['bodies']['candidate'][2][0])*(1.-shoulder2_ratio)
y_offset_shoulder2 = (results_vis[i]['bodies']['candidate'][1][1]-results_vis[i]['bodies']['candidate'][2][1])*(1.-shoulder2_ratio)
results_vis[i]['bodies']['candidate'][2,0] += x_offset_shoulder2
results_vis[i]['bodies']['candidate'][2,1] += y_offset_shoulder2
results_vis[i]['bodies']['candidate'][3,0] += x_offset_shoulder2
results_vis[i]['bodies']['candidate'][3,1] += y_offset_shoulder2
results_vis[i]['bodies']['candidate'][4,0] += x_offset_shoulder2
results_vis[i]['bodies']['candidate'][4,1] += y_offset_shoulder2
results_vis[i]['hands'][1,:,0] += x_offset_shoulder2
results_vis[i]['hands'][1,:,1] += y_offset_shoulder2
########shoulder5########
x_offset_shoulder5 = (results_vis[i]['bodies']['candidate'][1][0]-results_vis[i]['bodies']['candidate'][5][0])*(1.-shoulder5_ratio)
y_offset_shoulder5 = (results_vis[i]['bodies']['candidate'][1][1]-results_vis[i]['bodies']['candidate'][5][1])*(1.-shoulder5_ratio)
results_vis[i]['bodies']['candidate'][5,0] += x_offset_shoulder5
results_vis[i]['bodies']['candidate'][5,1] += y_offset_shoulder5
results_vis[i]['bodies']['candidate'][6,0] += x_offset_shoulder5
results_vis[i]['bodies']['candidate'][6,1] += y_offset_shoulder5
results_vis[i]['bodies']['candidate'][7,0] += x_offset_shoulder5
results_vis[i]['bodies']['candidate'][7,1] += y_offset_shoulder5
results_vis[i]['hands'][0,:,0] += x_offset_shoulder5
results_vis[i]['hands'][0,:,1] += y_offset_shoulder5
########arm3########
x_offset_arm3 = (results_vis[i]['bodies']['candidate'][2][0]-results_vis[i]['bodies']['candidate'][3][0])*(1.-arm3_ratio)
y_offset_arm3 = (results_vis[i]['bodies']['candidate'][2][1]-results_vis[i]['bodies']['candidate'][3][1])*(1.-arm3_ratio)
results_vis[i]['bodies']['candidate'][3,0] += x_offset_arm3
results_vis[i]['bodies']['candidate'][3,1] += y_offset_arm3
results_vis[i]['bodies']['candidate'][4,0] += x_offset_arm3
results_vis[i]['bodies']['candidate'][4,1] += y_offset_arm3
results_vis[i]['hands'][1,:,0] += x_offset_arm3
results_vis[i]['hands'][1,:,1] += y_offset_arm3
########arm4########
x_offset_arm4 = (results_vis[i]['bodies']['candidate'][3][0]-results_vis[i]['bodies']['candidate'][4][0])*(1.-arm4_ratio)
y_offset_arm4 = (results_vis[i]['bodies']['candidate'][3][1]-results_vis[i]['bodies']['candidate'][4][1])*(1.-arm4_ratio)
results_vis[i]['bodies']['candidate'][4,0] += x_offset_arm4
results_vis[i]['bodies']['candidate'][4,1] += y_offset_arm4
results_vis[i]['hands'][1,:,0] += x_offset_arm4
results_vis[i]['hands'][1,:,1] += y_offset_arm4
########arm6########
x_offset_arm6 = (results_vis[i]['bodies']['candidate'][5][0]-results_vis[i]['bodies']['candidate'][6][0])*(1.-arm6_ratio)
y_offset_arm6 = (results_vis[i]['bodies']['candidate'][5][1]-results_vis[i]['bodies']['candidate'][6][1])*(1.-arm6_ratio)
results_vis[i]['bodies']['candidate'][6,0] += x_offset_arm6
