710 lines
32 KiB
Python
710 lines
32 KiB
Python
# Openpose
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# Original from CMU https://github.com/CMU-Perceptual-Computing-Lab/openpose
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# 2nd Edited by https://github.com/Hzzone/pytorch-openpose
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# 3rd Edited by ControlNet
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# 4th Edited by ControlNet (added face and correct hands)
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import os
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os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
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import cv2
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import torch
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import numpy as np
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import json
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import copy
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import torch
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import random
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import argparse
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import shutil
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import tempfile
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import subprocess
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import numpy as np
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import math
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import torch.multiprocessing as mp
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import torch.distributed as dist
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# import pickle
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import logging
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# from io import BytesIO
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# import oss2 as oss
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# import os.path as osp
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import sys
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from .dwpose import util
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from .dwpose.wholebody import Wholebody
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def smoothing_factor(t_e, cutoff):
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r = 2 * math.pi * cutoff * t_e
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return r / (r + 1)
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def exponential_smoothing(a, x, x_prev):
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return a * x + (1 - a) * x_prev
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class OneEuroFilter:
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def __init__(self, t0, x0, dx0=0.0, min_cutoff=1.0, beta=0.0,
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d_cutoff=1.0):
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"""Initialize the one euro filter."""
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# The parameters.
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self.min_cutoff = float(min_cutoff)
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self.beta = float(beta)
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self.d_cutoff = float(d_cutoff)
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# Previous values.
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self.x_prev = x0
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self.dx_prev = float(dx0)
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self.t_prev = float(t0)
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def __call__(self, t, x):
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"""Compute the filtered signal."""
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t_e = t - self.t_prev
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# The filtered derivative of the signal.
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a_d = smoothing_factor(t_e, self.d_cutoff)
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dx = (x - self.x_prev) / t_e
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dx_hat = exponential_smoothing(a_d, dx, self.dx_prev)
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# The filtered signal.
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cutoff = self.min_cutoff + self.beta * abs(dx_hat)
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a = smoothing_factor(t_e, cutoff)
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x_hat = exponential_smoothing(a, x, self.x_prev)
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# Memorize the previous values.
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self.x_prev = x_hat
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self.dx_prev = dx_hat
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self.t_prev = t
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return x_hat
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def get_logger(name="essmc2"):
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logger = logging.getLogger(name)
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logger.propagate = False
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if len(logger.handlers) == 0:
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std_handler = logging.StreamHandler(sys.stdout)
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formatter = logging.Formatter(
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'%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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std_handler.setFormatter(formatter)
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std_handler.setLevel(logging.INFO)
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logger.setLevel(logging.INFO)
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logger.addHandler(std_handler)
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return logger
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class DWposeDetector:
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def __init__(self):
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self.pose_estimation = Wholebody()
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def __call__(self, oriImg):
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oriImg = oriImg.copy()
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# print(f'The shape of the image should be in HWC format but it is currently: {oriImg.shape} ')
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H, W, C = oriImg.shape
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with torch.no_grad():
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candidate, subset = self.pose_estimation(oriImg)
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candidate = candidate[0][np.newaxis, :, :]
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subset = subset[0][np.newaxis, :]
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nums, keys, locs = candidate.shape
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candidate[..., 0] /= float(W)
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candidate[..., 1] /= float(H)
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body = candidate[:,:18].copy()
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body = body.reshape(nums*18, locs)
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score = subset[:,:18].copy()
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for i in range(len(score)):
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for j in range(len(score[i])):
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if score[i][j] > 0.3:
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score[i][j] = int(18*i+j)
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else:
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score[i][j] = -1
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un_visible = subset<0.3
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candidate[un_visible] = -1
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bodyfoot_score = subset[:,:24].copy()
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for i in range(len(bodyfoot_score)):
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for j in range(len(bodyfoot_score[i])):
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if bodyfoot_score[i][j] > 0.3:
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bodyfoot_score[i][j] = int(18*i+j)
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else:
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bodyfoot_score[i][j] = -1
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if -1 not in bodyfoot_score[:,18] and -1 not in bodyfoot_score[:,19]:
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bodyfoot_score[:,18] = np.array([18.])
