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# 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) |