House3D: A Rich and Realistic 3D Environment

Last update: Dec 14, 2022

Related tags

Overview

House3D: A Rich and Realistic 3D Environment

Yi Wu, Yuxin Wu, Georgia Gkioxari and Yuandong Tian

House3D is a virtual 3D environment which consists of thousands of indoor scenes equipped with a diverse set of scene types, layouts and objects sourced from the SUNCG dataset. It consists of over 45k indoor 3D scenes, ranging from studios to two-storied houses with swimming pools and fitness rooms. All 3D objects are fully annotated with category labels. Agents in the environment have access to observations of multiple modalities, including RGB images, depth, segmentation masks and top-down 2D map views. The renderer runs at thousands frames per second, making it suitable for large-scale RL training.

Usage instructions can be found at INSTRUCTION.md

Existing Research Projects with House3D

A. RoomNav (paper)

Yi Wu, Yuxin Wu, Georgia Gkioxari, Yuandong Tian

In this work we introduce a concept learning task, RoomNav, where an agent is asked to navigate to a destination specified by a high-level concept, e.g. dining room. We demonstrated two neural models: a gated-CNN and a gated-LSTM, which effectively improve the agent's sensitivity to different concepts. For evaluation, we emphasize on generalization ability and show that our agent can generalize across environments due to the diverse and large-scale dataset.

B. Embodied QA (project page | EQA paper | NMC paper)

Abhishek Das, Samyak Datta, Georgia Gkioxari, Stefan Lee, Devi Parikh, Dhruv Batra

Embodied Question Answering is a new AI task where an agent is spawned at a random location in a 3D environment and asked a natural language question ("What color is the car?"). In order to answer, the agent must first intelligently navigate to explore the environment, gather information through first-person (egocentric) vision, and then answer the question ("orange").

Citation

If you use our platform in your research, you can cite us with:

@article{wu2018building,
  title={Building generalizable agents with a realistic and rich 3D environment},
  author={Wu, Yi and Wu, Yuxin and Gkioxari, Georgia and Tian, Yuandong},
  journal={arXiv preprint arXiv:1801.02209},
  year={2018}
}

License

House3D is released under the Apache 2.0 license.

Comments

Error occurred when compile to build objrender

when I runing SYSTEM=conda.linux PYTHON_CONFIG=/home/zjw/anaconda3/envs/LG/bin/python-config make -j It comes that: /usr/include/glm/detail/type_vec3.inl:86:33: error: invalid static_cast from type ‘const glm::detail::tvec3<float, (glm::precision)0u>’ to type ‘float’ /usr/include/glm/detail/type_vec3.inl:86:33: error: invalid static_cast from type ‘const glm::detail::tvec3<float, (glm::precision)0u>’ to type ‘float’

make: *** [build/objview-suncg.o] Error 1 make: *** [build/suncg/render.o] Error 1

opened by Zzmonica 43

error: ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061

I am using the docker to run House3D so I guess there is no build issues. When I run python3 test-rendering.py $TEST_HOUSE or ./renderer/test-rectangle.bin headless the error error: ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061 occur.

The output of ./debug-build.sh is as follow:

PATH:
/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin

CPATH:


PKG_CONFIG_PATH:


LIBRARY_PATH:


LD_LIBRARY_PATH:
/usr/lib/x86_64-linux-gnu:/usr/lib/i386-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64

PYTHONPATH:


ldconfig:
	libEGL_nvidia.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.0
	libEGL_nvidia.so.0 (libc6) => /usr/lib/i386-linux-gnu/libEGL_nvidia.so.0
	libEGL_mesa.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0
	libEGL_mesa.so.0 (libc6) => /usr/lib/i386-linux-gnu/libEGL_mesa.so.0
	libEGL.so.1 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so.1
	libEGL.so.1 (libc6) => /usr/lib/i386-linux-gnu/libEGL.so.1
	libEGL.so (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so
	libEGL.so (libc6) => /usr/lib/i386-linux-gnu/libEGL.so
+ pkg-config --cflags --libs glfw3
-lglfw
+ '[' '!' '' ']'
+ pkg-config --cflags --libs libglvnd

+ pkg-config --cflags --libs egl
-I/usr/include/libdrm -lEGL
+ which find
/usr/bin/find
+ which pkg-config
/usr/bin/pkg-config
+ which python3-config
/usr/bin/python3-config
+ python3-config --includes --ldflags
-I/usr/include/python3.6m -I/usr/include/python3.6m
-L/usr/lib/python3.6/config-3.6m-x86_64-linux-gnu -L/usr/lib -lpython3.6m -lpthread -ldl  -lutil -lm  -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions
+ '[' ']'
+ g++ --version
g++ (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

+ '[' -f ../House3D/objrender.so ']'
+ '[' -f objview.bin ']

The output of ./test-rectangle.bin egl is :

[EGL] Detected 1 devices. Using device 0
----------- OpenGL Context Info --------------
GL Version: 4.5.0 NVIDIA 384.130
GLSL Version: 4.50 NVIDIA
Vendor: NVIDIA Corporation
Renderer: GeForce GTX 1060 6GB/PCIe/SSE2

The output of ./test-rectangle.bin headless is:

----------- OpenGL Context Info --------------
GL Version: 3.3.0 NVIDIA 384.130
GLSL Version: 3.30 NVIDIA via Cg compiler
Vendor: NVIDIA Corporation
Renderer: GeForce GTX 1060 6GB/PCIe/SSE2
----------------------------------------------
error: ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061

Many thanks!

opened by weihaosky 13

Error in running objview-offline.bin

Hi, I am getting the following error when I run objview-offline.bin.