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else:
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bodyfoot_score[:,18] = np.array([-1.])
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if -1 not in bodyfoot_score[:,21] and -1 not in bodyfoot_score[:,22]:
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bodyfoot_score[:,19] = np.array([19.])
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else:
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bodyfoot_score[:,19] = np.array([-1.])
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bodyfoot_score = bodyfoot_score[:, :20]
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bodyfoot = candidate[:,:24].copy()
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for i in range(nums):
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if -1 not in bodyfoot[i][18] and -1 not in bodyfoot[i][19]:
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bodyfoot[i][18] = (bodyfoot[i][18]+bodyfoot[i][19])/2
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else:
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bodyfoot[i][18] = np.array([-1., -1.])
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if -1 not in bodyfoot[i][21] and -1 not in bodyfoot[i][22]:
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bodyfoot[i][19] = (bodyfoot[i][21]+bodyfoot[i][22])/2
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else:
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bodyfoot[i][19] = np.array([-1., -1.])
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bodyfoot = bodyfoot[:,:20,:]
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bodyfoot = bodyfoot.reshape(nums*20, locs)
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foot = candidate[:,18:24]
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faces = candidate[:,24:92]
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hands = candidate[:,92:113]
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hands = np.vstack([hands, candidate[:,113:]])
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# bodies = dict(candidate=body, subset=score)
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bodies = dict(candidate=bodyfoot, subset=bodyfoot_score)
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pose = dict(bodies=bodies, hands=hands, faces=faces)
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# return draw_pose(pose, H, W)
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return pose
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def draw_pose(pose, H, W):
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bodies = pose['bodies']
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faces = pose['faces']
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hands = pose['hands']
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candidate = bodies['candidate']
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subset = bodies['subset']
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canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8)
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canvas = util.draw_body_and_foot(canvas, candidate, subset)
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canvas = util.draw_handpose(canvas, hands)
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canvas_without_face = copy.deepcopy(canvas)
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canvas = util.draw_facepose(canvas, faces)
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return canvas_without_face, canvas
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def dw_func(_id, frame, dwpose_model, dwpose_woface_folder='tmp_dwpose_wo_face', dwpose_withface_folder='tmp_dwpose_with_face'):
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# frame = cv2.imread(frame_name, cv2.IMREAD_COLOR)
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pose = dwpose_model(frame)
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return pose
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def mp_main(reference_image, video):
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logger.info(f"There are {video.size(0)} frames for extracting poses")
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logger.info('LOAD: DW Pose Model')
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dwpose_model = DWposeDetector()
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results_vis = []
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num_frames = video.size(0)
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for i in range(num_frames):
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logger.info(f"Processing frame {i + 1}/{num_frames}")
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frame = video[i].permute(0, 1, 2).cpu().numpy()*255 # Convert to HWC format and numpy array
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frame = np.flip(frame, axis=2)
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pose = dw_func(i, frame, dwpose_model)
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results_vis.append(pose)
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logger.info(f'All frames have been processed.')
