I just installed your code and ran it succesfully. Here are some comments:

• You should mention that your install script requires us to allow the miniconda install to append to our .bashrc - I didn't allow this and it took me a bit to figure out why the rest of the script wasn't working.
• you are sourcing .bashrc without the ~/ in

  SurfaceNet/installEnv.sh

  Line 16 in 2e93c47

  . .bashrc # to enable the conda command

  
  which just always fails
• the else clause is commented here:
  

  SurfaceNet/installEnv.sh

  Line 28 in 2e93c47

  echo "The '$conda_env_name' conda env exists." # but the env will be visible even thoug the installation was terminated. In this case you should delete this conda env first.else # if the env does not exist.

aside from those, I got everything working pretty smoothly

I installed lasagne 0.1 and theano 0.9 at first, but it doesn't work
ImportError: Could not import Theano. Please make sure you install a recent enough version of Theano.
Then I installed lasagne 0.2.dev1 and theano 1 instead but theano.sandbox.cuda.dnn is discarded in theano 1(like #3 )
import similarityNet File "./nets/similarityNet.py", line 6, in <module> if lasagne.utils.theano.sandbox.cuda.dnn_available(): # when cuDNN available AttributeError: 'module' object has no attribute 'cuda'
@mjiUST could U help me？ thanks

Could you update your source file layer.py?
Because theano.sandbox.cuda.dnn is discarded in theano 1(>theano 0.9).
from theano.sandbox.cuda.dnn import gpu_contiguous, GpuDnnConvDesc, gpu_alloc_empty, GpuDnnConv3dGradW wont work, and if lasagne.utils.theano.sandbox.cuda.dnn_available() in similarityNet.py.
Could you use theano.gpuarray.dnn instead?
I cant replace gpu_contiguous, GpuDnnConvDesc, gpu_alloc_empty, GpuDnnConv3dGradW with classes of theano.gpuarray.dnn by myself.
And I cant backwards to theano 0.9 either, due to the new vision of cudnn does not support old theano and pygpu.
plz help me,thanks

I'm running this code in my Amazon AWS server
Configuration of my system
`==============NVSMI LOG==============

Timestamp : Tue Apr 24 17:43:40 2018
Driver Version : 375.66

Attached GPUs : 1
GPU 0000:00:1E.0
Product Name : Tesla K80
Product Brand : Tesla
CUDA versionnvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2016 NVIDIA Corporation
Built on Tue_Jan_10_13:22:03_CST_2017
Cuda compilation tools, release 8.0, V8.0.61
`

So when I run python main.py
I got this error

attached as log file
log.txt

Thanks for the great released code! I am wondering what the detailed information recorded in the pos file is. Is that an essential matrix or a homography matrix? And how can we generate it by ourselves? Eager for your reply.

After I follow this #4, the enviroment problem seems to be gone.
But evertime python main.py occour Segmentation fault (core dumped), the python interpreter stops on main_reconstruc.py line 73
patches_embedding, inScope_cubes_vs_views = earlyRejection.patch2embedding(
images_list, img_h_cubesCorner, img_w_cubesCorner, patch2embedding_fn, patches_mean_bgr,
N_cubes, N_views, D_embedding, patchSize = params.__imgPatch_hw_size,
batchSize = params.__batchSize_similNet_patch2embedding,
cubeCenter_hw = np.stack([img_h_cubesCenter, img_w_cubesCenter], axis=0)) # (N_cubes, N_views, D_embedding), (N_cubes, N_views).

output like this
start reconstruction ...
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0007.png
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0008.png
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0009.png
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0010.png
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0011.png
loaded img ./inputs/Middlebury/dinoSparseRing/dinoSR0012.png
xyz bounding box of the reconstructed scene: [-0.061897 0.010897], [-0.018874 0.068227], [-0.057845 0.015495]
loaded similarityNet model: ./inputs/SurfaceNet_models/epoch33_acc_tr0.707_val0.791.model
loaded SurfaceNet model: ./inputs/SurfaceNet_models/2D_2_3D-19-0.918_0.951.model
Segmentation fault (core dumped)

