pathak22 / ccnn Goto Github PK

$ python ./src/train.py
cnn/ccnn/src/ccnn.py:19: RuntimeWarning: to-Python converter for std::vector<int, std::allocator > already registered; second conversion method ignored.
from python.ccnn import *
F0725 15:37:23.709703 4820 db.cpp:18] Check failed: status.ok() Failed to open leveldb /mnt/a/pathak/fcn_mil_cache/VOC2012/images_train_lmdb
IO error: /mnt/a/pathak/fcn_mil_cache/VOC2012/images_train_lmdb/LOCK: No such file or directory
*** Check failure stack trace: ***
@ 0x7f0e98f9e04d google::LogMessage::Fail()
@ 0x7f0e98fa0603 google::LogMessage::SendToLog()
@ 0x7f0e98f9dbdb google::LogMessage::Flush()
@ 0x7f0e98f9f54e google::LogMessageFatal::~LogMessageFatal()
@ 0x7f0e99320e23 caffe::db::LevelDB::Open()
@ 0x7f0e9937dfb6 caffe::DataLayer<>::DataLayerSetUp()
@ 0x7f0e9938e882 caffe::BaseDataLayer<>::LayerSetUp()
@ 0x7f0e9938e919 caffe::BasePrefetchingDataLayer<>::LayerSetUp()
@ 0x7f0e99367e99 caffe::Net<>::Init()
@ 0x7f0e9936a05e caffe::Net<>::Net()
@ 0x7f0e993000a5 caffe::Solver<>::InitTrainNet()
@ 0x7f0e9930138e caffe::Solver<>::Init()
@ 0x7f0e99301556 caffe::Solver<>::Solver()
@ 0x7f0e9992edf0 caffe::GetSolver<>()
@ 0x7f0e998fc7d3 caffe::GetSolverFromString()
@ 0x7f0e999086b8 boost::python::objects::caller_py_function_impl<>::operator()()
@ 0x7f0e987175cd boost::python::objects::function::call()
@ 0x7f0e987177c8 (unknown)
@ 0x7f0e9871f823 boost::python::detail::exception_handler::operator()()
@ 0x7f0e3a8a8d20 boost::python::detail::translate_exception<>::operator()()
@ 0x7f0e3a884f3d boost::_bi::list3<>::operator()<>()
@ 0x7f0e3a871ec7 boost::_bi::bind_t<>::operator()<>()
@ 0x7f0e3a86b268 boost::detail::function::function_obj_invoker2<>::invoke()
@ 0x7f0e9871f5dd boost::python::handle_exception_impl()
@ 0x7f0e98714999 (unknown)
@ 0x7f0e9b4567a3 PyObject_Call
@ 0x7f0e9b4ecb69 PyEval_EvalFrameEx
@ 0x7f0e9b4f24e9 PyEval_EvalCodeEx
@ 0x7f0e9b4f270a PyEval_EvalCode
@ 0x7f0e9b50b9cd run_mod
@ 0x7f0e9b50cb48 PyRun_FileExFlags
@ 0x7f0e9b50dd68 PyRun_SimpleFileExFlags
已放弃 (核心已转储)
请问这个问题什么意思？该怎么解决啊？着急，在线等！！！

Hi,

I am trying to re-generate the numbers reported in your ICCV paper from scratch. Everything works fine when I use the pre-trained models. But when I train the models myself they seem to classify all pixels to the background. The only files I generated myself are LMDBs using the provided code (/extras/generate_lmdb.py).

Can you please also tell your loss value at 35,000 iterations?

Here is the snapshot of last 100 iterations in my case:

I0601 04:28:17.000000 34992 solver.cpp:489] Iteration 34700, lr = 1e-06
I0601 04:28:33.000000 34992 solver.cpp:214] Iteration 34720, loss = 0.0137566
I0601 04:28:33.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0137567 (* 1 = 0.0137567 loss)
I0601 04:28:33.000000 34992 solver.cpp:489] Iteration 34720, lr = 1e-06
I0601 04:28:53.000000 34992 solver.cpp:214] Iteration 34740, loss = 0.0162213
I0601 04:28:53.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0162215 (* 1 = 0.0162215 loss)
I0601 04:28:53.000000 34992 solver.cpp:489] Iteration 34740, lr = 1e-06
I0601 04:29:11.000000 34992 solver.cpp:214] Iteration 34760, loss = 0.0857187
I0601 04:29:11.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0857188 (* 1 = 0.0857188 loss)
I0601 04:29:11.000000 34992 solver.cpp:489] Iteration 34760, lr = 1e-06
I0601 04:29:29.000000 34992 solver.cpp:214] Iteration 34780, loss = 0.365484
I0601 04:29:29.000000 34992 solver.cpp:229] Train net output #0: loss = 0.365484 (* 1 = 0.365484 loss)
I0601 04:29:29.000000 34992 solver.cpp:489] Iteration 34780, lr = 1e-06
I0601 04:29:47.000000 34992 solver.cpp:214] Iteration 34800, loss = 0.427323
I0601 04:29:47.000000 34992 solver.cpp:229] Train net output #0: loss = 0.427323 (* 1 = 0.427323 loss)
I0601 04:29:47.000000 34992 solver.cpp:489] Iteration 34800, lr = 1e-06
I0601 04:30:05.000000 34992 solver.cpp:214] Iteration 34820, loss = 0.272257
I0601 04:30:05.000000 34992 solver.cpp:229] Train net output #0: loss = 0.272258 (* 1 = 0.272258 loss)
I0601 04:30:05.000000 34992 solver.cpp:489] Iteration 34820, lr = 1e-06
I0601 04:30:23.000000 34992 solver.cpp:214] Iteration 34840, loss = 0.0660284
I0601 04:30:23.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0660286 (* 1 = 0.0660286 loss)
I0601 04:30:23.000000 34992 solver.cpp:489] Iteration 34840, lr = 1e-06
I0601 04:30:40.000000 34992 solver.cpp:214] Iteration 34860, loss = 0.696421
I0601 04:30:40.000000 34992 solver.cpp:229] Train net output #0: loss = 0.696421 (* 1 = 0.696421 loss)
I0601 04:30:40.000000 34992 solver.cpp:489] Iteration 34860, lr = 1e-06
I0601 04:30:58.000000 34992 solver.cpp:214] Iteration 34880, loss = 0.096779
I0601 04:30:58.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0967792 (* 1 = 0.0967792 loss)
I0601 04:30:58.000000 34992 solver.cpp:489] Iteration 34880, lr = 1e-06
I0601 04:31:16.000000 34992 solver.cpp:214] Iteration 34900, loss = 0.216992
I0601 04:31:16.000000 34992 solver.cpp:229] Train net output #0: loss = 0.216992 (* 1 = 0.216992 loss)
I0601 04:31:16.000000 34992 solver.cpp:489] Iteration 34900, lr = 1e-06
I0601 04:31:33.000000 34992 solver.cpp:214] Iteration 34920, loss = 0.047195
I0601 04:31:33.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0471952 (* 1 = 0.0471952 loss)
I0601 04:31:33.000000 34992 solver.cpp:489] Iteration 34920, lr = 1e-06
I0601 04:31:51.000000 34992 solver.cpp:214] Iteration 34940, loss = 0.32279
I0601 04:31:51.000000 34992 solver.cpp:229] Train net output #0: loss = 0.32279 (* 1 = 0.32279 loss)
I0601 04:31:51.000000 34992 solver.cpp:489] Iteration 34940, lr = 1e-06
I0601 04:32:08.000000 34992 solver.cpp:214] Iteration 34960, loss = 0.0153671
I0601 04:32:08.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0153672 (* 1 = 0.0153672 loss)
I0601 04:32:08.000000 34992 solver.cpp:489] Iteration 34960, lr = 1e-06
I0601 04:32:26.000000 34992 solver.cpp:214] Iteration 34980, loss = 0.0963567
I0601 04:32:26.000000 34992 solver.cpp:229] Train net output #0: loss = 0.0963568 (* 1 = 0.0963568 loss)
I0601 04:32:26.000000 34992 solver.cpp:489] Iteration 34980, lr = 1e-06
35000 iterations t = 892.211614132

Any help is welcome.

Thanks!

Hi,

I am trying to reproduce your work. During this period, sadly, I failed to load python.caffe in ccnn.py. It seems that this lib cannot be found. Besides, I am confused about how you implement the latent distribution optimisation.

Looking forward to your reply. Thank you~