[EGL] Detected 0 devices. Using device 0 assertion "device < numDevices" failed, in EGLContext, (gl/glContext.cc:137) Aborted (core dumped)

Here's the output of debug_build.sh

PATH:
/root/anaconda3/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/u
sr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin

CPATH:


PKG_CONFIG_PATH:


LIBRARY_PATH:
/usr/local/cuda/lib64/stubs:

LD_LIBRARY_PATH:
/root/anaconda3/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64

+ pkg-config --cflags --libs glew
Package glew was not found in the pkg-config search path.
Perhaps you should add the directory containing `glew.pc'
to the PKG_CONFIG_PATH environment variable
No package 'glew' found
+ pkg-config --cflags --libs glfw3
-I/usr/include/libdrm -lglfw
+ '[' '!' '' ']'
+ pkg-config --cflags --libs libglvnd
Package libglvnd was not found in the pkg-config search path.
Perhaps you should add the directory containing `libglvnd.pc'
to the PKG_CONFIG_PATH environment variable
No package 'libglvnd' found
+ pkg-config --cflags --libs egl
-I/usr/include/libdrm -lEGL
+ which find
/usr/bin/find
+ which pkg-config
/usr/bin/pkg-config
+ which python-config
/usr/bin/python-config
+ python-config --includes --ldflags
-I/usr/include/python2.7 -I/usr/include/x86_64-linux-gnu/python2.7
-L/usr/lib/python2.7/config-x86_64-linux-gnu -L/usr/lib -lpython2.7 -lpthread -ldl  -lutil -lm  -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions
+ '[' ']'
+ g++ --version
g++ (Ubuntu 5.4.0-6ubuntu1~16.04.6) 5.4.0 20160609
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

+ '[' -f ../House3D/objrender.so ']'
+ ldd ../House3D/objrender.so
        linux-vdso.so.1 =>  (0x00007ffefcbbc000)
        libpng16.so.16 => /root/anaconda3/lib/libpng16.so.16 (0x00007f9c7ea50000)
        libGL.so.1 => /usr/local/nvidia/lib64/libGL.so.1 (0x00007f9c7e7ac000)
        libEGL.so.1 => /usr/local/nvidia/lib64/libEGL.so.1 (0x00007f9c7e59a000)
        libX11.so.6 => /usr/lib/x86_64-linux-gnu/libX11.so.6 (0x00007f9c7e260000)
        libglfw.so.3 => /usr/lib/x86_64-linux-gnu/libglfw.so.3 (0x00007f9c7e04a000)
        libjpeg.so.9 => /root/anaconda3/lib/libjpeg.so.9 (0x00007f9c7de0e000)
        libpython3.6m.so.1.0 => /root/anaconda3/lib/libpython3.6m.so.1.0 (0x00007f9c7d8c9000)
        libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f9c7d6ac000)
        libstdc++.so.6 => /root/anaconda3/lib/libstdc++.so.6 (0x00007f9c7d372000)
        libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007f9c7d069000)
        libgcc_s.so.1 => /root/anaconda3/lib/libgcc_s.so.1 (0x00007f9c7ce57000)
        libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f9c7ca8d000)
        /lib64/ld-linux-x86-64.so.2 (0x00007f9c7ef87000)
        libz.so.1 => /root/anaconda3/lib/./libz.so.1 (0x00007f9c7c876000)
        libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007f9c7c672000)
        libGLX.so.0 => /usr/local/nvidia/lib64/libGLX.so.0 (0x00007f9c7c442000)
        libGLdispatch.so.0 => /usr/local/nvidia/lib64/libGLdispatch.so.0 (0x00007f9c7c174000)
        libxcb.so.1 => /root/anaconda3/lib/libxcb.so.1 (0x00007f9c7bf4b000)
        librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007f9c7bd43000)
        libXrandr.so.2 => /usr/lib/x86_64-linux-gnu/libXrandr.so.2 (0x00007f9c7bb38000)
        libXinerama.so.1 => /usr/lib/x86_64-linux-gnu/libXinerama.so.1 (0x00007f9c7b935000)
        libXi.so.6 => /usr/lib/x86_64-linux-gnu/libXi.so.6 (0x00007f9c7b725000)
        libXxf86vm.so.1 => /usr/lib/x86_64-linux-gnu/libXxf86vm.so.1 (0x00007f9c7b51f000)
        libXcursor.so.1 => /usr/lib/x86_64-linux-gnu/libXcursor.so.1 (0x00007f9c7b315000)
        libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007f9c7b112000)
        libXext.so.6 => /usr/lib/x86_64-linux-gnu/libXext.so.6 (0x00007f9c7af00000)
        libXau.so.6 => /usr/lib/x86_64-linux-gnu/libXau.so.6 (0x00007f9c7acfc000)
        libXrender.so.1 => /usr/lib/x86_64-linux-gnu/libXrender.so.1 (0x00007f9c7aaf2000)
        libXfixes.so.3 => /usr/lib/x86_64-linux-gnu/libXfixes.so.3 (0x00007f9c7a8ec000)

I am using Anaconda 3 inside a docker on a Ubuntu16 system with 2 Nvidia GPUs.

opened by devendrachaplot 12

Error when running test-rendering.py

Error message:

error: Failed to get function pointer of eglQueryDevicesEXT/eglGetPlatformDisplayEXT! Maybe EGL extensions are unsupported.

On Ubuntu 14.04. Exactly followed the instructions. glfw3 and glm were installed at /usr/local. Build command

PYTHON_CONFIG=python3-config make

Output of debug-build.sh

PATH:
/home/hzjiang/.nvm/versions/node/v8.9.4/bin:/usr/local/cuda/bin:/usr/local/cuda/bin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/usr/lib/jvm/java-8-oracle/bin:/usr/lib/jvm/java-8-oracle/db/bin:/usr/lib/jvm/java-8-oracle/jre/bin

CPATH:


PKG_CONFIG_PATH:


LIBRARY_PATH:


LD_LIBRARY_PATH:
/usr/local/lib:/usr/local/cuda/lib:/usr/local/cuda/lib64:/usr/local/cuda/lib:/usr/local/cuda/lib64:

+ pkg-config --cflags --libs glew
-I/usr/include/GL -I/usr/include/libdrm  -lGLEW -lGLU -lGL  
+ pkg-config --cflags --libs glfw3
-I/usr/local/include  -L/usr/local/lib -lglfw  
+ [ !  ]
+ pkg-config --cflags --libs libglvnd
Package libglvnd was not found in the pkg-config search path.
Perhaps you should add the directory containing `libglvnd.pc'
to the PKG_CONFIG_PATH environment variable
No package 'libglvnd' found
+ pkg-config --cflags --libs egl
-I/usr/include/libdrm  -lEGL  
+ which find
/usr/bin/find
+ which pkg-config
/usr/bin/pkg-config
+ which python-config
/usr/bin/python-config
+ python-config --includes --ldflags
-I/usr/include/python2.7 -I/usr/include/x86_64-linux-gnu/python2.7
-L/usr/lib/python2.7/config-x86_64-linux-gnu -L/usr/lib -lpthread -ldl  -lutil -lm  -lpython2.7 -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions
+ [ ]
+ g++ --version
g++ (Ubuntu 4.9.4-2ubuntu1~14.04.1) 4.9.4
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

+ [ -f ../House3D/objrender.so ]
+ ldd ../House3D/objrender.so
	linux-vdso.so.1 =>  (0x00007ffc26ddb000)
	libGL.so.1 => /usr/lib/x86_64-linux-gnu/mesa/libGL.so.1 (0x00007f5fa1fe4000)
	libEGL.so.1 => /usr/lib/x86_64-linux-gnu/mesa-egl/libEGL.so.1 (0x00007f5fa1dbf000)
	libX11.so.6 => /usr/lib/x86_64-linux-gnu/libX11.so.6 (0x00007f5fa1a8a000)
	libpng16.so.16 => /usr/local/lib/libpng16.so.16 (0x00007f5fa1858000)
	libglfw.so.3 => /usr/local/lib/libglfw.so.3 (0x00007f5fa1635000)
	libjpeg.so.8 => /usr/lib/x86_64-linux-gnu/libjpeg.so.8 (0x00007f5fa13e0000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f5fa11c2000)
	libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007f5fa0fbe000)
	libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007f5fa0dbb000)
	libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007f5fa0aa8000)
	libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007f5fa07a2000)
	libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007f5fa058b000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f5fa01c2000)
	/lib64/ld-linux-x86-64.so.2 (0x00007f5fa2846000)
	libglapi.so.0 => /usr/lib/x86_64-linux-gnu/libglapi.so.0 (0x00007f5f9ff9b000)
	libXext.so.6 => /usr/lib/x86_64-linux-gnu/libXext.so.6 (0x00007f5f9fd89000)
	libXdamage.so.1 => /usr/lib/x86_64-linux-gnu/libXdamage.so.1 (0x00007f5f9fb86000)
	libXfixes.so.3 => /usr/lib/x86_64-linux-gnu/libXfixes.so.3 (0x00007f5f9f980000)
	libX11-xcb.so.1 => /usr/lib/x86_64-linux-gnu/libX11-xcb.so.1 (0x00007f5f9f77e000)
	libxcb-glx.so.0 => /usr/lib/x86_64-linux-gnu/libxcb-glx.so.0 (0x00007f5f9f567000)
	libxcb-dri2.so.0 => /usr/lib/x86_64-linux-gnu/libxcb-dri2.so.0 (0x00007f5f9f362000)
	libxcb-dri3.so.0 => /usr/lib/x86_64-linux-gnu/libxcb-dri3.so.0 (0x00007f5f9f15f000)
	libxcb-present.so.0 => /usr/lib/x86_64-linux-gnu/libxcb-present.so.0 (0x00007f5f9ef5c000)
	libxcb-sync.so.1 => /usr/lib/x86_64-linux-gnu/libxcb-sync.so.1 (0x00007f5f9ed56000)
	libxcb.so.1 => /usr/lib/x86_64-linux-gnu/libxcb.so.1 (0x00007f5f9eb37000)
	libxshmfence.so.1 => /usr/lib/x86_64-linux-gnu/libxshmfence.so.1 (0x00007f5f9e935000)
	libXxf86vm.so.1 => /usr/lib/x86_64-linux-gnu/libXxf86vm.so.1 (0x00007f5f9e72f000)
	libdrm.so.2 => /usr/lib/x86_64-linux-gnu/libdrm.so.2 (0x00007f5f9e521000)
	libxcb-xfixes.so.0 => /usr/lib/x86_64-linux-gnu/libxcb-xfixes.so.0 (0x00007f5f9e31a000)
	libwayland-client.so.0 => /usr/lib/x86_64-linux-gnu/libwayland-client.so.0 (0x00007f5f9e10d000)
	libwayland-server.so.0 => /usr/lib/x86_64-linux-gnu/libwayland-server.so.0 (0x00007f5f9defc000)
	libgbm.so.1 => /usr/lib/x86_64-linux-gnu/libgbm.so.1 (0x00007f5f9dcf4000)
	libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007f5f9dadb000)
	librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007f5f9d8d3000)
	libXrandr.so.2 => /usr/lib/x86_64-linux-gnu/libXrandr.so.2 (0x00007f5f9d6c9000)
	libXinerama.so.1 => /usr/lib/x86_64-linux-gnu/libXinerama.so.1 (0x00007f5f9d4c6000)
	libXcursor.so.1 => /usr/lib/x86_64-linux-gnu/libXcursor.so.1 (0x00007f5f9d2bc000)
	libXau.so.6 => /usr/lib/x86_64-linux-gnu/libXau.so.6 (0x00007f5f9d0b8000)
	libXdmcp.so.6 => /usr/lib/x86_64-linux-gnu/libXdmcp.so.6 (0x00007f5f9ceb2000)
	libffi.so.6 => /usr/lib/x86_64-linux-gnu/libffi.so.6 (0x00007f5f9ccaa000)
	libXrender.so.1 => /usr/lib/x86_64-linux-gnu/libXrender.so.1 (0x00007f5f9caa0000)

Any help is appreciated.

opened by playerkk 10

random sample generation

I'm trying to figure out how I can multithread the loading of these houses, since the metadata (JSON) processing in house.py is taking the most amount of time when trying to iterate through a lot of houses. I was trying this code out (apologies for being a bit messy, but you can start looking @ L139 of test-samples.py). When I run this code, though, it results in a segfault as soon as I start trying to render images (L149). Do you have any idea what I could try to fix this issue?

opened by mr-lubo 9
Floor/walls not rendered, camera only rotates in test-env.py
I am using the provided Dockerfile and running test-env.py on house 0a0b9b45a1db29832dd84e80c1347854

Why aren't the walls/floors being rendered properly, but everything else is?