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print(len(results_vis))
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# Process the reference image
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ref_frame = reference_image.squeeze(0).cpu().numpy()*255 # Convert to HWC format and numpy array
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ref_frame = np.flip(ref_frame, axis=2)
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pose_ref = dw_func(-1, ref_frame, dwpose_model)
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# print(f'The content of the image is currently: {pose_ref} ')
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bodies = results_vis[0]['bodies']
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faces = results_vis[0]['faces']
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hands = results_vis[0]['hands']
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candidate = bodies['candidate']
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ref_bodies = pose_ref['bodies']
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ref_faces = pose_ref['faces']
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ref_hands = pose_ref['hands']
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ref_candidate = ref_bodies['candidate']
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ref_2_x = ref_candidate[2][0]
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ref_2_y = ref_candidate[2][1]
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ref_5_x = ref_candidate[5][0]
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ref_5_y = ref_candidate[5][1]
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ref_8_x = ref_candidate[8][0]
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ref_8_y = ref_candidate[8][1]
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ref_11_x = ref_candidate[11][0]
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ref_11_y = ref_candidate[11][1]
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ref_center1 = 0.5*(ref_candidate[2]+ref_candidate[5])
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ref_center2 = 0.5*(ref_candidate[8]+ref_candidate[11])
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zero_2_x = candidate[2][0]
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zero_2_y = candidate[2][1]
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zero_5_x = candidate[5][0]
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zero_5_y = candidate[5][1]
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zero_8_x = candidate[8][0]
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zero_8_y = candidate[8][1]
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zero_11_x = candidate[11][0]
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zero_11_y = candidate[11][1]
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zero_center1 = 0.5*(candidate[2]+candidate[5])
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zero_center2 = 0.5*(candidate[8]+candidate[11])
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x_ratio, y_ratio = 1, 1
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if (zero_5_x-zero_2_x) > 0 :
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x_ratio = (ref_5_x-ref_2_x)/(zero_5_x-zero_2_x)
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if (zero_center2[1]-zero_center1[1]) > 0 :
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y_ratio = (ref_center2[1]-ref_center1[1])/(zero_center2[1]-zero_center1[1])
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results_vis[0]['bodies']['candidate'][:,0] *= x_ratio
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results_vis[0]['bodies']['candidate'][:,1] *= y_ratio
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results_vis[0]['faces'][:,:,0] *= x_ratio
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results_vis[0]['faces'][:,:,1] *= y_ratio
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results_vis[0]['hands'][:,:,0] *= x_ratio
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results_vis[0]['hands'][:,:,1] *= y_ratio
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########neck########
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neck_ratio = 1
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l_neck_ref = ((ref_candidate[0][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[0][1] - ref_candidate[1][1]) ** 2) ** 0.5
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l_neck_0 = ((candidate[0][0] - candidate[1][0]) ** 2 + (candidate[0][1] - candidate[1][1]) ** 2) ** 0.5
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if l_neck_0 != 0:
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neck_ratio = l_neck_ref / l_neck_0
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x_offset_neck = (candidate[1][0]-candidate[0][0])*(1.-neck_ratio)
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y_offset_neck = (candidate[1][1]-candidate[0][1])*(1.-neck_ratio)
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results_vis[0]['bodies']['candidate'][0,0] += x_offset_neck
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results_vis[0]['bodies']['candidate'][0,1] += y_offset_neck
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results_vis[0]['bodies']['candidate'][14,0] += x_offset_neck
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results_vis[0]['bodies']['candidate'][14,1] += y_offset_neck
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results_vis[0]['bodies']['candidate'][15,0] += x_offset_neck
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results_vis[0]['bodies']['candidate'][15,1] += y_offset_neck
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results_vis[0]['bodies']['candidate'][16,0] += x_offset_neck
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results_vis[0]['bodies']['candidate'][16,1] += y_offset_neck
