threestudio
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A unified framework for 3D content generation.
🎉 Hi guys and maintainers, we just release [Hash3D](https://github.com/Adamdad/hash3D) that aims to accelerate SDS for free. It is universal, so that any text23D or image23D code can benefit from our...
I am facing this after setting up the Docker project: ```python dreamer@9d615a31c0af:~/threestudio$ python launch.py --config configs/dreamfusion-if.yaml --train --gpu 0 system.prompt_processor.prompt="white flully dog :)" trainer.max_steps=10000 system.prompt_processor.spawn=false Traceback (most recent call last):...
## summary * GaussianDreamer installation was successful * Successfully created `point_cloud.ply` file under `outputs/gs-sds-mvdream/an_astronaut_wearing_a_blue_suit@20240329-022833/save`, and `last.ckpt` under `gs-sds-mvdream/an_astronaut_wearing_a_blue_suit@20240329-022833/ckpts` * Tried running `Mesh export` commands causes `Missing mandatory value: tag` error...
is there any plan to embed sv3d into threestudio?
While running **DreamFusion**, I wanted to delve deeper into the values of gradients, but I found that the following two values are different (though I merely decomposed it manually using...
https://discuss.pytorch.org/t/saving-tensor-with-torch-save-uses-too-much-memory/46865/2 saving the text embedding as cache without .clone() will have the file size of whole tensor.
For example, when the batch_size = 2, the arrangement of text embeddings is [pos_b_1, pos_b_2, uncond_b_1, uncond_b_2, neg_1_b_1, neg_2_b_1, neg_1_b_2, neg_2_b_2], while the arrangement of $t$ is [t_b_1, t_b_2] *...
Hi, Thank you all for a great git! I want to try some new thing instead use the text prompt diffusion model to generate 3d I want to try the...
I have tried to run a couple of Image-to-3D methods, including Wonder3D, TripoSR, SV3D, etc. The output of these methods is all single .obj file without .mtl and textured_UV maps....
The current volsdf alpha value is computed as: alpha = torch.abs(dists.detach()) * volsdf_density(sdf, inv_std) I believe the actual formula should be: alpha = 1 - torch.exp(-dists * volsdf_density(sdf, inv_std) )...