File size: 29,890 Bytes
b5042f1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
# common utils
import os
import argparse
import time

# pytorch3d
from pytorch3d.renderer import TexturesUV

# torch
import torch

from torchvision import transforms

# numpy
import numpy as np

# image
from PIL import Image


# customized
import sys
# sys.path.append(".")
sys.path.append("./text2tex")

from lib.mesh_helper import (
    init_mesh,
    apply_offsets_to_mesh,
    adjust_uv_map
)
from lib.render_helper import render
from lib.io_helper import (
    save_backproject_obj,
    save_args,
    save_viewpoints
)
from lib.vis_helper import (
    visualize_outputs, 
    visualize_principle_viewpoints, 
    visualize_refinement_viewpoints
)
from lib.diffusion_helper import (
    get_controlnet_depth,
    get_inpainting,
    apply_controlnet_depth,
    apply_inpainting_postprocess
)
from lib.projection_helper import (
    backproject_from_image,
    render_one_view_and_build_masks,
    select_viewpoint,
    build_similarity_texture_cache_for_all_views
)
from lib.camera_helper import init_viewpoints

# Setup
if torch.cuda.is_available():
    DEVICE = torch.device("cuda:0")
    torch.cuda.set_device(DEVICE)
else:
    print("no gpu avaiable")
    exit()


"""
    Use Diffusion Models conditioned on depth input to back-project textures on 3D mesh.

    The inputs should be constructed as follows:
        - <input_dir>/
            |- <obj_file> # name of the input OBJ file
    
    The outputs of this script would be stored under `outputs/`, with the
    configuration parameters as the folder name. Specifically, there should be following files in such
    folder:
        - outputs/
            |- <configs>/                       # configurations of the run
                |- generate/                    # assets generated in generation stage
                    |- depth/                   # depth map
                    |- inpainted/               # images generated by diffusion models
                    |- intermediate/            # renderings of textured mesh after each step
                    |- mask/                    # generation mask
                    |- mesh/                    # textured mesh
                    |- normal/                  # normal map
                    |- rendering/               # input renderings
                    |- similarity/              # simiarity map
                |- update/                      # assets generated in refinement stage
                    |- ...                      # the structure is the same as generate/
                |- args.json                    # all arguments for the run
                |- viewpoints.json              # all viewpoints
                |- principle_viewpoints.png     # principle viewpoints
                |- refinement_viewpoints.png    # refinement viewpoints

"""

def init_args():
    print("=> initializing input arguments...")
    parser = argparse.ArgumentParser()
    parser.add_argument("--input_dir", type=str, default="./inputs",)
    parser.add_argument("--output_dir", type=str, default="./outputs")
    parser.add_argument("--obj_name", type=str, default="mesh")
    parser.add_argument("--obj_file", type=str, default="mesh.obj")
    parser.add_argument("--prompt", type=str, default="a 3D object")
    parser.add_argument("--a_prompt", type=str, default="best quality, high quality, extremely detailed, good geometry")
    parser.add_argument("--n_prompt", type=str, default="deformed, extra digit, fewer digits, cropped, worst quality, low quality, smoke")
    parser.add_argument("--new_strength", type=float, default=1)
    parser.add_argument("--update_strength", type=float, default=0.5)
    parser.add_argument("--ddim_steps", type=int, default=20)
    parser.add_argument("--guidance_scale", type=float, default=10)
    parser.add_argument("--output_scale", type=float, default=1)
    parser.add_argument("--view_threshold", type=float, default=0.1)
    parser.add_argument("--num_viewpoints", type=int, default=8)
    parser.add_argument("--viewpoint_mode", type=str, default="predefined", choices=["predefined", "hemisphere"])
    parser.add_argument("--update_steps", type=int, default=8)
    parser.add_argument("--update_mode", type=str, default="heuristic", choices=["sequential", "heuristic", "random"])
    parser.add_argument("--blend", type=float, default=0.5)
    parser.add_argument("--eta", type=float, default=0.0)
    parser.add_argument("--seed", type=int, default=42)