results_vis[i]['bodies']['candidate'][6,1] += y_offset_arm6
results_vis[i]['bodies']['candidate'][7,0] += x_offset_arm6
results_vis[i]['bodies']['candidate'][7,1] += y_offset_arm6
results_vis[i]['hands'][0,:,0] += x_offset_arm6
results_vis[i]['hands'][0,:,1] += y_offset_arm6
########arm7########
x_offset_arm7 = (results_vis[i]['bodies']['candidate'][6][0]-results_vis[i]['bodies']['candidate'][7][0])*(1.-arm7_ratio)
y_offset_arm7 = (results_vis[i]['bodies']['candidate'][6][1]-results_vis[i]['bodies']['candidate'][7][1])*(1.-arm7_ratio)
results_vis[i]['bodies']['candidate'][7,0] += x_offset_arm7
results_vis[i]['bodies']['candidate'][7,1] += y_offset_arm7
results_vis[i]['hands'][0,:,0] += x_offset_arm7
results_vis[i]['hands'][0,:,1] += y_offset_arm7
########head14########
x_offset_head14 = (results_vis[i]['bodies']['candidate'][0][0]-results_vis[i]['bodies']['candidate'][14][0])*(1.-head14_ratio)
y_offset_head14 = (results_vis[i]['bodies']['candidate'][0][1]-results_vis[i]['bodies']['candidate'][14][1])*(1.-head14_ratio)
results_vis[i]['bodies']['candidate'][14,0] += x_offset_head14
results_vis[i]['bodies']['candidate'][14,1] += y_offset_head14
results_vis[i]['bodies']['candidate'][16,0] += x_offset_head14
results_vis[i]['bodies']['candidate'][16,1] += y_offset_head14
########head15########
x_offset_head15 = (results_vis[i]['bodies']['candidate'][0][0]-results_vis[i]['bodies']['candidate'][15][0])*(1.-head15_ratio)
y_offset_head15 = (results_vis[i]['bodies']['candidate'][0][1]-results_vis[i]['bodies']['candidate'][15][1])*(1.-head15_ratio)
results_vis[i]['bodies']['candidate'][15,0] += x_offset_head15
results_vis[i]['bodies']['candidate'][15,1] += y_offset_head15
results_vis[i]['bodies']['candidate'][17,0] += x_offset_head15
results_vis[i]['bodies']['candidate'][17,1] += y_offset_head15
########head16########
x_offset_head16 = (results_vis[i]['bodies']['candidate'][14][0]-results_vis[i]['bodies']['candidate'][16][0])*(1.-head16_ratio)
y_offset_head16 = (results_vis[i]['bodies']['candidate'][14][1]-results_vis[i]['bodies']['candidate'][16][1])*(1.-head16_ratio)
results_vis[i]['bodies']['candidate'][16,0] += x_offset_head16
results_vis[i]['bodies']['candidate'][16,1] += y_offset_head16
########head17########
x_offset_head17 = (results_vis[i]['bodies']['candidate'][15][0]-results_vis[i]['bodies']['candidate'][17][0])*(1.-head17_ratio)
y_offset_head17 = (results_vis[i]['bodies']['candidate'][15][1]-results_vis[i]['bodies']['candidate'][17][1])*(1.-head17_ratio)
results_vis[i]['bodies']['candidate'][17,0] += x_offset_head17
results_vis[i]['bodies']['candidate'][17,1] += y_offset_head17
# ########MovingAverage########
########left leg########
x_offset_ll1 = (results_vis[i]['bodies']['candidate'][9][0]-results_vis[i]['bodies']['candidate'][8][0])*(ll1_ratio-1.)
y_offset_ll1 = (results_vis[i]['bodies']['candidate'][9][1]-results_vis[i]['bodies']['candidate'][8][1])*(ll1_ratio-1.)
