This is because the default number of epoches for training is 300. You can modify it here.
In addition, we noticed that you did not modify exp_name, using the default 'dtu_pretrain', during training, the code will first check whether there is checkpoint in trained_model/mvsgs/exp_name, if there is, it will load latest.pth. So if your exp_name is 'dtu_pretrain', the model will load the weight of trained_model/mvsgs/dtu_pretrain/latest.pth, and then continue training. If you want to train our model on your own data from scratch, you will need to change exp_name to something else. Of course, if you just want to fine-tune model, it's fine to do so. Just a reminder ~

from mvsgaussian.

We only provide commands in the readme to inference on custom data using our pre-trained model, if you need training, you can execute the following commands:

python train_net.py --cfg_file configs/mvsgs/colmap_eval.yaml train_dataset.data_root examples/scene1 test_dataset.data_root examples/scene1

You can also specify batchsize:

python train_net.py --cfg_file configs/mvsgs/colmap_eval.yaml train_dataset.data_root examples/scene1 test_dataset.data_root examples/scene1 train.batch_size 2

Note that we updated the lib/datasets/colmap/mvsgs.py file by adding two lines of code to ensure that the test view is not visible when training.

from mvsgaussian.

I followed your method, but there were some errors. I hope you can give me some help.

from mvsgaussian.

I only changed this sentence in the entire source code.Because my image suffix is JPG.

from mvsgaussian.

Your modification may be inappropriate, consider replacing it with:

img_paths = sorted([item for item in os.listdir(os.path.join(self.data_root, 'images')) if ('.png' in item) or ('.jpg' in item) or ('.JPG' in item)])

from mvsgaussian.

('.JPG' or '.png'or '.jpg') is equivalent to '.JPG', but your image suffix is indeed JPG, so I suspect this error may be caused by environmental issues, can you successfully run our data?

from mvsgaussian.

scene2 is your data (images)
python lib/colmap/imgs2poses.py -s examples/scene2 Running successfully
python run.py --type evaluate --cfg_file configs/mvsgs/colmap_eval.yaml test_dataset.data_root examples/scene2 Running successfully
python train_net.py --cfg_file configs/mvsgs/colmap_eval.yaml train_dataset.data_root examples/scene2 test_dataset.data_root examples/scene2 Running fail

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We re-clone the repo and can run the above three commands successfully. Can you post your environment (Python version, pip/conda environment, etc.)? That might help narrow down the issue.

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Name Version Build Channel

av 10.0.0 pypi_0 pypi
backcall 0.2.0 pypi_0 pypi
ca-certificates 2024.3.11 haa95532_0
certifi 2022.12.7 py37haa95532_0
charset-normalizer 3.3.2 pypi_0 pypi
colorama 0.4.6 pypi_0 pypi
cycler 0.11.0 pypi_0 pypi
decorator 5.1.1 pypi_0 pypi
diff-gaussian-rasterization 0.0.0 pypi_0 pypi
fonttools 4.38.0 pypi_0 pypi
idna 3.7 pypi_0 pypi
imageio 2.27.0 pypi_0 pypi
imageio-ffmpeg 0.5.1 pypi_0 pypi
imgaug 0.4.0 pypi_0 pypi
ipdb 0.13.13 pypi_0 pypi
ipython 7.34.0 pypi_0 pypi
jedi 0.19.1 pypi_0 pypi
kiwisolver 1.4.5 pypi_0 pypi
kornia 0.6.12 pypi_0 pypi
lpips 0.1.4 pypi_0 pypi
matplotlib 3.5.3 pypi_0 pypi
matplotlib-inline 0.1.6 pypi_0 pypi
networkx 2.6.3 pypi_0 pypi
numpy 1.21.6 pypi_0 pypi
opencv-python 4.10.0.84 pypi_0 pypi
openssl 1.1.1w h2bbff1b_0
packaging 24.0 pypi_0 pypi
parso 0.8.4 pypi_0 pypi
pickleshare 0.7.5 pypi_0 pypi
pillow 9.5.0 pypi_0 pypi
pip 22.3.1 py37haa95532_0
plyfile 0.9 pypi_0 pypi
prompt-toolkit 3.0.47 pypi_0 pypi
protobuf 4.24.4 pypi_0 pypi
psutil 6.0.0 pypi_0 pypi
pygments 2.17.2 pypi_0 pypi
pyparsing 3.1.2 pypi_0 pypi
python 3.7.13 h6244533_1
python-dateutil 2.9.0.post0 pypi_0 pypi
pywavelets 1.3.0 pypi_0 pypi
pyyaml 6.0.1 pypi_0 pypi
requests 2.31.0 pypi_0 pypi
scikit-image 0.19.0 pypi_0 pypi
scipy 1.7.3 pypi_0 pypi
setuptools 65.6.3 py37haa95532_0
shapely 2.0.4 pypi_0 pypi
simple-knn 0.0.0 pypi_0 pypi
six 1.16.0 pypi_0 pypi
sqlite 3.45.3 h2bbff1b_0
tensorboardx 2.6.2.2 pypi_0 pypi
termcolor 2.3.0 pypi_0 pypi
tifffile 2021.11.2 pypi_0 pypi
tomli 2.0.1 pypi_0 pypi
torch 1.13.1+cu116 pypi_0 pypi
torchaudio 0.13.1+cu117 pypi_0 pypi
torchvision 0.14.1+cu116 pypi_0 pypi
tqdm 4.66.4 pypi_0 pypi
traitlets 5.9.0 pypi_0 pypi
typing-extensions 4.7.1 pypi_0 pypi
urllib3 2.0.7 pypi_0 pypi
vc 14.2 h2eaa2aa_4
vs2015_runtime 14.29.30133 h43f2093_4
wcwidth 0.2.13 pypi_0 pypi
wheel 0.38.4 py37haa95532_0
wincertstore 0.2 py37haa95532_2

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I have reproduced Gaussian, AtomGS, 2DGS, Gaussian Pro, and others before, all of which can run normally. I am not sure why I was unable to successfully reproduce this excellent paper.I hope you can give me some advice.

from mvsgaussian.

from mvsgaussian.

Hello, I have carefully looked at your environment and found that there is no problem.

The cause of this error may be that multiprocessing is not supported on Windows. You can:

1. Set num_workers = 0. You can modify num_workers here, which will slow down training compared to multiple num_workers.
2. Use Linux.

from mvsgaussian.

Thank you very much. I can train normally by setting numw_workers= 0.

from mvsgaussian.

It's strange, I've been training scenario 2 for 4 hours. Is this normal? If it's not normal, what's going on?

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