Comments (10)
Hi @ch1998 , were you successful in running the code? I mean I wanted to test the capabilities by giving prompt and checking what it generated. but the main issue is running the following command starts a training session which I dont want:
python launch.py --config configs/gaussiandreamer-sd.yaml --train --gpu 0 system.prompt_processor.prompt="a fox"
Did you find a way to test the model out-of-the-box without training it ?
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Sorry, I completed the training but didn't find a way to test it directly.
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@ch1998 Ah great how long did it take to complete the training?
Could you share the steps you used to install the code, I found that the steps mentioned in the Get Started section doesnot work if ran step by step
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Training takes about 10 minutes.
install step:
git clone https://github.com/hustvl/GaussianDreamer.git
cd GaussianDreamer
pip install torch==2.0.1+cu118 torchvision==0.15.2+cu118 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
pip install ninja
Modify xformers==0.0.20 in requirements.txt
pip install -r requirements.txt
pip install ./gaussiansplatting/submodules/diff-gaussian-rasterization
pip install ./gaussiansplatting/submodules/simple-knn
git clone https://github.com/openai/shap-e.git
cd shap-e
pip install -e .
pip install open3d
pip install plyfile
Please refer to #2 .
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@ch1998 great thanks... just one question i saw you have requirements.txt
file even before cloning the GaussianDreamer
Repo..
THe only requirements.txt
file I saw is inside the repo.. Where did you get the requirements.txt
before cloning the repo?
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@ch1998 great thanks... just one question i saw you have
requirements.txt
file even before cloning theGaussianDreamer
Repo.. THe onlyrequirements.txt
file I saw is inside the repo.. Where did you get therequirements.txt
before cloning the repo?
first,git clone https://github.com/hustvl/GaussianDreamer.git
then,other steps.
Sorry, the steps are in the wrong order.
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@ch1998 thank you so much for your help!!!
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@ch1998 could you tell me which GPU you used to reduce the training time to 10 mins, I am using T4 GPU on COlab and the time it takes is rediculously long.
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I am using a 3090. The first run will take some time. Some shape-e related files will be generated, which will take about an hour. Then there will be formal training, which will take about 10 minutes.
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Hello, I successfully ran the code, but when the training reached normal level, the program did not continue. Is there any error? There is stabilityai/stable-diffusion-2-1-base in gaussiandreamer-sd.yaml. Is it because I did not download the pre-trained model?
i met the same problem.I encountered this situation when running this code on both RTX3090 and RTX3080. When I reached this state, there was no next step. At most, I ran it for almost 4 hours without taking any further steps, and my memory status did not change during the run.
how can i sovel it?thanks!!!!!!!
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Related Issues (20)
- More less gaussian point?
- ply sotre the color info? HOT 1
- stand.obj HOT 1
- How to render the image with white background? HOT 1
- GPU Not Called HOT 1
- Generating quality HOT 2
- Failed to build pysdf ERROR: Could not build wheels for pysdf, which is required to install pyproject.toml-based projects HOT 1
- ERROR: Could not build wheels for pysdf, which is required to install pyproject.toml-based projects HOT 1
- Halfway through the execution, there was no response HOT 1
- About orthographic projection of Gaussian Splatting
- Question about the final result HOT 8
- type error HOT 1
- Assistance Requested for Replicating CLIP Score Calculations from Your Paper HOT 3
- Colab example broken due to mismatched dependencies HOT 1
- FileNotFoundError: [Errno 2] No such file or directory: './load/shapE_finetuned_with_330kdata.pth' HOT 1
- could not build wheels for diff-gaussian-rasterization
- Download finetuned Shap-E by Cap3D 消失 HOT 1
- T3Bench score calculation
- 执行代码遇到的一些问题
- ERROR: Failed to build installable wheels for some pyproject.toml based projects (diff_gaussian_rasterization) HOT 2
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