It seems like a stack or memery problem. Can you help me? Any advice?
My OS is
Ubuntu 1604 x64
cuda 8.0+ cudnn5.1 and cuda 9.0+cudnn7.1.1
1080Ti

.theanorc
[global]
floatX=float32
device=cuda
optimizer=None

allow_gc=True
gpuarray.preallocate=0.75
gcc.cxxflags=-Wno-narrowing
exception_verbosity=high

[lib]
cnmem=0.75

[nvcc]
nvcc.fastmath=True

[cuda]
root=/usr/local/cuda-8.0

@mjiUST @Rubikplayer

Hi thanks for previous feedback in another thread. After I setup up Cuda8.0/CuDNN 5.1 and theano 0.9, I can run some part of main.py. But there's still some error when executing patch2embedding() function in the early rejection stage.

More specifically:

Traceback (most recent call last):
  File "./main.py", line 27, in <module>
    save_npz_file_path = main_reconstruct.reconstruction(datasetFolder, _model, imgNamePattern, poseNamePattern, outputFolder, N_viewPairs4inference, resol, BB, viewList)
  File "/home/ICT2000/tli/Workspace/SurfaceNet/main_reconstruct.py", line 77, in reconstruction
    cubeCenter_hw = np.stack([img_h_cubesCenter, img_w_cubesCenter], axis=0))    # (N_cubes, N_views, D_embedding), (N_cubes, N_views)
  File "./utils/earlyRejection.py", line 31, in patch2embedding
    patches_embedding[:,:] = patch2embedding_fn(patch_allBlack)[0] # don't use np.repeat (out of memory)
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/compile/function_module.py", line 898, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/gof/link.py", line 325, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/compile/function_module.py", line 884, in __call__
    self.fn() if output_subset is None else\
RuntimeError: error doing operation: CUDNN_STATUS_INTERNAL_ERROR
Apply node that caused the error: GpuDnnConv{algo='small', inplace=False}(GpuContiguous.0, GpuContiguous.0, GpuAllocEmpty{dtype='float32', context_name=None}.0, GpuDnnConvDesc{border_mode=(1, 1), subsample=(1, 1), conv_mode='cross', precision='float32'}.0, Cast{float32}.0, Cast{float32}.0)
Toposort index: 276
Inputs types: [GpuArrayType<None>(float32, (False, False, False, False)), GpuArrayType<None>(float32, (False, False, False, False)), GpuArrayType<None>(float32, (False, False, False, False)), <theano.gof.type.CDataType object at 0x7fbd6848bc90>, Scalar(float32), Scalar(float32)]
Inputs shapes: [(1, 3, 64, 64), (64, 3, 3, 3), (1, 64, 64, 64), 'No shapes', (), ()]
Inputs strides: [(49152, 16384, 256, 4), (108, 36, 12, 4), (1048576, 16384, 256, 4), 'No strides', (), ()]
Inputs values: ['not shown', 'not shown', 'not shown', <capsule object NULL at 0x7fbb43bd10c0>, 1.0, 0.0]
Inputs type_num: [11, 11, 11, '', 11, 11]
Outputs clients: [[HostFromGpu(gpuarray)(GpuDnnConv{algo='small', inplace=False}.0)]]

Detail error log can be seen here:
err_log.txt

I have tried:

• Delete Theano cache theano-cache purge or rm -rf ./.theano
• Adjust CNMeM: (https://devtalk.nvidia.com/default/topic/950158/cnmem-limitations-when-using-cudnn/)
• Remove nvidia cache and reboot: (https://stackoverflow.com/questions/45810356/runtimeerror-cudnn-status-internal-error)

None has worked so far.

Have you seen this type of error before? Or did I set my computer correctly?
I observed you have a params.py to specify all parameters. Some has mentioned this error can result from lack of memory (link), and it seems your code did something for batch processing.