I am running test-env.py and the camera rotates when I press h or l but doesn't move when I use wasd.
opened by mfe7 5
Error while running test-rendering.py
I get an error when I try to run the python tests: python test-rendering.py house.obj

[EGL] Detected 2 devices. Using device 0 error: ERROR::FRAMEBUFFER: Framebuffer is not complete!

I read the common issues, I am not running any other renderer.

I am running House3D inside a docker.
opened by devendrachaplot 5
Even faster approximate initialization

This depends on the other diff, but I tested this with a sample of the SUNCG dataset and it seems to produce okay results. This just uses cv2 morphological operations and numpy to do some more approximate move map computation instead of trying to do fine-grained collision checking using pure python

opened by mr-lubo 5

ImportError: dynamic module does not define module export function (PyInit_objrender)

Hello, I have been building the renderer as instructed in House3D/renderer/README.md. When I tried checking whether the renderer works successfully by running python test-rendering.py (The corresponding house.obj file has already been created), I get the following results.

[email protected]:~/House3D/tests$ export PYTHONPATH=..
[email protected]:~/House3D/tests$ python test-rendering.py /home/kbkim/suncg_data/house/00065ecbdd7300d35ef4328ffe871505/house.obj
Traceback (most recent call last):
  File "test-rendering.py", line 12, in <module>
    from House3D import objrender, create_default_config
  File "/home/kbkim/House3D/House3D/__init__.py", line 6, in <module>
    from .core import Environment, MultiHouseEnv
  File "/home/kbkim/House3D/House3D/core.py", line 17, in <module>
    from .objrender import RenderMode
ImportError: dynamic module does not define module export function (PyInit_objrender)
Error in sys.excepthook:
Traceback (most recent call last):
  File "/usr/lib/python3/dist-packages/apport_python_hook.py", line 63, in apport_excepthook
    from apport.fileutils import likely_packaged, get_recent_crashes
  File "/usr/lib/python3/dist-packages/apport/__init__.py", line 5, in <module>
    from apport.report import Report
  File "/usr/lib/python3/dist-packages/apport/report.py", line 30, in <module>
    import apport.fileutils
  File "/usr/lib/python3/dist-packages/apport/fileutils.py", line 23, in <module>
    from apport.packaging_impl import impl as packaging
  File "/usr/lib/python3/dist-packages/apport/packaging_impl.py", line 23, in <module>
    import apt
  File "/usr/lib/python3/dist-packages/apt/__init__.py", line 23, in <module>
    import apt_pkg
ModuleNotFoundError: No module named 'apt_pkg'

Original exception was:
Traceback (most recent call last):
  File "test-rendering.py", line 12, in <module>
    from House3D import objrender, create_default_config
  File "/home/kbkim/House3D/House3D/__init__.py", line 6, in <module>
    from .core import Environment, MultiHouseEnv
  File "/home/kbkim/House3D/House3D/core.py", line 17, in <module>
    from .objrender import RenderMode
ImportError: dynamic module does not define module export function (PyInit_objrender)

As for the missing module 'apt_pkg', I have not found any other solution than apt-get install python-apt (as described here), which has not changed my error message either.

I have Python 3.6.7, and cv2.__version__ gives '4.0.0'.

The OS, NVidia driver versions are as follows.

[email protected]:~$ lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description:    Ubuntu 16.04.5 LTS
Release:        16.04
Codename:       xenial
[email protected]:~/House3D/tests$ nvidia-smi
Mon Jan 14 16:57:03 2019
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 384.130                Driver Version: 384.130                   |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  TITAN V             On   | 00000000:18:00.0 Off |                  N/A |
| 36%   51C    P8    33W / 250W |      0MiB / 12058MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   1  TITAN V             On   | 00000000:3B:00.0 Off |                  N/A |
| 40%   57C    P8    36W / 250W |      0MiB / 12058MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   2  TITAN V             On   | 00000000:86:00.0 Off |                  N/A |
| 38%   54C    P8    29W / 250W |      0MiB / 12058MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+
|   3  TITAN V             On   | 00000000:AF:00.0 Off |                  N/A |
| 41%   58C    P8    33W / 250W |      0MiB / 12058MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

Running debug-build.sh gives the following output.

[email protected]:~/House3D/renderer$ ./debug-build.sh
PATH:
/home/kbkim/bin:/home/kbkim/.local/bin:/usr/local/cuda-9.0/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin

CPATH:


PKG_CONFIG_PATH:


LIBRARY_PATH:


LD_LIBRARY_PATH:
/usr/local/cuda-9.0/lib64:

PYTHONPATH:
..

ldconfig:
        libEGL_nvidia.so.0 (libc6,x86-64) => /usr/lib/nvidia-384/libEGL_nvidia.so.0
        libEGL_nvidia.so.0 (libc6) => /usr/lib32/nvidia-384/libEGL_nvidia.so.0
        libEGL.so.1 (libc6,x86-64) => /usr/lib/nvidia-384/libEGL.so.1
        libEGL.so.1 (libc6) => /usr/lib32/nvidia-384/libEGL.so.1
        libEGL.so (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so
        libEGL.so (libc6,x86-64) => /usr/lib/nvidia-384/libEGL.so
        libEGL.so (libc6) => /usr/lib32/nvidia-384/libEGL.so
+ pkg-config --cflags --libs glfw3
-I/usr/include/libdrm -lglfw
+ '[' '!' '' ']'
+ pkg-config --cflags --libs libglvnd
-I/usr/local/include
+ pkg-config --cflags --libs egl
-I/usr/include/libdrm -lEGL
+ which find
/usr/bin/find
+ which pkg-config
/usr/bin/pkg-config
+ which python-config
/usr/bin/python-config
+ python-config --includes --ldflags
-I/usr/include/python2.7 -I/usr/include/x86_64-linux-gnu/python2.7
-L/usr/lib/python2.7/config-x86_64-linux-gnu -L/usr/lib -lpython2.7 -lpthread -ldl  -lutil -lm  -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions
+ '[' ']'
+ g++ --version
g++ (Ubuntu 5.4.0-6ubuntu1~16.04.11) 5.4.0 20160609
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

