Closed pavan4 closed 4 years ago
I commented out that piece and was able to move past the compilation step. Upon running the sample I get this error:
CUDASceneRepChunkGrid::create:386: out of memory.
I have an Nvidia 2070 GPU card. Any parameters to tweak to let me run the demo with fountain_all
data?
Did anyone have luck running this?
I commented out that piece and was able to move past the compilation step. Upon running the sample I get this error:
CUDASceneRepChunkGrid::create:386: out of memory.
I have an Nvidia 2070 GPU card. Any parameters to tweak to let me run the demo withfountain_all
data?Did anyone have luck running this?
Hi, Did you figure out this issue?
Yes, I was able to run the demo by setting these parameters:
This got rid of CUDASceneRepChunkGrid
OOM error
s_hashNumBuckets = 50000;
s_hashNumSDFBlocks = 50000;
However, I am getting an OOM errorCUDASceneRepHashSDF
with this https://github.com/KAIST-VCLAB/texturefusion/blob/22dd0eef639e9b00179867cbedeec4c72b95ef98/Source/CUDASceneRepHashSDF.h#L198
So I had to also set
s_offlineProcessing = false;
@pavan4 Is it possible to setup and run the texturefusion code on Ubuntu pc with 2080ti gpu.
I am looking to setup the code, your suggestion on hardware and OS requirements will be very helpful.
Thanks
@pavan4 Is it possible to setup and run the texturefusion code on Ubuntu pc with 2080ti gpu.
I am looking to setup the code, your suggestion on hardware and OS requirements will be very helpful.
Thanks
It should work. I was able to run on RTX 2070
Hi @pavan4 Thanks for the quick reply.
I have compiled the vowel hashing repo and will replace the source folder in voxelhashing cuda folder with the source folder from texture fusion repo.
Does this work straight away or are you facing issues while doing that.?
How is the quality of the result 3D volume on your own data with texture fusion?
Thanks
@chunduri11 , yeah those are the steps to get going. However, I had to spend some time to get the project to compile.
I made a PR here with the complete project integrated with voxel hashing : https://github.com/KAIST-VCLAB/texturefusion/pull/3 which should be quite straight forward to build
The quality of the result on my own data was not great or at least equivalent to the output of the dataset. The code still needs a major bit of work in terms of optimisation.
Hi @pavan4, thanks for the reply and the inputs. Very useful.
I am new to 3D reconstruction and also c++, your inputs are very helpful to me.
I am trying to compile your refactored code. I am facing errors related to NuiApi.h and NuiSkeleton.h. From my exploration I see that these files are related to Kinect sdk 1.8, but I am using Kinect sdk 2.0 and corresponding runtime drivers. Does ur refactored code work with Kinect sdk 2.0 with its runtime drivers or should I use Kinect sdk 1.8?
Thanks again.
@pavan4 I have managed to compile the refactored code that you shared.
After compiling, when I run the code with the waterfall dataset, I am running into an error after reading the rib and depth images.
The error is as follows: "DX11RGBDRenderer.h(132) : cudaSafeCall() Runtime API error 101: decompressing frame invalid device ordinal."
Ever after this error message decompressing frame continues till 9 and stops execution.
Can you please help me in what is going wrong and how I can resolve this issue and ensure that I am able to generated 3D models for the waterfall dataset given in the repository?
Thanks
Hi, I'm trying to make your PR work, thank you for your modification! @pavan4 I have a question, is it possible to save the textured mesh in the end? I'd like to save the reconstructed mesh result.
Thank you for the code!
Is the recent commit up to date? The code fails to compile at this place:
I only see
extern "C" void renderCorrespondenceCUDA(unsigned int imageWidth, unsigned int imageHeight, float *output, CameraTrackingInput cameraTrackingInput, float* intrinsics, CameraTrackingParameters cameraTrackingIParameters, float* transform);
But no definition for this in code? Am I missing something here?
fyi, I am able to compile and run
voxelhashing