File size: 11,117 Bytes
710e818
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
import numpy as np
import torch
import trimesh
import os
import mesh2sdf
import time
from scipy.spatial.transform import Rotation as R

QUASI_DYN_ROOT = "/home/xueyi/diffsim/NeuS"
if not os.path.exists(QUASI_DYN_ROOT):
    QUASI_DYN_ROOT = "/root/diffsim/quasi-dyn"

ARCTIC_CANON_OBJ_SV_FOLDER = os.path.join(QUASI_DYN_ROOT, "raw_data/arctic_processed_canon_obj")



def export_canon_obj_file(kinematic_mano_gt_sv_fn, obj_name):
    
    subject_idx = kinematic_mano_gt_sv_fn.split("/")[-2] # 
    print(f"subject_idx: {subject_idx}, obj name: {obj_name}")
    sv_dict = np.load(kinematic_mano_gt_sv_fn, allow_pickle=True).item()
    
    
    object_global_orient = sv_dict["obj_rot"]  
    object_transl = sv_dict["obj_trans"] * 0.001
    obj_pcs = sv_dict["verts.object"]
    
    # obj_pcs = sv_dict['object_pc']
    obj_pcs = torch.from_numpy(obj_pcs).float().cuda()
    
    
    # self.obj_verts = obj_verts
    init_obj_verts = obj_pcs[0]
    init_obj_rot_vec = object_global_orient[0]
    init_obj_transl = object_transl[0]
    
    init_obj_transl = torch.from_numpy(init_obj_transl).float().cuda()
    init_rot_struct = R.from_rotvec(init_obj_rot_vec)
    
    init_glb_rot_mtx = init_rot_struct.as_matrix()
    init_glb_rot_mtx = torch.from_numpy(init_glb_rot_mtx).float().cuda()
    # ## reverse the global rotation matrix ##
    init_glb_rot_mtx_reversed = init_glb_rot_mtx.contiguous().transpose(1, 0).contiguous()


    
    ''' canonical object verts '''
    canon_obj_verts = torch.matmul(
        init_glb_rot_mtx_reversed.transpose(1, 0).contiguous(), (init_obj_verts - init_obj_transl.unsqueeze(0)).contiguous().transpose(1, 0).contiguous()
    ).contiguous().transpose(1, 0).contiguous()

    # ## get canon obj verts ##
    
    # /home/xueyi/diffsim/NeuS/raw_data/arctic_processed_canon_obj
    
    canon_obj_sv_folder = ARCTIC_CANON_OBJ_SV_FOLDER # "/root/diffsim/control-vae-2/assets/arctic"
    canon_obj_mesh = trimesh.Trimesh(vertices=canon_obj_verts.detach().cpu().numpy(), faces=sv_dict['f'][0])
    
    canon_obj_mesh_sv_fn = f"{subject_idx}_{obj_name}.obj"
    canon_obj_mesh_sv_fn = os.path.join(canon_obj_sv_folder, canon_obj_mesh_sv_fn)
    canon_obj_mesh.export(canon_obj_mesh_sv_fn)

    print(f"Canonical obj mesh saved to {canon_obj_mesh_sv_fn}")
    return canon_obj_mesh_sv_fn


def compute_sdf(obj_file_name):
    filename = obj_file_name

    # init_mesh_scale = 1.0
    init_mesh_scale = 0.8

    mesh_scale = 0.8
    size = 128
    level = 2 / size

    mesh = trimesh.load(filename, force='mesh')