+ '[' -f ../House3D/objrender.so ']'
+ ldd ../House3D/objrender.so
        linux-vdso.so.1 =>  (0x00007ffc1d558000)
        libGL.so.1 => /usr/local/lib/libGL.so.1 (0x00007fa83a6ec000)
        libEGL.so.1 => /usr/lib/nvidia-384/libEGL.so.1 (0x00007fa83a4e7000)
        libX11.so.6 => /usr/lib/x86_64-linux-gnu/libX11.so.6 (0x00007fa83a1ad000)
        libpng12.so.0 => /lib/x86_64-linux-gnu/libpng12.so.0 (0x00007fa839f87000)
        libglfw.so.3 => /usr/lib/x86_64-linux-gnu/libglfw.so.3 (0x00007fa839d71000)
        libjpeg.so.8 => /usr/lib/x86_64-linux-gnu/libjpeg.so.8 (0x00007fa839b18000)
        libpython2.7.so.1.0 => /usr/lib/x86_64-linux-gnu/libpython2.7.so.1.0 (0x00007fa839589000)
        libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fa83936c000)
        libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007fa838fea000)
        libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fa838ce0000)
        libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007fa838aca000)
        libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fa838700000)
        /lib64/ld-linux-x86-64.so.2 (0x000056458ad58000)
        libGLX.so.0 => /usr/local/lib/libGLX.so.0 (0x00007fa8384c3000)
        libGLdispatch.so.0 => /usr/local/lib/libGLdispatch.so.0 (0x00007fa838208000)
        libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007fa838004000)
        libxcb.so.1 => /usr/lib/x86_64-linux-gnu/libxcb.so.1 (0x00007fa837de1000)
        libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007fa837bc7000)
        librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007fa8379bf000)
        libXrandr.so.2 => /usr/lib/x86_64-linux-gnu/libXrandr.so.2 (0x00007fa8377b3000)
        libXinerama.so.1 => /usr/lib/x86_64-linux-gnu/libXinerama.so.1 (0x00007fa8375b0000)
        libXi.so.6 => /usr/lib/x86_64-linux-gnu/libXi.so.6 (0x00007fa8373a0000)
        libXxf86vm.so.1 => /usr/lib/x86_64-linux-gnu/libXxf86vm.so.1 (0x00007fa837199000)
        libXcursor.so.1 => /usr/lib/x86_64-linux-gnu/libXcursor.so.1 (0x00007fa836f8f000)
        libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007fa836d8c000)
        libXau.so.6 => /usr/lib/x86_64-linux-gnu/libXau.so.6 (0x00007fa836b87000)
        libXdmcp.so.6 => /usr/lib/x86_64-linux-gnu/libXdmcp.so.6 (0x00007fa836981000)
        libXext.so.6 => /usr/lib/x86_64-linux-gnu/libXext.so.6 (0x00007fa83676e000)
        libXrender.so.1 => /usr/lib/x86_64-linux-gnu/libXrender.so.1 (0x00007fa836564000)
        libXfixes.so.3 => /usr/lib/x86_64-linux-gnu/libXfixes.so.3 (0x00007fa83635e000)

Thank you in advance.

opened by lionminhu 4

Error: cannot reslove "Assertion "glGetString(GL_VERSION)" FAILED" after trying all possible issue

ubuntu 16.04 with nvidia 1080Ti, 396.44

sudo apt install libglfw3-dev libglm-dev libx11-dev libegl1-mesa-dev libpng-dev libjpeg-dev
cd
git clone https://github.com/NVIDIA/libglvnd && cd libglvnd
./autogen.sh && ./configure --disable-egl
make -j && sudo make install -j

PATH:
/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/home/jiayi/.local/bin

CPATH:


PKG_CONFIG_PATH:


LIBRARY_PATH:


LD_LIBRARY_PATH:


PYTHONPATH:


+ pkg-config --cflags --libs glfw3
-I/usr/include/libdrm -lglfw
+ '[' '!' '' ']'
+ pkg-config --cflags --libs libglvnd
-I/usr/local/include
+ pkg-config --cflags --libs egl
-I/usr/include/libdrm -lEGL
+ which find
/usr/bin/find
+ which pkg-config
/usr/bin/pkg-config
+ which python-config
/usr/bin/python-config
+ python-config --includes --ldflags
-I/usr/include/python2.7 -I/usr/include/x86_64-linux-gnu/python2.7
-L/usr/lib/python2.7/config-x86_64-linux-gnu -L/usr/lib -lpython2.7 -lpthread -ldl  -lutil -lm  -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions
+ '[' ']'
+ g++ --version
g++ (Ubuntu 5.4.0-6ubuntu1~16.04.10) 5.4.0 20160609
Copyright (C) 2015 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

