diff --git a/unpose_one_hot.py b/unpose_one_hot.py
new file mode 100644
index 0000000..d96091f
--- /dev/null
+++ b/unpose_one_hot.py
@@ -0,0 +1,230 @@
+import os
+import sys
+import time
+import argparse
+
+import numpy as np
+import scipy.io as sio
+import scipy as sp
+import plotly.graph_objects as go
+from scipy.spatial.transform import Rotation
+
+from tqdm import tqdm
+
+from custom_utils.custom_utils import maskFacesBatch, _maskFaces
+
+
+os.environ["CUDA_VISIBLE_DEVICES"] = "1"
+import tensorflow as tf
+gpus = tf.config.experimental.list_physical_devices('GPU')
+if gpus:
+    try:
+        for gpu in gpus:
+            tf.config.experimental.set_memory_growth(gpu, True)
+
+    except RuntimeError as e:
+        print(e)
+
+
+from custom_utils.smpl import SMPL
+from custom_utils.smpl_2 import SMPL as SMPL_2
+from custom_utils.supersmpl_io import readPC2
+
+
+
+# run = wandb.init(config=tf.compat.v1.flags.FLAGS, sync_tensorboard=True, project='unpose', name='new_smpl_2', notes='')
+# artifact = wandb.Artifact('code', type='code')
+# artifact.add_file('Data/unpose.py')
+# artifact.add_file('Data/verify_unposed.py')
+# artifact.add_file('FeatureLines/superSMPL/smpl.py')
+# artifact.add_file('FeatureLines/superSMPL/smpl_2.py')
+# run.log_artifact(artifact)
+
+
+def read_garment(folder, id):
+    garment_dir = os.path.join(folder, id)
+
+    garments = [f.replace('.pc16','') for f in os.listdir(garment_dir) if f.find('_') == -1 and f != 'info.mat' and not f.endswith('.obj')]
+    assert len (garments) == 1, id
+        
+    garment = garments[0]
+
+    _posed = readPC2(os.path.join(folder, id, garment + '_registered.pc16'), True)['V']
+    info = sio.loadmat(os.path.join(folder, id, 'info.mat'))
+    _pose, _shape, gender = info['poses'].astype(np.float32), info['shape'], info['gender']
+    _shape = np.squeeze(np.concatenate((_shape, gender), axis=1)).astype(np.float32)
+    mask = np.load(os.path.join(folder, id, garment + '_mask.npy'))
+    # offsets = sio.loadmat(os.path.join(folder, id, garment + '_offsets_static.mat'))['label'][:,:3]
+    # template = sio.loadmat(os.path.join(folder, id, 'info_body.mat'))['B']
+    # mesh_static = (template + offsets) * mask[:, np.newaxis]
+
+    # posed, mesh_static = posed[:, mask, :], mesh_static[mask, :]
+    mask_idx = np.array(range(14475))[mask]
+    _shape = np.tile(_shape[np.newaxis, :], [_pose.shape[1], 1])
+
+    posed = np.zeros((300, 14475, 3), np.float32)
+    pose = np.zeros((72, 300), np.float32)
+    shape = np.zeros((300, 11), np.float32)
+
+    frames = _posed.shape[0]
+    posed[:frames, :, :] = _posed
+    pose[:, :frames,] = _pose
+    shape[:frames, :] = _shape
+
+    return posed, mask, pose, shape, mask_idx
+
+
+def plot_3d(mesh_orig, mesh_pred, unposed, faces):
+    _mesh_pred = mesh_pred.copy()
+    _unposed = unposed.copy()
+    _mesh_pred[:,1] += 1
+    _unposed[:,1] += 3
+    fig = go.Figure(data=[
+        go.Mesh3d(
+            # 8 vertices of a cube
+            x=mesh_orig[:,0],
+            y=mesh_orig[:,1],
+            z=mesh_orig[:,2],
+            # i, j and k give the vertices of triangles
+            i = faces[:,0],
+            j = faces[:,1],
+            k = faces[:,2]
+        ),
+        go.Mesh3d(
+            # 8 vertices of a cube
+            x=_mesh_pred[:,0],
+            y=_mesh_pred[:,1],
+            z=_mesh_pred[:,2],
+            # i, j and k give the vertices of triangles
+            i = faces[:,0],
+            j = faces[:,1],
+            k = faces[:,2],
+        ),
+        go.Mesh3d(
+            # 8 vertices of a cube
+            x=_unposed[:,0],
+            y=_unposed[:,1],
+            z=_unposed[:,2],
+            # i, j and k give the vertices of triangles
+            i = faces[:,0],
+            j = faces[:,1],
+            k = faces[:,2],
+            # vertexcolor=collision_color
+        )
+    ])
+
+    fig.update_layout(scene_aspectmode='manual',
+                    scene_aspectratio=dict(x=1, y=2, z=1))
+    fig.update_layout(