results_vis[i]['bodies']['candidate'][9,0] += x_offset_ll1
results_vis[i]['bodies']['candidate'][9,1] += y_offset_ll1
results_vis[i]['bodies']['candidate'][10,0] += x_offset_ll1
results_vis[i]['bodies']['candidate'][10,1] += y_offset_ll1
results_vis[i]['bodies']['candidate'][19,0] += x_offset_ll1
results_vis[i]['bodies']['candidate'][19,1] += y_offset_ll1
x_offset_ll2 = (results_vis[i]['bodies']['candidate'][10][0]-results_vis[i]['bodies']['candidate'][9][0])*(ll2_ratio-1.)
y_offset_ll2 = (results_vis[i]['bodies']['candidate'][10][1]-results_vis[i]['bodies']['candidate'][9][1])*(ll2_ratio-1.)
results_vis[i]['bodies']['candidate'][10,0] += x_offset_ll2
results_vis[i]['bodies']['candidate'][10,1] += y_offset_ll2
results_vis[i]['bodies']['candidate'][19,0] += x_offset_ll2
results_vis[i]['bodies']['candidate'][19,1] += y_offset_ll2
########right leg########
x_offset_rl1 = (results_vis[i]['bodies']['candidate'][12][0]-results_vis[i]['bodies']['candidate'][11][0])*(rl1_ratio-1.)
y_offset_rl1 = (results_vis[i]['bodies']['candidate'][12][1]-results_vis[i]['bodies']['candidate'][11][1])*(rl1_ratio-1.)
results_vis[i]['bodies']['candidate'][12,0] += x_offset_rl1
results_vis[i]['bodies']['candidate'][12,1] += y_offset_rl1
results_vis[i]['bodies']['candidate'][13,0] += x_offset_rl1
results_vis[i]['bodies']['candidate'][13,1] += y_offset_rl1
results_vis[i]['bodies']['candidate'][18,0] += x_offset_rl1
results_vis[i]['bodies']['candidate'][18,1] += y_offset_rl1
x_offset_rl2 = (results_vis[i]['bodies']['candidate'][13][0]-results_vis[i]['bodies']['candidate'][12][0])*(rl2_ratio-1.)
y_offset_rl2 = (results_vis[i]['bodies']['candidate'][13][1]-results_vis[i]['bodies']['candidate'][12][1])*(rl2_ratio-1.)
results_vis[i]['bodies']['candidate'][13,0] += x_offset_rl2
results_vis[i]['bodies']['candidate'][13,1] += y_offset_rl2
results_vis[i]['bodies']['candidate'][18,0] += x_offset_rl2
results_vis[i]['bodies']['candidate'][18,1] += y_offset_rl2
results_vis[i]['bodies']['candidate'] += offset[np.newaxis, :]
results_vis[i]['faces'] += offset[np.newaxis, np.newaxis, :]
results_vis[i]['hands'] += offset[np.newaxis, np.newaxis, :]
dwpose_woface_list = []
for i in range(len(results_vis)):
#try:
dwpose_woface, dwpose_wface = draw_pose(results_vis[i], H=height, W=width, stick_width=stick_width,
draw_body=draw_body, draw_hands=draw_hands, hand_keypoint_size=hand_keypoint_size,
draw_feet=draw_feet, body_keypoint_size=body_keypoint_size, draw_head=draw_head)
result = torch.from_numpy(dwpose_woface)
#except:
# result = torch.zeros((height, width, 3), dtype=torch.uint8)
dwpose_woface_list.append(result)
dwpose_woface_tensor = torch.stack(dwpose_woface_list, dim=0)
dwpose_woface_ref_tensor = None
if ref_image is not None:
dwpose_woface_ref, dwpose_wface_ref = draw_pose(pose_ref, H=height, W=width, stick_width=stick_width,
draw_body=draw_body, draw_hands=draw_hands, hand_keypoint_size=hand_keypoint_size,
draw_feet=draw_feet, body_keypoint_size=body_keypoint_size, draw_head=draw_head)
dwpose_woface_ref_tensor = torch.from_numpy(dwpose_woface_ref)
return dwpose_woface_tensor, dwpose_woface_ref_tensor
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