+ '[' -f ../House3D/objrender.so ']'
+ ldd ../House3D/objrender.so
	linux-vdso.so.1 =>  (0x00007ffea73cc000)
	libGL.so.1 => /usr/lib/nvidia-396/libGL.so.1 (0x00007fc093a5e000)
	libEGL.so.1 => /usr/lib/nvidia-396/libEGL.so.1 (0x00007fc093858000)
	libX11.so.6 => /usr/lib/x86_64-linux-gnu/libX11.so.6 (0x00007fc09351e000)
	libpng12.so.0 => /lib/x86_64-linux-gnu/libpng12.so.0 (0x00007fc0932f8000)
	libglfw.so.3 => /usr/lib/x86_64-linux-gnu/libglfw.so.3 (0x00007fc0930e2000)
	libjpeg.so.8 => /usr/lib/x86_64-linux-gnu/libjpeg.so.8 (0x00007fc092e89000)
	libpython2.7.so.1.0 => /usr/lib/x86_64-linux-gnu/libpython2.7.so.1.0 (0x00007fc0928fa000)
	libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007fc0926dd000)
	libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007fc09235b000)
	libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007fc092051000)
	libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007fc091e3b000)
	libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007fc091a71000)
	/lib64/ld-linux-x86-64.so.2 (0x000055d4ef045000)
	libnvidia-tls.so.396.44 => /usr/lib/nvidia-396/tls/libnvidia-tls.so.396.44 (0x00007fc09186c000)
	libnvidia-glcore.so.396.44 => /usr/lib/nvidia-396/libnvidia-glcore.so.396.44 (0x00007fc08fb9d000)
	libXext.so.6 => /usr/lib/x86_64-linux-gnu/libXext.so.6 (0x00007fc08f98b000)
	libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007fc08f786000)
	libGLdispatch.so.0 => /usr/lib/nvidia-396/libGLdispatch.so.0 (0x00007fc08f4b8000)
	libxcb.so.1 => /usr/lib/x86_64-linux-gnu/libxcb.so.1 (0x00007fc08f296000)
	libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007fc08f07b000)
	librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007fc08ee73000)
	libXrandr.so.2 => /usr/lib/x86_64-linux-gnu/libXrandr.so.2 (0x00007fc08ec68000)
	libXinerama.so.1 => /usr/lib/x86_64-linux-gnu/libXinerama.so.1 (0x00007fc08ea64000)
	libXi.so.6 => /usr/lib/x86_64-linux-gnu/libXi.so.6 (0x00007fc08e854000)
	libXxf86vm.so.1 => /usr/lib/x86_64-linux-gnu/libXxf86vm.so.1 (0x00007fc08e64e000)
	libXcursor.so.1 => /usr/lib/x86_64-linux-gnu/libXcursor.so.1 (0x00007fc08e443000)
	libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007fc08e240000)
	libXau.so.6 => /usr/lib/x86_64-linux-gnu/libXau.so.6 (0x00007fc08e03b000)
	libXdmcp.so.6 => /usr/lib/x86_64-linux-gnu/libXdmcp.so.6 (0x00007fc08de35000)
	libXrender.so.1 => /usr/lib/x86_64-linux-gnu/libXrender.so.1 (0x00007fc08dc2b000)
	libXfixes.so.3 => /usr/lib/x86_64-linux-gnu/libXfixes.so.3 (0x00007fc08da24000)

after typing command unset DISPLAY

➜  renderer git:(master) unset DISPLAY
➜  renderer git:(master) ./test-rectangle.bin egl     
[EGL] Detected 8 devices. Using device 0
assertion "glGetString(GL_VERSION)" failed, in printInfo, (gl/glContext.cc:92)
[1]    52092 abort (core dumped)  ./test-rectangle.bin egl
➜  renderer git:(master) ./test-rectangle.bin headless
error: Cannot connect to DISPLAY!
➜  renderer git:(master)

More info:

➜  renderer git:(master) ./objview-offline.bin /data/.share/suncg/house/bd4d249bb93e43e023f7fa2ff30fa0b1/house.obj
[EGL] Detected 8 devices. Using device 0
assertion "glGetString(GL_VERSION)" failed, in printInfo, (gl/glContext.cc:92)
[1]    52610 abort (core dumped)  ./objview-offline.bin

and use ssh -X command:

➜  ~ glxinfo
name of display: localhost:11.0
X Error of failed request:  BadValue (integer parameter out of range for operation)
  Major opcode of failed request:  155 (GLX)
  Minor opcode of failed request:  24 (X_GLXCreateNewContext)
  Value in failed request:  0x0
  Serial number of failed request:  35
  Current serial number in output stream:  36

I also try to install virtualGL as one issue suggested, however it seems unsuccessful in my machine. I'm so confused that I only type the command listed in README.md but failed to build. I have reinstalled all the dependency but no promising things happened. Any help?

opened by Trinkle23897 4

error while running Dockerfile

hi, I've just run the Dockerfile in ubuntu 14.04 system with nvida gpu, and got following error in the terminal:

[dep]test-rectangle.cpp ... Packge gl was not found in the pkg-config serach path. Perhaps you should add the directory containing 'gl.pc' to the PKG_CONFIG_PATH environment variable No package 'gl' found Packge egl was not found in the pkg-config serach path. Perhaps you should add the directory containing 'egl.pc' to the PKG_CONFIG_PATH environment variable No package 'x11' found Packge x11 was not found in the pkg-config serach path. Perhaps you should add the directory containing 'x11.pc' to the PKG_CONFIG_PATH environment variable No package 'x11' found [dep]objvie-offline.cpp ... Packge gl was not found in the pkg-config serach path. Perhaps you should add the directory containing 'gl.pc' to the PKG_CONFIG_PATH environment variable No package 'gl' found Packge egl was not found in the pkg-config serach path. Perhaps you should add the directory containing 'egl.pc' to the PKG_CONFIG_PATH environment variable No package 'x11' found Packge x11 was not found in the pkg-config serach path. Perhaps you should add the directory containing 'x11.pc' to the PKG_CONFIG_PATH environment variable No package 'x11' found ...

I already installed opencv and related libraries, and the 'gl.pc', 'egl.pc', 'x11.pc' these files have been copied to the pkg-config serach path. Still it reports these error. Thanks in advance

opened by wwwqqqqq 4
Target $I$ for the Gated-LSTM baseline

Hello, I have been trying to implement the Gated-LSTM baseline according to the descriptions in the RoomNav paper (link), but I am confused with the some of the notations.

From Section 5.2.2 (for Gated-LSTM):

The symbol $I$ is used to denote the target instruction. This same symbol was used in Section 5.1.2 (for Gated-CNN) to denote the target instruction prior to conversion to an embedding vector $y$ :

So if we were to follow the same notation as in Section 5.1.2, we would have to feed the one-hot vector $I$ (and not the embedding vector) as input to the gated fusion module and the LSTM for the Gated-LSTM.