    parser.add_argument("--use_patch", action="store_true", help="apply repaint during refinement to patch up the missing regions")
    parser.add_argument("--use_multiple_objects", action="store_true", help="operate on multiple objects")
    parser.add_argument("--use_principle", action="store_true", help="poperate on multiple objects")
    parser.add_argument("--use_shapenet", action="store_true", help="operate on ShapeNet objects")
    parser.add_argument("--use_objaverse", action="store_true", help="operate on Objaverse objects")
    parser.add_argument("--use_unnormalized", action="store_true", help="save unnormalized mesh")

    parser.add_argument("--add_view_to_prompt", action="store_true", help="add view information to the prompt")
    parser.add_argument("--post_process", action="store_true", help="post processing the texture")

    parser.add_argument("--smooth_mask", action="store_true", help="smooth the diffusion mask")

    parser.add_argument("--force", action="store_true", help="forcefully generate more image")

    # negative options
    parser.add_argument("--no_repaint", action="store_true", help="do NOT apply repaint")
    parser.add_argument("--no_update", action="store_true", help="do NOT apply update")

    # device parameters
    parser.add_argument("--device", type=str, choices=["a6000", "2080"], default="a6000")

    # camera parameters NOTE need careful tuning!!!
    parser.add_argument("--test_camera", action="store_true")
    parser.add_argument("--dist", type=float, default=1, 
        help="distance to the camera from the object")
    parser.add_argument("--elev", type=float, default=0,
        help="the angle between the vector from the object to the camera and the horizontal plane")
    parser.add_argument("--azim", type=float, default=180,
        help="the angle between the vector from the object to the camera and the vertical plane")
    parser.add_argument("--uv_size", type=int, default=1000)
    parser.add_argument("--image_size", type=int, default=768)

    args = parser.parse_args()

    if args.device == "a6000":
        setattr(args, "render_simple_factor", 12)
        setattr(args, "fragment_k", 1)
        setattr(args, "image_size", 768)
        setattr(args, "uv_size", 3000)
    else:
        setattr(args, "render_simple_factor", 4)
        setattr(args, "fragment_k", 1)
        setattr(args, "image_size", args.image_size)
        setattr(args, "uv_size", args.uv_size)

    return args

def text2tex_call(args):
    tik = time.time()

    # save
    output_dir = os.path.join(
        args.output_dir, 
        "{}-{}-{}-{}-{}-{}-{}-{}-{}".format(
            str(args.seed),
            args.viewpoint_mode[0]+str(args.num_viewpoints),
            args.update_mode[0]+str(args.update_steps),
            'd'+str(args.ddim_steps),
            str(args.new_strength),
            str(args.update_strength),
            str(args.view_threshold),
            'uv'+str(args.uv_size),
            'img'+str(args.image_size),
        ),
    )
    if args.no_repaint: output_dir += "-norepaint"
    if args.no_update: output_dir += "-noupdate"

    os.makedirs(output_dir, exist_ok=True)
    print("=> OUTPUT_DIR:", output_dir)

    # init resources
    # init mesh
    mesh, _, faces, aux, principle_directions, mesh_center, mesh_scale = init_mesh(
        os.path.join(args.input_dir, args.obj_file),
        os.path.join(output_dir, args.obj_file), 
        DEVICE
    )

    # gradient texture
    init_texture = Image.open("./text2tex/samples/textures/dummy.png").convert("RGB").resize((args.uv_size, args.uv_size))

    # HACK adjust UVs for multiple materials
    if args.use_multiple_objects:
        new_verts_uvs, init_texture = adjust_uv_map(faces, aux, init_texture, args.uv_size)
    else:
        new_verts_uvs = aux.verts_uvs

    # update the mesh
    mesh.textures = TexturesUV(
        maps=transforms.ToTensor()(init_texture)[None, ...].permute(0, 2, 3, 1).to(DEVICE),
        faces_uvs=faces.textures_idx[None, ...],
        verts_uvs=new_verts_uvs[None, ...]
    )

    # back-projected faces
    exist_texture = torch.from_numpy(np.zeros([args.uv_size, args.uv_size]).astype(np.float32)).to(DEVICE)