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results_vis[0]['bodies']['candidate'][17,0] += x_offset_neck
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results_vis[0]['bodies']['candidate'][17,1] += y_offset_neck
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########shoulder2########
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shoulder2_ratio = 1
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l_shoulder2_ref = ((ref_candidate[2][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[2][1] - ref_candidate[1][1]) ** 2) ** 0.5
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l_shoulder2_0 = ((candidate[2][0] - candidate[1][0]) ** 2 + (candidate[2][1] - candidate[1][1]) ** 2) ** 0.5
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if l_shoulder2_0 != 0:
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shoulder2_ratio = l_shoulder2_ref / l_shoulder2_0
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x_offset_shoulder2 = (candidate[1][0]-candidate[2][0])*(1.-shoulder2_ratio)
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y_offset_shoulder2 = (candidate[1][1]-candidate[2][1])*(1.-shoulder2_ratio)
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results_vis[0]['bodies']['candidate'][2,0] += x_offset_shoulder2
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results_vis[0]['bodies']['candidate'][2,1] += y_offset_shoulder2
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results_vis[0]['bodies']['candidate'][3,0] += x_offset_shoulder2
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results_vis[0]['bodies']['candidate'][3,1] += y_offset_shoulder2
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results_vis[0]['bodies']['candidate'][4,0] += x_offset_shoulder2
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results_vis[0]['bodies']['candidate'][4,1] += y_offset_shoulder2
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results_vis[0]['hands'][1,:,0] += x_offset_shoulder2
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results_vis[0]['hands'][1,:,1] += y_offset_shoulder2
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########shoulder5########
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shoulder5_ratio = 1
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l_shoulder5_ref = ((ref_candidate[5][0] - ref_candidate[1][0]) ** 2 + (ref_candidate[5][1] - ref_candidate[1][1]) ** 2) ** 0.5
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l_shoulder5_0 = ((candidate[5][0] - candidate[1][0]) ** 2 + (candidate[5][1] - candidate[1][1]) ** 2) ** 0.5
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if l_shoulder5_0 != 0:
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shoulder5_ratio = l_shoulder5_ref / l_shoulder5_0
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x_offset_shoulder5 = (candidate[1][0]-candidate[5][0])*(1.-shoulder5_ratio)
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y_offset_shoulder5 = (candidate[1][1]-candidate[5][1])*(1.-shoulder5_ratio)
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results_vis[0]['bodies']['candidate'][5,0] += x_offset_shoulder5
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results_vis[0]['bodies']['candidate'][5,1] += y_offset_shoulder5
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results_vis[0]['bodies']['candidate'][6,0] += x_offset_shoulder5
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results_vis[0]['bodies']['candidate'][6,1] += y_offset_shoulder5
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results_vis[0]['bodies']['candidate'][7,0] += x_offset_shoulder5
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results_vis[0]['bodies']['candidate'][7,1] += y_offset_shoulder5
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results_vis[0]['hands'][0,:,0] += x_offset_shoulder5
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results_vis[0]['hands'][0,:,1] += y_offset_shoulder5
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########arm3########
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arm3_ratio = 1
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l_arm3_ref = ((ref_candidate[3][0] - ref_candidate[2][0]) ** 2 + (ref_candidate[3][1] - ref_candidate[2][1]) ** 2) ** 0.5
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l_arm3_0 = ((candidate[3][0] - candidate[2][0]) ** 2 + (candidate[3][1] - candidate[2][1]) ** 2) ** 0.5
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if l_arm3_0 != 0:
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arm3_ratio = l_arm3_ref / l_arm3_0
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x_offset_arm3 = (candidate[2][0]-candidate[3][0])*(1.-arm3_ratio)
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y_offset_arm3 = (candidate[2][1]-candidate[3][1])*(1.-arm3_ratio)
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results_vis[0]['bodies']['candidate'][3,0] += x_offset_arm3
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results_vis[0]['bodies']['candidate'][3,1] += y_offset_arm3
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results_vis[0]['bodies']['candidate'][4,0] += x_offset_arm3
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results_vis[0]['bodies']['candidate'][4,1] += y_offset_arm3
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results_vis[0]['hands'][1,:,0] += x_offset_arm3
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results_vis[0]['hands'][1,:,1] += y_offset_arm3
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########arm4########
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arm4_ratio = 1
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l_arm4_ref = ((ref_candidate[4][0] - ref_candidate[3][0]) ** 2 + (ref_candidate[4][1] - ref_candidate[3][1]) ** 2) ** 0.5
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l_arm4_0 = ((candidate[4][0] - candidate[3][0]) ** 2 + (candidate[4][1] - candidate[3][1]) ** 2) ** 0.5
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if l_arm4_0 != 0:
