Hello. I am trying to run the code on Google Colab. While trying to install the third party dependency (following the instructions given in the Dockerfile) octree_handler via the command:

cd depoco/submodules/octree_handler && pip3 install -U .

...I get the following error:

Processing /content/git-clone/submodules/octree_handler
  DEPRECATION: A future pip version will change local packages to be built in-place without first copying to a temporary directory. We recommend you use --use-feature=in-tree-build to test your packages with this new behavior before it becomes the default.
   pip 21.3 will remove support for this functionality. You can find discussion regarding this at https://github.com/pypa/pip/issues/7555.
Building wheels for collected packages: octree-handler
  Building wheel for octree-handler (setup.py) ... error
  ERROR: Failed building wheel for octree-handler
  Running setup.py clean for octree-handler
Failed to build octree-handler
Installing collected packages: octree-handler
    Running setup.py install for octree-handler ... error
ERROR: Command errored out with exit status 1: /usr/bin/python3 -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-7l37y9ju/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-7l37y9ju/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-qzusj2ky/install-record.txt --single-version-externally-managed --compile --install-headers /usr/local/include/python3.7/octree-handler Check the logs for full command output.

Hello @louis-wiesmann . After training the model to at the default params with epochs=15, I am using the trained model to test the results on a sample point cloud.

The input cloud I used for testing when looked from side looks like this :

On the other hand, the output obtained from the decoder looks like this:

As is clearly visible, the output from the decoder has a somewhat layered structure. Is there any way to minimize this / correct this?

Some other info:

1. Total points in the original cloud = 11,000,000
2. max_nr_points (set in the yaml file) = 60,000

Also, I am getting some big clusters in the outputs that I get from the decoder...as can be seen in sample outputs below :

Input Cloud	Output Cloud

Can you please tell if there is any parameter that can be tweaked in the YAML config file to get rid of this layered clustering. Or is there any other way to minimize or eliminate this ?

NOTE : I have already seen the other issue on clustering, but in my case the clusters seem to be large.

Thanks

Hello @louis-wiesmann . Is there any way to retain the class labels of the points obtained after decompression from the decoder?

Thanks in advance. Aakash

when I install the 3rdparty dependencies, I meet the problem:

deep-point-map-compression/submodules/octree_handler$ pip3 install -U .

the problem is:

/home/bianjiang/CVPR/deep-point-map-compression/submodules/octree-handler/src/OctreeHandler.cpp: In member function ‘Eigen::MatrixXf Octree::computeEigenvaluesNormal(const float&)’: /home/bianjiang/CVPR/deep-point-map-compression/submodules/octree-handler/src/OctreeHandler.cpp:181:12: error: ‘cout’ is not a member of ‘std’ 181 | std::cout << "sing: " << singularv | ^~~~ /home/bianjiang/CVPR/deep-point-map-compression/submodules/octree-handler/src/OctreeHandler.cpp:9:1: note: ‘std::cout’ is defined in header ‘’; did you forget to ‘#include ’? 8 | #include <eigen3/Eigen/Dense> +++ |+#include 9 | #include make[2]: *** [src/CMakeFiles/octree_handler.dir/build.make:63：src/CMakeFiles/octree_handler.dir/OctreeHandler.cpp.o] error 1 make[1]: *** [CMakeFiles/Makefile2:94：src/CMakeFiles/octree_handler.dir/all] error 2 make: *** [Makefile:84：all] error 2

I solve this probelm by add #include <iostream> to deep-point-map-compression/submodules/octree-handler/src/OctreeHandler.h

So if anyone meets the same problem, this method may work.