    # initialize viewpoints
    # including: principle viewpoints for generation + refinement viewpoints for updating
    (
        dist_list, 
        elev_list, 
        azim_list, 
        sector_list,
        view_punishments
    ) = init_viewpoints(args.viewpoint_mode, args.num_viewpoints, args.dist, args.elev, principle_directions, 
                            use_principle=True, 
                            use_shapenet=args.use_shapenet,
                            use_objaverse=args.use_objaverse)

    # save args
    save_args(args, output_dir)

    # initialize depth2image model
    controlnet, ddim_sampler = get_controlnet_depth()


    # ------------------- OPERATION ZONE BELOW ------------------------

    # 1. generate texture with RePaint 
    # NOTE no update / refinement

    generate_dir = os.path.join(output_dir, "generate")
    os.makedirs(generate_dir, exist_ok=True)

    update_dir = os.path.join(output_dir, "update")
    os.makedirs(update_dir, exist_ok=True)

    init_image_dir = os.path.join(generate_dir, "rendering")
    os.makedirs(init_image_dir, exist_ok=True)

    normal_map_dir = os.path.join(generate_dir, "normal")
    os.makedirs(normal_map_dir, exist_ok=True)

    mask_image_dir = os.path.join(generate_dir, "mask")
    os.makedirs(mask_image_dir, exist_ok=True)

    depth_map_dir = os.path.join(generate_dir, "depth")
    os.makedirs(depth_map_dir, exist_ok=True)

    similarity_map_dir = os.path.join(generate_dir, "similarity")
    os.makedirs(similarity_map_dir, exist_ok=True)

    inpainted_image_dir = os.path.join(generate_dir, "inpainted")
    os.makedirs(inpainted_image_dir, exist_ok=True)

    mesh_dir = os.path.join(generate_dir, "mesh")
    os.makedirs(mesh_dir, exist_ok=True)

    interm_dir = os.path.join(generate_dir, "intermediate")
    os.makedirs(interm_dir, exist_ok=True)

    # prepare viewpoints and cache
    NUM_PRINCIPLE = 10 if args.use_shapenet or args.use_objaverse else 6
    pre_dist_list = dist_list[:NUM_PRINCIPLE]
    pre_elev_list = elev_list[:NUM_PRINCIPLE]
    pre_azim_list = azim_list[:NUM_PRINCIPLE]
    pre_sector_list = sector_list[:NUM_PRINCIPLE]
    pre_view_punishments = view_punishments[:NUM_PRINCIPLE]

    pre_similarity_texture_cache = build_similarity_texture_cache_for_all_views(mesh, faces, new_verts_uvs,
        pre_dist_list, pre_elev_list, pre_azim_list,
        args.image_size, args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
        DEVICE
    )


    # start generation
    print("=> start generating texture...")
    start_time = time.time()
    for view_idx in range(NUM_PRINCIPLE):
        print("=> processing view {}...".format(view_idx))

        # sequentially pop the viewpoints
        dist, elev, azim, sector = pre_dist_list[view_idx], pre_elev_list[view_idx], pre_azim_list[view_idx], pre_sector_list[view_idx] 
        prompt = " the {} view of {}".format(sector, args.prompt) if args.add_view_to_prompt else args.prompt
        print("=> generating image for prompt: {}...".format(prompt))

        # 1.1. render and build masks
        (
            view_score,
            renderer, cameras, fragments,
            init_image, normal_map, depth_map, 
            init_images_tensor, normal_maps_tensor, depth_maps_tensor, similarity_tensor, 
            keep_mask_image, update_mask_image, generate_mask_image, 
            keep_mask_tensor, update_mask_tensor, generate_mask_tensor, all_mask_tensor, quad_mask_tensor,
        ) = render_one_view_and_build_masks(dist, elev, azim, 
            view_idx, view_idx, view_punishments, # => actual view idx and the sequence idx 
            pre_similarity_texture_cache, exist_texture,
            mesh, faces, new_verts_uvs,
            args.image_size, args.fragment_k,
            init_image_dir, mask_image_dir, normal_map_dir, depth_map_dir, similarity_map_dir,
            DEVICE, save_intermediate=True, smooth_mask=args.smooth_mask, view_threshold=args.view_threshold
        )

