Open altava-sgp opened 2 months ago
Hello, can you check how to you set the path to your threestudio package. I am sure that the class of zero123-unified-guidance-cache
is inside the code but it seems that you cannot access this class. Can you please check?
@Adamdad The structure of folders and files is here.
Can you run the code again, and set export PYTHONPATH="$PWD"
before running your script?
It pauses for a little time after this...
$ pwd
/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d
$
$ export PYTHONPATH="$PWD"
$
$ python launch.py --config configs/stable-zero123_hash3d.yaml --train --gpu 0 data.image_path=load/images/dog1_rgba.png
Global seed set to 0
find: single-image-datamodule
find: zero123-system
find: implicit-volume
find: diffuse-with-point-light-material
find: solid-color-background
find: nerf-volume-renderer
[INFO] ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None) will duplicate the last checkpoint saved.
[INFO] GPU available: True (cuda), used: True
[INFO] TPU available: False, using: 0 TPU cores
[INFO] IPU available: False, using: 0 IPUs
[INFO] HPU available: False, using: 0 HPUs
[INFO] You are using a CUDA device ('NVIDIA GeForce RTX 4090') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
[INFO] single image dataset: load image load/images/dog1_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load image load/images/dog1_rgba.png torch.Size([1, 128, 128, 3])
[INFO] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
I am waiting...
I run command in docker terminal.
Eventually I got this error again.
$ pwd
/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d
$
$ export PYTHONPATH="$PWD"
$
$ python launch.py --config configs/stable-zero123_hash3d.yaml --train --gpu 0 data.image_path=load/images/dog1_rgba.png
Global seed set to 0
find: single-image-datamodule
find: zero123-system
find: implicit-volume
find: diffuse-with-point-light-material
find: solid-color-background
find: nerf-volume-renderer
[INFO] ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None) will duplicate the last checkpoint saved.
[INFO] GPU available: True (cuda), used: True
[INFO] TPU available: False, using: 0 TPU cores
[INFO] IPU available: False, using: 0 IPUs
[INFO] HPU available: False, using: 0 HPUs
[INFO] You are using a CUDA device ('NVIDIA GeForce RTX 4090') that has Tensor Cores. To properly utilize them, you should set `torch.set_float32_matmul_precision('medium' | 'high')` which will trade-off precision for performance. For more details, read https://pytorch.org/docs/stable/generated/torch.set_float32_matmul_precision.html#torch.set_float32_matmul_precision
[INFO] single image dataset: load image load/images/dog1_rgba.png torch.Size([1, 128, 128, 3])
[INFO] single image dataset: load image load/images/dog1_rgba.png torch.Size([1, 128, 128, 3])
[INFO] LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
[INFO]
| Name | Type | Params
-------------------------------------------------------------
0 | geometry | ImplicitVolume | 12.6 M
1 | material | DiffuseWithPointLightMaterial | 0
2 | background | SolidColorBackground | 0
3 | renderer | NeRFVolumeRenderer | 0
-------------------------------------------------------------
12.6 M Trainable params
0 Non-trainable params
12.6 M Total params
50.450 Total estimated model params size (MB)
[INFO] Validation results will be saved to outputs/zero123-sai-hash3d/[64, 128, 256]_dog1_rgba.png@20240418-092826/save
find: zero123-unified-guidance-cache
Traceback (most recent call last):
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/launch.py", line 301, in <module>
main(args, extras)
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/launch.py", line 244, in main
trainer.fit(system, datamodule=dm, ckpt_path=cfg.resume)
File "/home/dreamer/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 532, in fit
call._call_and_handle_interrupt(
File "/home/dreamer/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 43, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/dreamer/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 571, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "/home/dreamer/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/trainer.py", line 961, in _run
call._call_lightning_module_hook(self, "on_fit_start")
File "/home/dreamer/.local/lib/python3.10/site-packages/pytorch_lightning/trainer/call.py", line 146, in _call_lightning_module_hook
output = fn(*args, **kwargs)
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/systems/zero123.py", line 40, in on_fit_start
self.guidance = threestudio.find(self.cfg.guidance_type)(self.cfg.guidance)
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/__init__.py", line 33, in find
return __modules__[name]
KeyError: 'zero123-unified-guidance-cache'
can git pull again? I just push one line of code
I got this error.
$ pwd
/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d
$
$ python launch.py --config configs/stable-zero123_hash3d.yaml --train --gpu 0 data.image_path=load/images/dog1_rgba.png
Traceback (most recent call last):
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/launch.py", line 301, in <module>
main(args, extras)
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/launch.py", line 135, in main
import threestudio
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/__init__.py", line 55, in <module>
from . import data, models, systems
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/models/__init__.py", line 1, in <module>
from . import (
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/models/guidance/__init__.py", line 1, in <module>
from . import (
File "/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/models/guidance/zero123_unified_guidance_cache.py", line 31, in <module>
from threestudio.utils.hash_table import GridBasedHashTable, GridBasedHashTable_Sim, AdaptiveGridBasedHashTable, GridBasedHashTable_Key
ImportError: cannot import name 'GridBasedHashTable_Key' from 'threestudio.utils.hash_table' (/home/dreamer/threestudio/custom/hash3D/threestudio-hash3d/threestudio/utils/hash_table.py)
Sorry, just remove this. Can pull again. GridBasedHashTable_Key
is an ablated version of my full method.
It is working!
Let's see what will happen
It continues...
So can I use this ckpt file to proceed next steps ?
Yes, threestudio can help you to convert this ckpt to mesh .obj and can be applied to other applications.
@Adamdad Are you in threestudio discord server ?
Yes I am in, but I never send any message there.
Can you give a star on the project? Thank you so much!
I run this command.
I got this error.
What's the problem ?