Comments (10)
I think my problem is not compatible with cuda and cudnn version in my device. So I will try to change those version compatible with my device and ask again for more details. Please don't close this issue, and thank you for your quick answer.
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I solve this problem by changing cudatoolkit=10.2 to cudatoolkit=11.1. Thank you for your help.
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Thanks a lot for your interest in our work.
Could you please provide more details about your use case, e.g., the command, GPU memory, CUDA version, and cuDNN version?
I just searched around with your error message, it may come from not-enough GPU memory, see this link. If this is the case, you could try to use small chunk_n_planes
as mentioned in the README and #14
Hope this helps.
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I'm sorry, but when I apply rendering a video according to your code
Render a Video
The following command renders a video in ${OUTPUT_DIR}, along with:
video_rgb.mp4: video for the RGB rendering,
video_depth.mp4: video for the depth rendering.
conda activate gmpi && \
export PYTHONPATH=${GMPI_ROOT}:${GMPI_ROOT}/gmpi/models:$PYTHONPATH && \
python ${GMPI_ROOT}/gmpi/eval/vis/render_video.py \
--ckpt_path ${OUTPUT_DIR}/generator.pth \
--output_dir ${OUTPUT_DIR} \
--seeds ${SEED} \
--nplanes 96 \
--truncation_psi ${TRUNCATION_PSI} \
--exp_config ${OUTPUT_DIR}/config.pth \
--render_single_image 0 \
--horizontal_cam_move 1
I got this error,
TypeError: write_frames() got an unexpected keyword argument 'audio_path'
Could you tell me what is the problem??
I make rendering a video code to bash file, like this:
export GMPI_ROOT=$PWD
export DATASET_NAME=FFHQ512
export OUTPUT_DIR=${GMPI_ROOT}/ckpts/gmpi_pretrained/${DATASET_NAME}
export SEED=11
export TRUNCATION_PSI=1.0
export PYTHONPATH=${GMPI_ROOT}:${GMPI_ROOT}/gmpi/models:$PYTHONPATH && \
python ${GMPI_ROOT}/gmpi/eval/vis/render_video.py \
--ckpt_path ${OUTPUT_DIR}/generator.pth \
--output_dir ${OUTPUT_DIR} \
--seeds ${SEED} \
--nplanes 32 \
--truncation_psi ${TRUNCATION_PSI} \
--exp_config ${OUTPUT_DIR}/config.pth \
--render_single_image 0 \
--horizontal_cam_move 1
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Do you mind posting the full traceback if possible? That would be helpful here.
And what is the version of your package imageio
and imageio-ffmpeg
? My guts say that this is related to the package versions as
- For
imageio-ffmpeg
:0.4.3
does not have the argumentaudio_path
(this link) while the newer version has it (this link). - For
ffmpeg
:2.9.0
does not useaudio_path
when callingffmpeg
(this link) while the newer version uses it (this link).
So this may come from package incompatibility. If this is the case, you could consider either downgrading the imageio
or upgrading imageio-ffmpeg
. FYI: the combination of imageio=2.9.0
and imageio-ffmpeg=0.4.3
is the one that I find workable. But there are definitely many other combinations that could also work.
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Thanks for your help. The problem is the version of imageio. When I see environment.yml for setting environment, it install the newest version of imageio. But when I change imageio newest version to 2.9.0, it is solved.
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Thanks a lot for confirming the issue. Glad that it works now.
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Hello, thanks for your kind reply. I have other questions at Generative MultiPlane Image models.
In here, I'd like to see the parts of "Alpha Branch" in your paper. But when I see the code, all StyleGANv2 models came from pretrained model and the model was trained at face datasets, like FFHQ, MetFaces.
But I'd like to train my custom dataset(RealEstate10K frame images), and I guess it will not work because data domain is different.
My First Question is that I'd like to use your model at different domain datasets. In that case, I think I have to re-train StyleGANv2 to my custom datasets. Is it right??
And last Question is where is the Alpha Branch Part in your code when I evaluate FFHQ 512 dataset??
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Hi Albert, to answer your questions:
I'd like to use your model for different domain datasets. In that case, I think I have to re-train StyleGANv2 to my custom datasets. Is it right
Not necessary. You can directly train GMPI from the scratch. At least for FFHQ, we tried to train from the scratch before. The results look good. It will just take quite a long time as there is no prior from the pre-trained checkpoints anymore.
Another caveat I want to mention: GMPI needs a camera pose for the discriminator to be conditioned on. Essentially, this means that you need to be able to somehow provide camera poses for images from RealEstate10K. Frankly speaking, how to adapt GMPI to and whether GMPI will work well on such indoor scene data without further modification/adaptation is still an open research problem. Only experiments could tell.
where is the Alpha Branch Part in your code
Assume you use the model variant that conditions on normalized depth as mentioned here. Then this line could be a good starting point for you to understand how alphas are computed, i.e., checking how cond_x
is computed:
As the variable cond_x
will later be used to generate the alpha maps:
Hope these may help.
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Related Issues (20)
- environment.yml error HOT 13
- Problem In training the FFHQ1024 model HOT 3
- Great Work!!!!!! Few Queries HOT 7
- "RuntimeError: output is too large" when extracting meshes with 1024x1024 models HOT 2
- Problem in Importing upfirdn2d_plugin.so HOT 2
- RuntimeError: "slow_conv_transpose2d_out_cpu" not implemented for 'Half' HOT 1
- Great Work!!!!! HOT 9
- I got error when I start to train HOT 9
- download FFHQ tfrecord dataset related issue HOT 1
- Problem in reproducing fid score HOT 9
- Maximum range of yaw and pitches HOT 1
- 感觉真是充满坑点 HOT 1
- pose of AFHQ HOT 2
- Great Work!!!! Few queries regarding the evaluation code HOT 3
- Query Regarding the evaluation code for FFHOQ512 HOT 6
- Problem in calculating the Identity metric
- Query in calculating the depth and pose metric HOT 1
- Code for estimating pose for preprocessing (used in "Deep3DFaceRecon" directory) HOT 1
- Problem in Reproducing the Depth score HOT 5
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