diff --git a/newWorkflows/image2VidLong.json b/newWorkflows/image2VidLong.json
new file mode 100644
index 0000000..96bbb2b
--- /dev/null
+++ b/newWorkflows/image2VidLong.json
@@ -0,0 +1,286 @@
+{
+  "last_node_id": 48,
+  "last_link_id": 87,
+  "nodes": [
+    {
+      "id": 43,
+      "type": "VHS_VideoCombine",
+      "pos": [
+        1243,
+        37
+      ],
+      "size": [
+        616.010364874865,
+        1198.0155473122975
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 86
+        },
+        {
+          "name": "audio",
+          "type": "VHS_AUDIO",
+          "link": null
+        },
+        {
+          "name": "meta_batch",
+          "type": "VHS_BatchManager",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "Filenames",
+          "type": "VHS_FILENAMES",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VHS_VideoCombine"
+      },
+      "widgets_values": {
+        "frame_rate": 30,
+        "loop_count": 0,
+        "filename_prefix": "AnimateDiff",
+        "format": "video/h264-mp4",
+        "pix_fmt": "yuv420p",
+        "crf": 19,
+        "save_metadata": true,
+        "pingpong": false,
+        "save_output": false,
+        "videopreview": {
+          "hidden": false,
+          "paused": false,
+          "params": {
+            "filename": "AnimateDiff_00003.mp4",
+            "subfolder": "",
+            "type": "temp",
+            "format": "video/h264-mp4"
+          }
+        }
+      }
+    },
+    {
+      "id": 10,
+      "type": "LoadImage",
+      "pos": [
+        253,
+        403
+      ],
+      "size": [
+        473.3907491038491,
+        810.0922180224138
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            83
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3,
+          "slot_index": 1
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "00004-3184066658.png",
+        "image"
+      ]
+    },
+    {
+      "id": 34,
+      "type": "VHS_LoadVideo",
+      "pos": [
+        862,
+        794
+      ],
+      "size": [
+        235.1999969482422,
+        658.5777723524305
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "meta_batch",
+          "type": "VHS_BatchManager",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            87
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "frame_count",
+          "type": "INT",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "audio",
+          "type": "VHS_AUDIO",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "video_info",
+          "type": "VHS_VIDEOINFO",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VHS_LoadVideo"
+      },
+      "widgets_values": {
+        "video": "0001-0032.mp4",
+        "force_rate": 0,
+        "force_size": "Disabled",
+        "custom_width": 512,
+        "custom_height": 512,
+        "frame_load_cap": 0,
+        "skip_first_frames": 0,
+        "select_every_nth": 1,
+        "choose video to upload": "image",
+        "videopreview": {
+          "hidden": false,
+          "paused": false,
+          "params": {
+            "frame_load_cap": 0,
+            "skip_first_frames": 0,
+            "force_rate": 0,
+            "filename": "0001-0032.mp4",
+            "type": "input",
+            "format": "video/mp4",
+            "select_every_nth": 1
+          }
+        }
+      }
+    },
+    {
+      "id": 48,
+      "type": "UniAnimateImageLong",
+      "pos": [
+        819,
+        408
+      ],
+      "size": {
+        "0": 315,
+        "1": 318
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 83
+        },
+        {
+          "name": "video",
+          "type": "IMAGE",
+          "link": 87
+        }
+      ],
+      "outputs": [
+        {
+          "name": "video",
+          "type": "IMAGE",
+          "links": [
+            86
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "poses",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "UniAnimateImageLong"
+      },
+      "widgets_values": [
+        7,
+        "fixed",
+        30,
+        false,
+        false,
+        1,
+        32,
+        1,
+        8,
+        1024000,
+        512
+      ]
+    }
+  ],
+  "links": [
+    [
+      83,
+      10,
+      0,
+      48,
+      0,
+      "IMAGE"
+    ],
+    [
+      86,
+      48,
+      0,
+      43,
+      0,
+      "IMAGE"
+    ],
+    [
+      87,
+      34,
+      0,
+      48,
+      1,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.7627768444385601,
+      "offset": [
+        763.4664376576395,
+        113.77478574061502
+      ]
+    }
+  },
+  "version": 0.4
+}
\ No newline at end of file
diff --git a/newWorkflows/reposeImgNew.json b/newWorkflows/reposeImgNew.json
new file mode 100644
index 0000000..6908e5e
--- /dev/null
+++ b/newWorkflows/reposeImgNew.json
@@ -0,0 +1,239 @@
+{
+  "last_node_id": 52,
+  "last_link_id": 91,
+  "nodes": [
+    {
+      "id": 50,
