How to reproduce llff dataset

[zkaiWu]

I use the command

"ns-process-data images --data /data5/wuzhongkai/data/dreamfusion_data/llff/nerf_llff_data/flower --output-dir /data5/wuzhongkai/data/dreamfusion_data/llff/nerf_llff_data/flower --skip_colmap --colmap_model_path sparse/0 --skip_image_processing"

to generate transform.json and use the command

CUDA_VISIBLE_DEVICES=$1 ns-train nerfacto --data /data/nerf_llff_data/flower/transforms.json
--experiment-name llff/flower --vis wandb
nerfstudio-data

to train the model, but get bad result. Are there any key points to train the nerfacto on llff

[lixinyu123-lxy]

almost the same.I use vanilla-nerf to train the fox dataset of instant-ngp but get awful result with blurry color blocks but no convergence. I use the same command "ns-process-data ..." and get a transforms.json and then use command "ns-train vanilla-nerf ...... nerfstudio-data" to train it. Also ,I notice that it works the same in mipnerf , and it's weird that its training time remain the same when I use different numbers of pictures to train.

[tancik]

The vanilla-nerf and mipnerf models are setup to work with the blender synthetic data, not real-world data. For real-world data, use nerfacto or instant-ngp

[lixinyu123-lxy]

和模型设置为使用搅拌机合成数据，而不是真实世界的数据vanilla-nerf。mipnerf对于真实世界的数据，使用nerfacto或instant-ngp

How can I prepare this Blender data to train and reconstruct on Mip-NeRF or Vanilla-NeRF by using colmap? I also noticed that if the command ns-train is used without the nerfstudio-data suffix, the system assumes the data format is Blender data, but it throws an error saying that transforms_train.json cannot be found.

[MvWouden]

The vanilla-nerf and mipnerf models are setup to work with the blender synthetic data, not real-world data. For real-world data, use nerfacto or instant-ngp

Are there any mipnerf parameters we could try to change to make it more "suitable" for real-world bounded data like this?

[Arcxml]

Hello, I would like to ask if you have solved this problem?