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arm4_ratio = l_arm4_ref / l_arm4_0
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x_offset_arm4 = (candidate[3][0]-candidate[4][0])*(1.-arm4_ratio)
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y_offset_arm4 = (candidate[3][1]-candidate[4][1])*(1.-arm4_ratio)
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results_vis[0]['bodies']['candidate'][4,0] += x_offset_arm4
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results_vis[0]['bodies']['candidate'][4,1] += y_offset_arm4
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results_vis[0]['hands'][1,:,0] += x_offset_arm4
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results_vis[0]['hands'][1,:,1] += y_offset_arm4
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########arm6########
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arm6_ratio = 1
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l_arm6_ref = ((ref_candidate[6][0] - ref_candidate[5][0]) ** 2 + (ref_candidate[6][1] - ref_candidate[5][1]) ** 2) ** 0.5
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l_arm6_0 = ((candidate[6][0] - candidate[5][0]) ** 2 + (candidate[6][1] - candidate[5][1]) ** 2) ** 0.5
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if l_arm6_0 != 0:
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arm6_ratio = l_arm6_ref / l_arm6_0
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x_offset_arm6 = (candidate[5][0]-candidate[6][0])*(1.-arm6_ratio)
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y_offset_arm6 = (candidate[5][1]-candidate[6][1])*(1.-arm6_ratio)
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results_vis[0]['bodies']['candidate'][6,0] += x_offset_arm6
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results_vis[0]['bodies']['candidate'][6,1] += y_offset_arm6
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results_vis[0]['bodies']['candidate'][7,0] += x_offset_arm6
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results_vis[0]['bodies']['candidate'][7,1] += y_offset_arm6
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results_vis[0]['hands'][0,:,0] += x_offset_arm6
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results_vis[0]['hands'][0,:,1] += y_offset_arm6
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########arm7########
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arm7_ratio = 1
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l_arm7_ref = ((ref_candidate[7][0] - ref_candidate[6][0]) ** 2 + (ref_candidate[7][1] - ref_candidate[6][1]) ** 2) ** 0.5
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l_arm7_0 = ((candidate[7][0] - candidate[6][0]) ** 2 + (candidate[7][1] - candidate[6][1]) ** 2) ** 0.5
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if l_arm7_0 != 0:
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arm7_ratio = l_arm7_ref / l_arm7_0
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x_offset_arm7 = (candidate[6][0]-candidate[7][0])*(1.-arm7_ratio)
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y_offset_arm7 = (candidate[6][1]-candidate[7][1])*(1.-arm7_ratio)
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results_vis[0]['bodies']['candidate'][7,0] += x_offset_arm7
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results_vis[0]['bodies']['candidate'][7,1] += y_offset_arm7
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results_vis[0]['hands'][0,:,0] += x_offset_arm7
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results_vis[0]['hands'][0,:,1] += y_offset_arm7
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########head14########
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l_head14_ref = ((ref_candidate[14][0] - ref_candidate[0][0]) ** 2 + (ref_candidate[14][1] - ref_candidate[0][1]) ** 2) ** 0.5
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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########
|
|
ll1_ratio = 1
|
|
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
|
|
if l_ll1_0 != 0 :
|
|
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########
|
|
rl1_ratio = 1
|
|
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
|
|
if l_rl1_0 != 0:
|
|
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, :]
|
|
|
|
# Prepare to return the dwpose images
|
|
dwpose_images = []
|
|
|
|
for i in range(len(results_vis)):
|
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dwpose_woface, _ = draw_pose(results_vis[i], H=768, W=512)
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dwpose_tensor = torch.from_numpy(dwpose_woface).permute(2, 0, 1).unsqueeze(0).float() # Convert to tensor and CHW format
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dwpose_tensor = dwpose_tensor.permute(0, 2, 3, 1)
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dwpose_images.append(dwpose_tensor)
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dwpose_images = torch.cat(dwpose_images, dim=0)
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dwpose_woface_ref, _ = draw_pose(pose_ref, H=768, W=512)
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dwpose_ref_tensor = torch.from_numpy(dwpose_woface_ref).permute(2, 0, 1).unsqueeze(0).float() # Convert to tensor and CHW format
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dwpose_ref_tensor = dwpose_ref_tensor.permute(0, 2, 3, 1)
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# print(f'The type of the pose from run_align_pose is currently of the form : {type(dwpose_ref_tensor)} ')
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# print(f'The content of the pose from run_align_pose is currently: {dwpose_ref_tensor} ')
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return dwpose_images, dwpose_ref_tensor
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logger = get_logger('dw pose extraction')
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