+        scene = dict(
+            xaxis = dict(nticks=4, range=[-1,1],),
+                        yaxis = dict(nticks=4, range=[-1,3],),
+                        zaxis = dict(nticks=4, range=[-1,1],),)
+                        )
+
+    return fig
+
+
+@tf.function
+def smpl_run_wrapper(R, shape):
+    return smpl.run(R, shape)
+
+@tf.function
+def smpl_run_backward_wrapper(Rt, J, posed):
+    return smpl.run_backward(Rt, J, posed, smpl.weights_one_hot)
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument("-f", "--folder", help = "end of range", default='/home/workspace/data/dataset/test_skirt')
+    parser.add_argument("-s", "--start", help = "start of range", default=0)
+    parser.add_argument("-e", "--end", help = "end of range", default=1500)
+    parser.add_argument("-n", "--name", help = "end of range", default='lhunor')
+    args = parser.parse_args()
+
+    F = np.load('custom_utils/smpl_faces_skirt.npy')
+    folder = args.folder
+    smpl = SMPL()
+    # smpl_2 = SMPL_2('custom_utils')
+
+    is_skirt = True
+
+    ids = os.listdir(folder)[int(args.start):int(args.end)]
+
+    for id in tqdm(ids):
+        if not os.path.isdir(os.path.join(folder, id)):
+            continue
+
+        # if len(id) == 5:
+        #     continue
+
+        os.makedirs(os.path.join(folder, id, 'mesh_unposed_one_hot'), exist_ok=True)
+        
+        posed, mask, pose, shape, mask_idx = read_garment(folder, id)
+        # gender = (shape[:, -1] > 0).astype(np.int32)
+        # init =  Rotation.from_euler('zyz', [90,90,90], degrees=True).apply(mesh_static.copy()).astype(np.float32)
+
+        # existing_frames = os.listdir(os.path.join(folder, id, 'mesh_unposed'))
+        # if len(existing_frames) == posed.shape[0]:
+        #     continue
+
+        frames = posed.shape[0]
+
+        # R = smpl.run_rodrigues(np.transpose(pose, [1,0]))
+
+        if is_skirt:
+            pose_dress = np.copy(pose)
+            p_avg = (pose[:, 3:6] + pose[:, 6:9]) / 2
+            pose_dress[:,3:9] = np.concatenate([p_avg, p_avg], axis=-1)
+            R = smpl.run_rodrigues(np.transpose(pose_dress, [1,0])).numpy()
+            for b in range(frames):
+                R[b][[4,5,7,8,10,11],:,:] = np.eye(3)
+        else:
+            R = smpl.run_rodrigues(np.transpose(pose, [1,0]))
+
+        Rt = tf.transpose(R, [0, 1, 3, 2])
+        T_body, J, _ = smpl_run_wrapper(R, shape)
+        # zero_body = smpl_run_wrapper(smpl.run_rodrigues(np.zeros((1, 72), np.float32)), shape[:1, :])[0][0].numpy()
+
+
+        T0_garment, J = smpl_run_backward_wrapper(Rt, J, posed)
+        # T_garment, _ = smpl.run_garment_orig(R, shape, T0_garment) # =====> you do not need this and next line for unposing
+        # metric = tf.reduce_max(tf.abs(mask[tf.newaxis,:,tf.newaxis] * (T_garment - posed)))
+
+
+        for frame in range(frames):
+            np.savez_compressed(os.path.join(folder, id, 'mesh_unposed_one_hot', id + '_' + str(frame) + '.npz'), mesh_unposed=T0_garment[frame])
+        
+        # F = np.load("custom_utils/smpl_faces" + ("_skirt" if is_skirt else "") + ".npy")
+        # _, faces = _maskFaces(np.zeros((14475, 3)), F, mask.astype(bool))
+
+        # batch = 0
+        # x = T0_garment[batch].numpy()[mask, :]
+        # y = zero_body
+        # go.Figure(data=[
+        #     go.Mesh3d(
+        #         # 8 vertices of a cube
+        #         x=x[:,0],
+        #         y=x[:,1],
+        #         z=x[:,2],
+        #         # i, j and k give the vertices of triangles
+        #         i = faces[:,0],
+        #         j = faces[:,1],
+        #         k = faces[:,2],
+        #      ),
+        #     go.Mesh3d(
+        #         # 8 vertices of a cube
+        #         x=y[:,0],
+        #         y=y[:,1],
+        #         z=y[:,2],
+        #         # i, j and k give the vertices of triangles
+        #         i = F[:,0],
+        #         j = F[:,1],
+        #         k = F[:,2],
+        #     )],
+        #     ).show()
+
+
+        # print()
+
+