        # 1.2. generate missing region
        # NOTE first view still gets the mask for consistent ablations
        if args.no_repaint and view_idx != 0:
            actual_generate_mask_image = Image.fromarray((np.ones_like(np.array(generate_mask_image)) * 255.).astype(np.uint8))
        else:
            actual_generate_mask_image = generate_mask_image

        print("=> generate for view {}".format(view_idx))
        generate_image, generate_image_before, generate_image_after = apply_controlnet_depth(controlnet, ddim_sampler, 
            init_image.convert("RGBA"), prompt, args.new_strength, args.ddim_steps,
            actual_generate_mask_image, keep_mask_image, depth_maps_tensor.permute(1, 2, 0).repeat(1, 1, 3).cpu().numpy(), 
            args.a_prompt, args.n_prompt, args.guidance_scale, args.seed, args.eta, 1, DEVICE, args.blend)

        generate_image.save(os.path.join(inpainted_image_dir, "{}.png".format(view_idx)))
        generate_image_before.save(os.path.join(inpainted_image_dir, "{}_before.png".format(view_idx)))
        generate_image_after.save(os.path.join(inpainted_image_dir, "{}_after.png".format(view_idx)))

        # 1.2.2 back-project and create texture
        # NOTE projection mask = generate mask
        init_texture, project_mask_image, exist_texture = backproject_from_image(
            mesh, faces, new_verts_uvs, cameras, 
            generate_image, generate_mask_image, generate_mask_image, init_texture, exist_texture, 
            args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
            DEVICE
        )

        project_mask_image.save(os.path.join(mask_image_dir, "{}_project.png".format(view_idx)))

        # update the mesh
        mesh.textures = TexturesUV(
            maps=transforms.ToTensor()(init_texture)[None, ...].permute(0, 2, 3, 1).to(DEVICE),
            faces_uvs=faces.textures_idx[None, ...],
            verts_uvs=new_verts_uvs[None, ...]
        )

        # 1.2.3. re: render 
        # NOTE only the rendered image is needed - masks should be re-used
        (
            view_score,
            renderer, cameras, fragments,
            init_image, *_,
        ) = render_one_view_and_build_masks(dist, elev, azim, 
            view_idx, view_idx, view_punishments, # => actual view idx and the sequence idx 
            pre_similarity_texture_cache, exist_texture,
            mesh, faces, new_verts_uvs,
            args.image_size, args.fragment_k,
            init_image_dir, mask_image_dir, normal_map_dir, depth_map_dir, similarity_map_dir,
            DEVICE, save_intermediate=False, smooth_mask=args.smooth_mask, view_threshold=args.view_threshold
        )

        # 1.3. update blurry region
        # only when: 1) use update flag; 2) there are contents to update; 3) there are enough contexts.
        if not args.no_update and update_mask_tensor.sum() > 0 and update_mask_tensor.sum() / (all_mask_tensor.sum()) > 0.05:
            print("=> update {} pixels for view {}".format(update_mask_tensor.sum().int(), view_idx))
            diffused_image, diffused_image_before, diffused_image_after = apply_controlnet_depth(controlnet, ddim_sampler, 
                init_image.convert("RGBA"), prompt, args.update_strength, args.ddim_steps,
                update_mask_image, keep_mask_image, depth_maps_tensor.permute(1, 2, 0).repeat(1, 1, 3).cpu().numpy(), 
                args.a_prompt, args.n_prompt, args.guidance_scale, args.seed, args.eta, 1, DEVICE, args.blend)

            diffused_image.save(os.path.join(inpainted_image_dir, "{}_update.png".format(view_idx)))
            diffused_image_before.save(os.path.join(inpainted_image_dir, "{}_update_before.png".format(view_idx)))
            diffused_image_after.save(os.path.join(inpainted_image_dir, "{}_update_after.png".format(view_idx)))
        
            # 1.3.2. back-project and create texture
            # NOTE projection mask = generate mask
            init_texture, project_mask_image, exist_texture = backproject_from_image(
                mesh, faces, new_verts_uvs, cameras, 
                diffused_image, update_mask_image, update_mask_image, init_texture, exist_texture, 
                args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
                DEVICE
            )
            