    # normalize mesh
    vertices = mesh.vertices
    vertices = vertices * init_mesh_scale
    bbmin = vertices.min(0) # 
    bbmax = vertices.max(0) # 
    center = (bbmin + bbmax) * 0.5
    scale = 2.0 * mesh_scale / (bbmax - bbmin).max() # bounding box's max # # bbmax - bbmin # 
    vertices = (vertices - center) * scale # (vertices - center) * scale #

    scaled_bbmin = vertices.min(0)
    scaled_bbmax = vertices.max(0)
    print(f"scaled_bbmin: {scaled_bbmin}, scaled_bbmax: {scaled_bbmax}")


    t0 = time.time()
    sdf, mesh = mesh2sdf.compute( ## sdf and mesh ##
        vertices, mesh.faces, size, fix=True, level=level, return_mesh=True)
    t1 = time.time()

    print(f"sdf: {sdf.shape}, mesh: {mesh.vertices.shape}")

    mesh.vertices = mesh.vertices / scale + center
    mesh.export(filename[:-4] + '.fixed.obj') ## .fixed.obj ##
    np.save(filename[:-4] + '.npy', sdf) ## .npy ##
    print('It takes %.4f seconds to process %s' % (t1-t0, filename))



def convert_tot_states_to_data_ref_format(tot_states_fn, sv_gt_ref_data_fn):
    tot_states_data = np.load(tot_states_fn, allow_pickle=True).item()
    tot_states = tot_states_data['tot_states']
    tot_mano_rot = []
    tot_mano_glb_trans = []
    tot_mano_states = []
    
    tot_obj_rot = []
    tot_obj_trans = []
    
    for i_fr in range(len(tot_states)):
        cur_state = tot_states[i_fr]
        cur_mano_state = cur_state[:-7]
        cur_obj_state  = cur_state[-7:]
        
        tot_mano_glb_trans.append(cur_mano_state[:3])
        cur_mano_rot_vec = cur_mano_state[3:6]
        cur_mano_rot_euler_zyx = [cur_mano_rot_vec[2], cur_mano_rot_vec[1], cur_mano_rot_vec[0]]
        cur_mano_rot_euler_zyx = np.array(cur_mano_rot_euler_zyx, dtype=np.float32)
        cur_mano_rot_struct = R.from_euler('zyx', cur_mano_rot_euler_zyx, degrees=False)
        cur_mano_rot_quat_xyzw = cur_mano_rot_struct.as_quat()
        cur_mano_rot_quat_wxyz = cur_mano_rot_quat_xyzw[[3, 0, 1, 2]]
        tot_mano_rot.append(cur_mano_rot_quat_wxyz.astype(np.float32))
        
        tot_mano_states.append(cur_mano_state[4:])
        
        tot_obj_rot.append(cur_obj_state[-4:][[3, 0, 1, 2]])
        tot_obj_trans.append(cur_obj_state[:3])
    tot_obj_rot = np.stack(tot_obj_rot, axis=0)
    tot_obj_trans = np.stack(tot_obj_trans, axis=0)
    tot_mano_rot =  np.stack(tot_mano_rot, axis=0)
    tot_mano_glb_trans = np.stack(tot_mano_glb_trans, axis=0)
    tot_mano_states = np.stack(tot_mano_states, axis=0)
    
    gt_ref_data = {
        'obj_rot': tot_obj_rot, 
        'obj_trans': tot_obj_trans,
        'mano_states': tot_mano_states,
        'mano_glb_trans': tot_mano_glb_trans,
        'mano_glb_rot': tot_mano_rot
    }
    
    np.save(sv_gt_ref_data_fn, gt_ref_data)
    print(f"gt ref data svaed to {sv_gt_ref_data_fn}")


# spoon --> how to sue the spoon #
# 

if __name__=='__main__':
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_mouse_idx_102_tracking_2/2024-02-27-05-44-09/sv_info_800.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_grab_mouse_102_dgrasptracking.npy"
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_bunny_idx_85_tracking_2/2024-02-26-08-33-58/sv_info_600.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_grab_bunny_85_dgrasptracking.npy"
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_spoon2_idx_20231105_067_tracking_2/2024-02-29-09-49-32/sv_info_300.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_spoon2_idx_20231105_067_dgrasptracking.npy"
    
    tot_states_fn= "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231027_086_idx_20231027_086_tracking_2/2024-03-09-13-01-24/sv_info_best.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231027_086_idx_20231027_086_dgrasptracking.npy"
    