+      "type": "LoadImage",
+      "pos": [
+        843,
+        647
+      ],
+      "size": {
+        "0": 473.3907470703125,
+        "1": 810.0922241210938
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            89
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3,
+          "slot_index": 1
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "welcomeGirl512.png",
+        "image"
+      ]
+    },
+    {
+      "id": 52,
+      "type": "PreviewImage",
+      "pos": [
+        1993,
+        421
+      ],
+      "size": {
+        "0": 210,
+        "1": 246
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 91
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 51,
+      "type": "PreviewImage",
+      "pos": [
+        1386,
+        403
+      ],
+      "size": {
+        "0": 540.4281005859375,
+        "1": 954.2872924804688
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 90
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 10,
+      "type": "LoadImage",
+      "pos": [
+        255,
+        404
+      ],
+      "size": {
+        "0": 473.3907470703125,
+        "1": 810.0922241210938
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            88
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3,
+          "slot_index": 1
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "00008-4136189013.png",
+        "image"
+      ]
+    },
+    {
+      "id": 49,
+      "type": "ReposeImage",
+      "pos": [
+        922,
+        401
+      ],
+      "size": {
+        "0": 315,
+        "1": 174
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 88
+        },
+        {
+          "name": "pose",
+          "type": "IMAGE",
+          "link": 89
+        }
+      ],
+      "outputs": [
+        {
+          "name": "newPose",
+          "type": "IMAGE",
+          "links": [
+            90
+          ],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "pose",
+          "type": "IMAGE",
+          "links": [
+            91
+          ],
+          "shape": 3,
+          "slot_index": 1
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ReposeImage"
+      },
+      "widgets_values": [
+        7,
+        "fixed",
+        30,
+        false,
+        512
+      ]
+    }
+  ],
+  "links": [
+    [
+      88,
+      10,
+      0,
+      49,
+      0,
+      "IMAGE"
+    ],
+    [
+      89,
+      50,
+      0,
+      49,
+      1,
+      "IMAGE"
+    ],
+    [
+      90,
+      49,
+      0,
+      51,
+      0,
+      "IMAGE"
+    ],
+    [
+      91,
+      49,
+      1,
+      52,
+      0,
+      "IMAGE"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.9229599817706606,
+      "offset": [
+        150.87071252512646,
+        -219.3009555197075
+      ]
+    }
+  },
+  "version": 0.4
+}
\ No newline at end of file
diff --git a/run_align_posev2.py b/run_align_posev2.py
new file mode 100644
index 0000000..40e69d8
--- /dev/null
+++ b/run_align_posev2.py
@@ -0,0 +1,719 @@
+# Openpose
+# Original from CMU https://github.com/CMU-Perceptual-Computing-Lab/openpose
+# 2nd Edited by https://github.com/Hzzone/pytorch-openpose
+# 3rd Edited by ControlNet
+# 4th Edited by ControlNet (added face and correct hands)
+
+import os
+os.environ["KMP_DUPLICATE_LIB_OK"]="TRUE"
+import cv2
+import torch
+import numpy as np
+import json
+import copy
+import torch
+import random
+import argparse
+import shutil
+import tempfile
+import subprocess
+import numpy as np
+import math
+
+import torch.multiprocessing as mp
+import torch.distributed as dist
+# import pickle
+import logging
+# from io import BytesIO
+# import oss2 as oss
+# import os.path as osp
+
+import sys
+from .dwpose import util
+from .dwpose.wholebody import Wholebody
+
+
+def smoothing_factor(t_e, cutoff):
+    r = 2 * math.pi * cutoff * t_e
+    return r / (r + 1)
+
+
+def exponential_smoothing(a, x, x_prev):
+    return a * x + (1 - a) * x_prev
+
+
+class OneEuroFilter:
+    def __init__(self, t0, x0, dx0=0.0, min_cutoff=1.0, beta=0.0,
+                 d_cutoff=1.0):
+        """Initialize the one euro filter."""
+        # The parameters.
+        self.min_cutoff = float(min_cutoff)
+        self.beta = float(beta)
+        self.d_cutoff = float(d_cutoff)
+        # Previous values.
+        self.x_prev = x0
+        self.dx_prev = float(dx0)
+        self.t_prev = float(t0)
+
+    def __call__(self, t, x):
+        """Compute the filtered signal."""
+        t_e = t - self.t_prev
+
+        # The filtered derivative of the signal.
+        a_d = smoothing_factor(t_e, self.d_cutoff)
+        dx = (x - self.x_prev) / t_e
+        dx_hat = exponential_smoothing(a_d, dx, self.dx_prev)
+
+        # The filtered signal.
+        cutoff = self.min_cutoff + self.beta * abs(dx_hat)
+        a = smoothing_factor(t_e, cutoff)
+        x_hat = exponential_smoothing(a, x, self.x_prev)
+
+        # Memorize the previous values.