            # update the mesh
            mesh.textures = TexturesUV(
                maps=transforms.ToTensor()(init_texture)[None, ...].permute(0, 2, 3, 1).to(DEVICE),
                faces_uvs=faces.textures_idx[None, ...],
                verts_uvs=new_verts_uvs[None, ...]
            )


        # 1.4. save generated assets
        # save backprojected OBJ file
        save_backproject_obj(
            mesh_dir, "{}.obj".format(view_idx),
            mesh_scale * mesh.verts_packed() + mesh_center if args.use_unnormalized else mesh.verts_packed(),
            faces.verts_idx, new_verts_uvs, faces.textures_idx, init_texture, 
            DEVICE
        )

        # save the intermediate view
        inter_images_tensor, *_ = render(mesh, renderer)
        inter_image = inter_images_tensor[0].cpu()
        inter_image = inter_image.permute(2, 0, 1)
        inter_image = transforms.ToPILImage()(inter_image).convert("RGB")
        inter_image.save(os.path.join(interm_dir, "{}.png".format(view_idx)))

        # save texture mask
        exist_texture_image = exist_texture * 255. 
        exist_texture_image = Image.fromarray(exist_texture_image.cpu().numpy().astype(np.uint8)).convert("L")
        exist_texture_image.save(os.path.join(mesh_dir, "{}_texture_mask.png".format(view_idx)))

    print("=> total generate time: {} s".format(time.time() - start_time))

    # visualize viewpoints
    visualize_principle_viewpoints(output_dir, pre_dist_list, pre_elev_list, pre_azim_list)

    # 2. update texture with RePaint 

    if args.update_steps > 0:

        update_dir = os.path.join(output_dir, "update")
        os.makedirs(update_dir, exist_ok=True)

        init_image_dir = os.path.join(update_dir, "rendering")
        os.makedirs(init_image_dir, exist_ok=True)

        normal_map_dir = os.path.join(update_dir, "normal")
        os.makedirs(normal_map_dir, exist_ok=True)

        mask_image_dir = os.path.join(update_dir, "mask")
        os.makedirs(mask_image_dir, exist_ok=True)

        depth_map_dir = os.path.join(update_dir, "depth")
        os.makedirs(depth_map_dir, exist_ok=True)

        similarity_map_dir = os.path.join(update_dir, "similarity")
        os.makedirs(similarity_map_dir, exist_ok=True)

        inpainted_image_dir = os.path.join(update_dir, "inpainted")
        os.makedirs(inpainted_image_dir, exist_ok=True)

        mesh_dir = os.path.join(update_dir, "mesh")
        os.makedirs(mesh_dir, exist_ok=True)

        interm_dir = os.path.join(update_dir, "intermediate")
        os.makedirs(interm_dir, exist_ok=True)

        dist_list = dist_list[NUM_PRINCIPLE:]
        elev_list = elev_list[NUM_PRINCIPLE:]
        azim_list = azim_list[NUM_PRINCIPLE:]
        sector_list = sector_list[NUM_PRINCIPLE:]
        view_punishments = view_punishments[NUM_PRINCIPLE:]

        similarity_texture_cache = build_similarity_texture_cache_for_all_views(mesh, faces, new_verts_uvs,
            dist_list, elev_list, azim_list,
            args.image_size, args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
            DEVICE
        )
        selected_view_ids = []

        print("=> start updating...")
        start_time = time.time()
        for view_idx in range(args.update_steps):
            print("=> processing view {}...".format(view_idx))
            
            # 2.1. render and build masks

            # heuristically select the viewpoints
            dist, elev, azim, sector, selected_view_ids, view_punishments = select_viewpoint(
                selected_view_ids, view_punishments,
                args.update_mode, dist_list, elev_list, azim_list, sector_list, view_idx,
                similarity_texture_cache, exist_texture,
                mesh, faces, new_verts_uvs,
                args.image_size, args.fragment_k,
                init_image_dir, mask_image_dir, normal_map_dir, depth_map_dir, similarity_map_dir,
                DEVICE, False
            )