    # /home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231024_044_idx_20231024_044_tracking_2/2024-03-09-13-20-07/sv_info_best.npy
    tot_states_fn= "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231024_044_idx_20231024_044_tracking_2/2024-03-09-13-20-07/sv_info_best.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231024_044_idx_20231024_044_dgrasptracking.npy"
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231027_130_idx_20231027_130_tracking_2/2024-03-09-13-40-52/sv_info_best.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231027_130_idx_20231027_130_dgrasptracking.npy" ## gt 130 ##
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231020_199_idx_20231020_199_tracking_2/2024-03-09-14-01-13/sv_info_best.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231020_199_idx_20231020_199_dgrasptracking.npy" ## gt 130 ##
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231026_016_idx_20231026_016_tracking_2/2024-03-11-10-06-43/sv_info_best.npy"
    
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231026_016_idx_20231026_016_dgrasptracking.npy" ## gt 130 ##
    
    tot_states_fn = "/home/xueyi/diffsim/raisim/dgrasp/raisimGymTorch/bullet_env/obj_20231027_114_idx_20231027_114_tracking_2/2024-03-11-10-07-36/sv_info_best.npy"
    sv_gt_ref_data_fn = "/home/xueyi/diffsim/Control-VAE/ReferenceData/shadow_taco_20231027_114_idx_20231027_114_dgrasptracking.npy" ## gt 130 ##
    
    convert_tot_states_to_data_ref_format(tot_states_fn, sv_gt_ref_data_fn)
    exit(0)
    
    
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s01/box_grab_01.npy'
    
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s01/ketchup_grab_01.npy'
    
    # kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s01/mixer_grab_01.npy'
    
    # kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s01/laptop_grab_01.npy'
    
    # kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s01/box_grab_01.npy'
    
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s02/waffleiron_grab_01.npy'
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s02/ketchup_grab_01.npy'
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s02/phone_grab_01.npy'
    kinematic_mano_gt_sv_fn = '/data/xueyi/sim/arctic_processed_data/processed_seqs/s02/box_grab_01.npy'
    
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s02"
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s04"
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s05"
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s06"
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s07"
    kinematic_mano_gt_sv_folder = "/data/xueyi/sim/arctic_processed_data/processed_seqs/s10"
    
    kinematic_mano_gt_sv_fn_all = os.listdir(kinematic_mano_gt_sv_folder)
    kinematic_mano_gt_sv_fn_all = [fn for fn in kinematic_mano_gt_sv_fn_all if fn.endswith(".npy") and "grab" in fn]
    kinematic_mano_gt_sv_fn_all = [os.path.join(kinematic_mano_gt_sv_folder, fn) for fn in kinematic_mano_gt_sv_fn_all]
    for kinematic_mano_gt_sv_fn in kinematic_mano_gt_sv_fn_all:
        obj_name = kinematic_mano_gt_sv_fn.split("/")[-1].split(".")[0].split("_")[0]
        print(f"obj_name: {obj_name}")
        
        ##### process and export canonical object file #####
        canon_obj_mesh_sv_fn = export_canon_obj_file(kinematic_mano_gt_sv_fn, obj_name)
        
        
        ##### compute sdf of the canonical object mesh #####
        compute_sdf(canon_obj_mesh_sv_fn)
        
    
    # obj_name = kinematic_mano_gt_sv_fn.split("/")[-1].split(".")[0].split("_")[0]
    # print(f"obj_name: {obj_name}")
    
    # ##### process and export canonical object file #####
    # canon_obj_mesh_sv_fn = export_canon_obj_file(kinematic_mano_gt_sv_fn, obj_name)
    
    
    # ##### compute sdf of the canonical object mesh #####
    # compute_sdf(canon_obj_mesh_sv_fn)