However, the Figure 2 seems to imply that it is in fact the embedding vector that is fed into the gated fusion and the LSTM:

Could you clarify whether the target $I$ for Gated-LSTM baseline is meant to be the one-hot vector or the embedding vector?

Thank you in advance.

opened by lionminhu 4
meet error: ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061 when execute test-rendering.py
when I execute test-rendering.py, I meet error:error: ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061 1.Nvidia GTX 1080Ti,Ubuntu16.04; 2.I build by docker; 3.When I execute cd /House3D/tests && python3 test-rendering.py $TEST_HOUSE --interactive,Error occur:ERROR::FRAMEBUFFER: Framebuffer is not complete! ErrorCode=36061; And i find error occur when it execute "api = objrender.RenderAPI(w=600, h=450, device=0)"(ln13) 4.after i execute debug-build.sh,result: PATH: /usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin

CPATH:

PKG_CONFIG_PATH:

LIBRARY_PATH:

LD_LIBRARY_PATH: /usr/lib/x86_64-linux-gnu:/usr/lib/i386-linux-gnu:/usr/local/nvidia/lib:/usr/local/nvidia/lib64

PYTHONPATH:

DISPLAY: :0

ldconfig: libEGL_nvidia.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_nvidia.so.0 libEGL_nvidia.so.0 (libc6) => /usr/lib/i386-linux-gnu/libEGL_nvidia.so.0 libEGL_mesa.so.0 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL_mesa.so.0 libEGL_mesa.so.0 (libc6) => /usr/lib/i386-linux-gnu/libEGL_mesa.so.0 libEGL.so.1 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so.1 libEGL.so.1 (libc6) => /usr/lib/i386-linux-gnu/libEGL.so.1 libEGL.so (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libEGL.so libEGL.so (libc6) => /usr/lib/i386-linux-gnu/libEGL.so

pkg-config --cflags --libs glfw3 -lglfw

'[' '!' '' ']'

pkg-config --cflags --libs libglvnd

pkg-config --cflags --libs egl -I/usr/include/libdrm -lEGL

which find /usr/bin/find

which pkg-config /usr/bin/pkg-config

which python3-config /usr/bin/python3-config

python3-config --includes --ldflags -I/usr/include/python3.6m -I/usr/include/python3.6m -L/usr/lib/python3.6/config-3.6m-x86_64-linux-gnu -L/usr/lib -lpython3.6m -lpthread -ldl -lutil -lm -Xlinker -export-dynamic -Wl,-O1 -Wl,-Bsymbolic-functions

'[' ']'

g++ --version g++ (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

'[' -f ../House3D/objrender.so ']'

ldd ../House3D/objrender.so linux-vdso.so.1 (0x00007ffc6c9dd000) libGL.so.1 => /usr/lib/x86_64-linux-gnu/libGL.so.1 (0x00007f852d3f4000) libEGL.so.1 => /usr/lib/x86_64-linux-gnu/libEGL.so.1 (0x00007f852d1e0000) libX11.so.6 => /usr/lib/x86_64-linux-gnu/libX11.so.6 (0x00007f852cea8000) libpng16.so.16 => /usr/lib/x86_64-linux-gnu/libpng16.so.16 (0x00007f852cc76000) libglfw.so.3 => /usr/lib/x86_64-linux-gnu/libglfw.so.3 (0x00007f852ca59000) libjpeg.so.8 => /usr/lib/x86_64-linux-gnu/libjpeg.so.8 (0x00007f852c7f1000) libpython3.6m.so.1.0 => /usr/lib/x86_64-linux-gnu/libpython3.6m.so.1.0 (0x00007f852c13f000) libpthread.so.0 => /lib/x86_64-linux-gnu/libpthread.so.0 (0x00007f852bf20000) libstdc++.so.6 => /usr/lib/x86_64-linux-gnu/libstdc++.so.6 (0x00007f852bb97000) libm.so.6 => /lib/x86_64-linux-gnu/libm.so.6 (0x00007f852b7f9000) libgcc_s.so.1 => /lib/x86_64-linux-gnu/libgcc_s.so.1 (0x00007f852b5e1000) libc.so.6 => /lib/x86_64-linux-gnu/libc.so.6 (0x00007f852b1f0000) /lib64/ld-linux-x86-64.so.2 (0x00007f852d984000) libGLX.so.0 => /usr/lib/x86_64-linux-gnu/libGLX.so.0 (0x00007f852afbf000) libGLdispatch.so.0 => /usr/lib/x86_64-linux-gnu/libGLdispatch.so.0 (0x00007f852ad09000) libdl.so.2 => /lib/x86_64-linux-gnu/libdl.so.2 (0x00007f852ab05000) libxcb.so.1 => /usr/lib/x86_64-linux-gnu/libxcb.so.1 (0x00007f852a8dd000) libz.so.1 => /lib/x86_64-linux-gnu/libz.so.1 (0x00007f852a6c0000) librt.so.1 => /lib/x86_64-linux-gnu/librt.so.1 (0x00007f852a4b8000) libXrandr.so.2 => /usr/lib/x86_64-linux-gnu/libXrandr.so.2 (0x00007f852a2ad000) libXinerama.so.1 => /usr/lib/x86_64-linux-gnu/libXinerama.so.1 (0x00007f852a0aa000) libXxf86vm.so.1 => /usr/lib/x86_64-linux-gnu/libXxf86vm.so.1 (0x00007f8529ea4000) libXcursor.so.1 => /usr/lib/x86_64-linux-gnu/libXcursor.so.1 (0x00007f8529c9a000) libexpat.so.1 => /lib/x86_64-linux-gnu/libexpat.so.1 (0x00007f8529a68000) libutil.so.1 => /lib/x86_64-linux-gnu/libutil.so.1 (0x00007f8529865000) libXau.so.6 => /usr/lib/x86_64-linux-gnu/libXau.so.6 (0x00007f8529661000) libXdmcp.so.6 => /usr/lib/x86_64-linux-gnu/libXdmcp.so.6 (0x00007f852945b000) libXext.so.6 => /usr/lib/x86_64-linux-gnu/libXext.so.6 (0x00007f8529249000) libXrender.so.1 => /usr/lib/x86_64-linux-gnu/libXrender.so.1 (0x00007f852903f000) libXfixes.so.3 => /usr/lib/x86_64-linux-gnu/libXfixes.so.3 (0x00007f8528e39000) libbsd.so.0 => /lib/x86_64-linux-gnu/libbsd.so.0 (0x00007f8528c24000)
opened by gitwld 6
The SUNCG dataset is not available now
As discussed in:

https://github.com/minosworld/minos/issues/159

https://github.com/shurans/SUNCGtoolbox/issues/32

https://github.com/HoME-Platform/home-platform/issues/30

All links are dead for the dataset.
opened by hzxie 7
Cache houses

Hi, How can we go about caching houses? I see there is a reference to a script named cache_houses.py, but I don't see it in the repo. It will be very helpful because currently the MultiHouseEnv takes forever to load with more than 5 houses or so.

Best, Amanjit

opened by amanjitsk 0
How to get and set the fx and fy of the camera from the test-rendering？

Is there any way to get or set the parameter of the camera in test-rendering (python file). And the which kind of device in parser.add_argument('--device', type=int, default=0) can be set?

opened by jiajialu1995 2
Step on multiple environment in parallel

Hi, thanks for open sourcing this code.

I am wondering whether we can load multiple environments and then step on them in parallel? It will be extremely useful to accelerate the data loading process.

thanks!

opened by jwyang 8

Releases(v0.9)

v0.9(Jan 15, 2018)

Source code(tar.gz)
Source code(zip)
all_houses.json(9.52 KB)

Owner

Meta Research

GitHub Repository

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "

5 Jan 08, 2023

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

422 Jan 04, 2023

From this paper "SESNet: A Semantically Enhanced Siamese Network for Remote Sensing Change Detection"

SESNet for remote sensing image change detection It is the implementation of the paper: "SESNet: A Semantically Enhanced Siamese Network for Remote Se

1 May 24, 2022

RDA: Robust Domain Adaptation via Fourier Adversarial Attacking

RDA: Robust Domain Adaptation via Fourier Adversarial Attacking Updates 08/2021: check out our domain adaptation for video segmentation paper Domain A

17 Nov 30, 2022

Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.

Conceptual 12M We introduce the Conceptual 12M (CC12M), a dataset with ~12 million image-text pairs meant to be used for vision-and-language pre-train

226 Dec 07, 2022

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

3.4k Jan 07, 2023

Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21

CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different

120 Jan 04, 2023

NeRD: Neural Reflectance Decomposition from Image Collections

NeRD: Neural Reflectance Decomposition from Image Collections Project Page | Video | Paper | Dataset Implementation for NeRD. A novel method which dec

195 Dec 29, 2022

Bi-level feature alignment for versatile image translation and manipulation (Under submission of TPAMI)

Bi-level feature alignment for versatile image translation and manipulation (Under submission of TPAMI) Preparation Clone the Synchronized-BatchNorm-P

12 Aug 10, 2022

Lightwood is Legos for Machine Learning.

Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu

312 Jan 08, 2023

Code and data for "Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning" (EMNLP 2021).

GD-VCR Code for Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning (EMNLP 2021). Research Questions and Aims: How well can a model perform o

24 Oct 13, 2022

TensorFlow Implementation of "Show, Attend and Tell"

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

902 Nov 29, 2022

PyTorch implementation of Higher Order Recurrent Space-Time Transformer

Higher Order Recurrent Space-Time Transformer (HORST) This is the official PyTorch implementation of Higher Order Recurrent Space-Time Transformer. Th

13 Oct 18, 2022

Distributing reference energies for SMIRNOFF implementations

Warning: This code is currently experimental and under active development. Is it not yet suitable for distribution or use as reference implementation.

1 Dec 07, 2021

The repo of Feedback Networks, CVPR17

Feedback Networks http://feedbacknet.stanford.edu/ Paper: Feedback Networks, CVPR 2017. Amir R. Zamir*,Te-Lin Wu*, Lin Sun, William B. Shen, Bertram E

87 Nov 19, 2022

Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet

Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet, CVPR2021 安全AI挑战者计划第六期：ImageNet无限制对抗攻击决赛第四名（team name: Advers）

51 Dec 01, 2022

Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN

Face Identity Disentanglement via Latent Space Mapping - Implement in pytorch with StyleGAN 2 Description Pytorch implementation of the paper Face Ide

58 Dec 24, 2022

House3D: A Rich and Realistic 3D Environment

Related tags

Overview

House3D: A Rich and Realistic 3D Environment

Yi Wu, Yuxin Wu, Georgia Gkioxari and Yuandong Tian

Existing Research Projects with House3D

A. RoomNav (paper)

B. Embodied QA (project page | EQA paper | NMC paper)

Citation

License

Comments

Releases(v0.9)

v0.9(Jan 15, 2018)

Owner

Meta Research

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

From this paper "SESNet: A Semantically Enhanced Siamese Network for Remote Sensing Change Detection"

RDA: Robust Domain Adaptation via Fourier Adversarial Attacking

Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21

NeRD: Neural Reflectance Decomposition from Image Collections

Bi-level feature alignment for versatile image translation and manipulation (Under submission of TPAMI)

Lightwood is Legos for Machine Learning.

Code and data for "Broaden the Vision: Geo-Diverse Visual Commonsense Reasoning" (EMNLP 2021).

TensorFlow Implementation of "Show, Attend and Tell"

PyTorch implementation of Higher Order Recurrent Space-Time Transformer

Distributing reference energies for SMIRNOFF implementations

The repo of Feedback Networks, CVPR17

Attack classification models with transferability, black-box attack; unrestricted adversarial attacks on imagenet

Non-Official Pytorch implementation of "Face Identity Disentanglement via Latent Space Mapping" https://arxiv.org/abs/2005.07728 Using StyleGAN2 instead of StyleGAN

(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"

Official pytorch implementation of the IrwGAN for unaligned image-to-image translation

pix2pix in tensorflow.js