            (
                view_score,
                renderer, cameras, fragments,
                init_image, normal_map, depth_map, 
                init_images_tensor, normal_maps_tensor, depth_maps_tensor, similarity_tensor, 
                old_mask_image, update_mask_image, generate_mask_image, 
                old_mask_tensor, update_mask_tensor, generate_mask_tensor, all_mask_tensor, quad_mask_tensor,
            ) = render_one_view_and_build_masks(dist, elev, azim, 
                selected_view_ids[-1], view_idx, view_punishments, # => actual view idx and the sequence idx 
                similarity_texture_cache, exist_texture,
                mesh, faces, new_verts_uvs,
                args.image_size, args.fragment_k,
                init_image_dir, mask_image_dir, normal_map_dir, depth_map_dir, similarity_map_dir,
                DEVICE, save_intermediate=True, smooth_mask=args.smooth_mask, view_threshold=args.view_threshold
            )

            # # -------------------- OPTION ZONE ------------------------
            # # still generate for missing regions during refinement
            # # NOTE this could take significantly more time to complete.
            # if args.use_patch:
            #     # 2.2.1 generate missing region
            #     prompt = " the {} view of {}".format(sector, args.prompt) if args.add_view_to_prompt else args.prompt
            #     print("=> generating image for prompt: {}...".format(prompt))

            #     if args.no_repaint:
            #         generate_mask_image = Image.fromarray((np.ones_like(np.array(generate_mask_image)) * 255.).astype(np.uint8))

            #     print("=> generate {} pixels for view {}".format(generate_mask_tensor.sum().int(), view_idx))
            #     generate_image, generate_image_before, generate_image_after = apply_controlnet_depth(controlnet, ddim_sampler, 
            #         init_image.convert("RGBA"), prompt, args.new_strength, args.ddim_steps,
            #         generate_mask_image, keep_mask_image, depth_maps_tensor.permute(1, 2, 0).repeat(1, 1, 3).cpu().numpy(), 
            #         args.a_prompt, args.n_prompt, args.guidance_scale, args.seed, args.eta, 1, DEVICE, args.blend)

            #     generate_image.save(os.path.join(inpainted_image_dir, "{}_new.png".format(view_idx)))
            #     generate_image_before.save(os.path.join(inpainted_image_dir, "{}_new_before.png".format(view_idx)))
            #     generate_image_after.save(os.path.join(inpainted_image_dir, "{}_new_after.png".format(view_idx)))

            #     # 2.2.2. back-project and create texture
            #     # NOTE projection mask = generate mask
            #     init_texture, project_mask_image, exist_texture = backproject_from_image(
            #         mesh, faces, new_verts_uvs, cameras, 
            #         generate_image, generate_mask_image, generate_mask_image, init_texture, exist_texture, 
            #         args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
            #         DEVICE
            #     )

            #     project_mask_image.save(os.path.join(mask_image_dir, "{}_new_project.png".format(view_idx)))

            #     # update the mesh
            #     mesh.textures = TexturesUV(
            #         maps=transforms.ToTensor()(init_texture)[None, ...].permute(0, 2, 3, 1).to(DEVICE),
            #         faces_uvs=faces.textures_idx[None, ...],
            #         verts_uvs=new_verts_uvs[None, ...]
            #     )

            #     # 2.2.4. save generated assets
            #     # save backprojected OBJ file
            #     save_backproject_obj(
            #         mesh_dir, "{}_new.obj".format(view_idx),
            #         mesh.verts_packed(), faces.verts_idx, new_verts_uvs, faces.textures_idx, init_texture, 
            #         DEVICE
            #     )

            # # -------------------- OPTION ZONE ------------------------


            # 2.2. update existing region
            prompt = " the {} view of {}".format(sector, args.prompt) if args.add_view_to_prompt else args.prompt
            print("=> updating image for prompt: {}...".format(prompt))

            if not args.no_update and update_mask_tensor.sum() > 0 and update_mask_tensor.sum() / (all_mask_tensor.sum()) > 0.05:
                print("=> update {} pixels for view {}".format(update_mask_tensor.sum().int(), view_idx))
                update_image, update_image_before, update_image_after = apply_controlnet_depth(controlnet, ddim_sampler, 
                    init_image.convert("RGBA"), prompt, args.update_strength, args.ddim_steps,
                    update_mask_image, old_mask_image, depth_maps_tensor.permute(1, 2, 0).repeat(1, 1, 3).cpu().numpy(), 
                    args.a_prompt, args.n_prompt, args.guidance_scale, args.seed, args.eta, 1, DEVICE, args.blend)