Info of my setting:

• Ubuntu 16.04
• CUDA 8.0 / CuDNN 5.1
• GPU: Nvidia 1080 Ti (11GB memory) --- I also tried on another machine with Titan X, not working
• theano 0.9

My ~/.theanorc:

[global] 
floatX=float32 
device=cuda0
optimizer=None
 
allow_gc=True 
#gpuarray.preallocate=0.95
gcc.cxxflags=-Wno-narrowing
exception_verbosity=high

[lib]
cnmem=0.75

[nvcc]
nvcc.fastmath=True 

[cuda] 
root=/usr/local/cuda-8.0

If you have any suggestions, please let me know! Thanks for your help and support!

Update:

After I tried to remove other versions of CuDNN: (https://groups.google.com/forum/#!topic/theano-users/w4M3Xy0ec60), the error changes to the following.

Traceback (most recent call last):
  File "./main.py", line 27, in <module>
    save_npz_file_path = main_reconstruct.reconstruction(datasetFolder, _model, imgNamePattern, poseNamePattern, outputFolder, N_viewPairs4inference, resol, BB, viewList)
  File "/home/ICT2000/tli/Workspace/SurfaceNet/main_reconstruct.py", line 77, in reconstruction
    cubeCenter_hw = np.stack([img_h_cubesCenter, img_w_cubesCenter], axis=0))    # (N_cubes, N_views, D_embedding), (N_cubes, N_views)
  File "./utils/earlyRejection.py", line 48, in patch2embedding
    _patches_embedding_inScope[_batch] = patch2embedding_fn(_patches_preprocessed[_batch])     # (N_batch, 3/1, patchSize, patchSize) --> (N_batch, D_embedding). similarityNet: patch --> embedding
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/compile/function_module.py", line 898, in __call__
    storage_map=getattr(self.fn, 'storage_map', None))
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/gof/link.py", line 325, in raise_with_op
    reraise(exc_type, exc_value, exc_trace)
  File "/home/ICT2000/tli/.conda/envs/SurfaceNet/lib/python2.7/site-packages/theano/compile/function_module.py", line 884, in __call__
    self.fn() if output_subset is None else\
  File "pygpu/gpuarray.pyx", line 676, in pygpu.gpuarray.pygpu_empty
  File "pygpu/gpuarray.pyx", line 290, in pygpu.gpuarray.array_empty
pygpu.gpuarray.GpuArrayException: cuMemAlloc: CUDA_ERROR_OUT_OF_MEMORY: out of memory
Apply node that caused the error: GpuDnnConv{algo='small', inplace=False}(GpuContiguous.0, GpuContiguous.0, GpuAllocEmpty{dtype='float32', context_name=None}.0, GpuDnnConvDesc{border_mode=(1, 1), subsample=(1, 1), conv_mode='cross', precision='float32'}.0, Cast{float32}.0, Cast{float32}.0)
Toposort index: 276
Inputs types: [GpuArrayType<None>(float32, (False, False, False, False)), GpuArrayType<None>(float32, (False, False, False, False)), GpuArrayType<None>(float32, (False, False, False, False)), <theano.gof.type.CDataType object at 0x7f703a019c90>, Scalar(float32), Scalar(float32)]
Inputs shapes: [(1100, 3, 64, 64), (64, 3, 3, 3), (1100, 64, 64, 64), 'No shapes', (), ()]
Inputs strides: [(49152, 16384, 256, 4), (108, 36, 12, 4), (1048576, 16384, 256, 4), 'No strides', (), ()]
Inputs values: ['not shown', 'not shown', 'not shown', <capsule object NULL at 0x7f6e133930c0>, 1.0, 0.0]
Inputs type_num: [11, 11, 11, '', 11, 11]
Outputs clients: [[HostFromGpu(gpuarray)(GpuDnnConv{algo='small', inplace=False}.0)]]