+        self.x_prev = x_hat
+        self.dx_prev = dx_hat
+        self.t_prev = t
+
+        return x_hat
+
+
+def get_logger(name="essmc2"):
+    logger = logging.getLogger(name)
+    logger.propagate = False
+    if len(logger.handlers) == 0:
+        std_handler = logging.StreamHandler(sys.stdout)
+        formatter = logging.Formatter(
+            '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+        std_handler.setFormatter(formatter)
+        std_handler.setLevel(logging.INFO)
+        logger.setLevel(logging.INFO)
+        logger.addHandler(std_handler)
+    return logger
+
+class DWposeDetector:
+    def __init__(self):
+
+        self.pose_estimation = Wholebody()
+
+    def __call__(self, oriImg):
+        oriImg = oriImg.copy()
+        # print(f'The shape of the image should be in HWC format but it is currently: {oriImg.shape} ')
+        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] > 0.3:
+                        score[i][j] = int(18*i+j)
+                    else:
+                        score[i][j] = -1
+
+            un_visible = subset<0.3
+            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] > 0.3:
+                        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):
+    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 = util.draw_body_and_foot(canvas, candidate, subset)
+
+    canvas = util.draw_handpose(canvas, hands)
+
+    canvas_without_face = copy.deepcopy(canvas)
+
+    canvas = util.draw_facepose(canvas, faces)
+
+    return canvas_without_face, canvas
+
+def dw_func(_id, frame, dwpose_model, dwpose_woface_folder='tmp_dwpose_wo_face', dwpose_withface_folder='tmp_dwpose_with_face'):
+    
+    # frame = cv2.imread(frame_name, cv2.IMREAD_COLOR)
+    pose = dwpose_model(frame)
+
+    return pose
+
+
+def mp_main(dontAlignPose, reference_image, video):
+    
+    logger.info(f"There are {video.size(0)} frames for extracting poses")
+
+    logger.info('LOAD: DW Pose Model')
+    dwpose_model = DWposeDetector()  
+    
+    results_vis = []
+    num_frames = video.size(0)
+
+
+    for i in range(num_frames):
+        logger.info(f"Processing frame {i + 1}/{num_frames}")
+        frame = video[i].permute(0, 1, 2).cpu().numpy() # Convert to HWC format and numpy array
+        frame = ((frame - frame.min()) / (frame.max() - frame.min()))*255 
+        frame = np.flip(frame, axis=2)  
+        pose = dw_func(i, frame, dwpose_model)
+        results_vis.append(pose)
+
+    logger.info(f'All frames have been processed.')
+    print(len(results_vis))
+
+    vid_not_aligned = copy.deepcopy(results_vis)
+
+    # Process the reference image
+    ref_frame = reference_image.squeeze(0).cpu().numpy()  # Convert to HWC format and numpy array
+    ref_frame = ((ref_frame - ref_frame.min()) / (ref_frame.max() - ref_frame.min()))*255
+    ref_frame = np.flip(ref_frame, axis=2)
+    pose_ref = dw_func(-1, ref_frame, dwpose_model)
+    # print(f'The content of the image is currently: {pose_ref} ')
+
+
+
+    bodies = results_vis[0]['bodies']
+    faces = results_vis[0]['faces']
+    hands = results_vis[0]['hands']
+    candidate = bodies['candidate']
+
+    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, y_ratio = 1, 1
+    if (zero_5_x-zero_2_x) > 0 :
+        x_ratio = (ref_5_x-ref_2_x)/(zero_5_x-zero_2_x)
+    if (zero_center2[1]-zero_center1[1]) > 0 :
+        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########
+    neck_ratio = 1
+    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
+    if l_neck_0 != 0:
+        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########
+    shoulder2_ratio = 1
+    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
+    if l_shoulder2_0 != 0:
+        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########
+    shoulder5_ratio  = 1
+    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
+    if l_shoulder5_0 != 0:
+        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########
+    arm3_ratio = 1
+    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
+    if l_arm3_0 != 0:
+        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########
+    arm4_ratio = 1
+    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
+    if l_arm4_0 != 0:
+        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########
+    arm6_ratio = 1
+    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
+    if l_arm6_0 != 0:
+        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########
+    arm7_ratio = 1
+    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
+    if l_arm7_0 != 0:
+        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########
+    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, :]
+
+
+    dwpose_images = []
+
+    for i in range(len(results_vis)):
+        dwpose_woface, _ = draw_pose(results_vis[i], H=768, W=512)
+        if dontAlignPose:
+            dwpose_woface, _ = draw_pose(vid_not_aligned[i], H=768, W=512)
+        dwpose_tensor = torch.from_numpy(dwpose_woface).permute(2, 0, 1).unsqueeze(0).float()  # Convert to tensor and CHW format
+        dwpose_tensor = dwpose_tensor.permute(0, 2, 3, 1)
+        dwpose_images.append(dwpose_tensor)
+    
+    dwpose_images = torch.cat(dwpose_images, dim=0)
+
+    dwpose_woface_ref, _ = draw_pose(pose_ref, H=768, W=512)
+    dwpose_ref_tensor = torch.from_numpy(dwpose_woface_ref).permute(2, 0, 1).unsqueeze(0).float()  # Convert to tensor and CHW format
+    dwpose_ref_tensor = dwpose_ref_tensor.permute(0, 2, 3, 1)
+
+
+    # print(f'The type of the pose from run_align_pose is currently of the form : {type(dwpose_ref_tensor)} ')
+    # print(f'The content of the pose from run_align_pose is currently: {dwpose_ref_tensor} ')
+    
+    return dwpose_images, dwpose_ref_tensor
+
+
+logger = get_logger('dw pose extraction')
+