                update_image.save(os.path.join(inpainted_image_dir, "{}.png".format(view_idx)))
                update_image_before.save(os.path.join(inpainted_image_dir, "{}_before.png".format(view_idx)))
                update_image_after.save(os.path.join(inpainted_image_dir, "{}_after.png".format(view_idx)))
            else:
                print("=> nothing to update for view {}".format(view_idx))
                update_image = init_image

                old_mask_tensor += update_mask_tensor
                update_mask_tensor[update_mask_tensor == 1] = 0 # HACK nothing to update

                old_mask_image = transforms.ToPILImage()(old_mask_tensor)
                update_mask_image = transforms.ToPILImage()(update_mask_tensor)


            # 2.3. back-project and create texture
            # NOTE projection mask = update mask
            init_texture, project_mask_image, exist_texture = backproject_from_image(
                mesh, faces, new_verts_uvs, cameras, 
                update_image, update_mask_image, update_mask_image, init_texture, exist_texture, 
                args.image_size * args.render_simple_factor, args.uv_size, args.fragment_k,
                DEVICE
            )

            project_mask_image.save(os.path.join(mask_image_dir, "{}_project.png".format(view_idx)))

            # update the mesh
            mesh.textures = TexturesUV(
                maps=transforms.ToTensor()(init_texture)[None, ...].permute(0, 2, 3, 1).to(DEVICE),
                faces_uvs=faces.textures_idx[None, ...],
                verts_uvs=new_verts_uvs[None, ...]
            )

            # 2.4. save generated assets
            # save backprojected OBJ file            
            save_backproject_obj(
                mesh_dir, "{}.obj".format(view_idx),
                mesh_scale * mesh.verts_packed() + mesh_center if args.use_unnormalized else mesh.verts_packed(),
                faces.verts_idx, new_verts_uvs, faces.textures_idx, init_texture, 
                DEVICE
            )

            # save the intermediate view
            inter_images_tensor, *_ = render(mesh, renderer)
            inter_image = inter_images_tensor[0].cpu()
            inter_image = inter_image.permute(2, 0, 1)
            inter_image = transforms.ToPILImage()(inter_image).convert("RGB")
            inter_image.save(os.path.join(interm_dir, "{}.png".format(view_idx)))

            # save texture mask
            exist_texture_image = exist_texture * 255. 
            exist_texture_image = Image.fromarray(exist_texture_image.cpu().numpy().astype(np.uint8)).convert("L")
            exist_texture_image.save(os.path.join(mesh_dir, "{}_texture_mask.png".format(view_idx)))

        print("=> total update time: {} s".format(time.time() - start_time))

        # post-process
        if args.post_process:
            del controlnet
            del ddim_sampler

            inpainting = get_inpainting(DEVICE)
            post_texture = apply_inpainting_postprocess(inpainting, 
                init_texture, 1-exist_texture[None, :, :, None], "", args.uv_size, args.uv_size, DEVICE)

            save_backproject_obj(
                mesh_dir, "{}_post.obj".format(view_idx),
                mesh_scale * mesh.verts_packed() + mesh_center if args.use_unnormalized else mesh.verts_packed(),
                faces.verts_idx, new_verts_uvs, faces.textures_idx, post_texture, 
                DEVICE
            )
    
        # save viewpoints
        save_viewpoints(args, output_dir, dist_list, elev_list, azim_list, selected_view_ids)

        # visualize viewpoints
        visualize_refinement_viewpoints(output_dir, selected_view_ids, dist_list, elev_list, azim_list)
        
    # output total time used and save to the output directory
    print("=> total time used: {} s".format(time.time() - tik))
    with open(os.path.join(output_dir, "time.txt"), "w") as f:
        f.write("total time used: {} s".format(time.time() - tik))

    return output_dir


if __name__ == "__main__":
    args = init_args()
    text2tex_call(args)