About dataset

[Iris]

Hi !
I found there are many data version, could you tell me which one was used in your work ?

I use the last one, and preprossed as README:

python collect_indoor3d_data.py
python gen_h5.py         
cd data && python generate_input_list.py`

but seems not work, because when I run sh +x train.sh 5, it shows :

Fail to load modelfile: None
**** EPOCH 000 ****
----
Current batch/total batch num: 0/824
2019-04-29 03:33:14.057889: E tensorflow/core/common_runtime/executor.cc:660] Executor failed to create kernel. Not found: No registered '_CopyFromGpuToHost' OpKernel for CPU devices compatible with node swap_out_gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0 = _CopyFromGpuToHost[T=DT_FLOAT, _class=["loc@gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](sem_fa_layer3/Squeeze/_301)
        .  Registered:  device='GPU'
         [[Node: swap_out_gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0 = _CopyFromGpuToHost[T=DT_FLOAT, _class=["loc@gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](sem_fa_layer3/Squeeze/_301)]]
Traceback (most recent call last):
  File "train.py", line 262, in <module>
    train()
  File "train.py", line 217, in train
    train_one_epoch(sess, ops, train_writer)
  File "train.py", line 249, in train_one_epoch
    feed_dict=feed_dict)
  File "/data/lirong/py2/venv_python2.7/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 900, in run
    run_metadata_ptr)
  File "/data/lirong/py2/venv_python2.7/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1135, in _run
    feed_dict_tensor, options, run_metadata)
  File "/data/lirong/py2/venv_python2.7/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1316, in _do_run
    run_metadata)
  File "/data/lirong/py2/venv_python2.7/local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1335, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: No registered '_CopyFromGpuToHost' OpKernel for CPU devices compatible with node swap_out_gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0 = _CopyFromGpuToHost[T=DT_FLOAT, _class=["loc@gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](sem_fa_layer3/Squeeze/_301)
        .  Registered:  device='GPU'
         [[Node: swap_out_gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0 = _CopyFromGpuToHost[T=DT_FLOAT, _class=["loc@gradients/sem_fa_layer4/ThreeInterpolate_grad/ThreeInterpolateGrad_0"], _device="/job:localhost/replica:0/task:0/device:CPU:0"](sem_fa_layer3/Squeeze/_301)]]
Traceback (most recent call last):
  File "estimate_mean_ins_size.py", line 49, in <module>
    estimate(FLAGS.test_area)
  File "estimate_mean_ins_size.py", line 30, in estimate
    cur_data, cur_group, _, cur_sem = provider.loadDataFile_with_groupseglabel_stanfordindoor(h5_filename)
  File "/data/lirong/ASIS/models/ASIS/provider.py", line 213, in loadDataFile_with_groupseglabel_stanfordindoor
    seg = f['seglabel'][:].astype(np.int32)
  File "h5py/_objects.pyx", line 54, in h5py._objects.with_phil.wrapper
  File "h5py/_objects.pyx", line 55, in h5py._objects.with_phil.wrapper
  File "/data/lirong/py2/venv_python2.7/local/lib/python2.7/site-packages/h5py/_hl/dataset.py", line 573, in __getitem__
    self.id.read(mspace, fspace, arr, mtype, dxpl=self._dxpl)
KeyboardInterrupt

I don't know if this is because the dataset. I use the virtual environment same as PointNet++ and is useful.

Thanks for your help !

[Xinlong Wang]

@iris0329 We use the aligned version. Did u compile the PointNet++ ops successfully? You can check it by running a vanilla PointNet++ on GPU.

[Iris]

Thanks for help.
I could run successfully !
It's because something about data generation.

[longma]

Thanks for help.
I could run successfully !
It's because something about data generation.

have you implemented visualization of segmentation on s3dis dataset?