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Expected outputs from examples #7

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CarlPoirier opened this issue Jul 8, 2019 · 2 comments
Closed

Expected outputs from examples #7

CarlPoirier opened this issue Jul 8, 2019 · 2 comments

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@CarlPoirier
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CarlPoirier commented Jul 8, 2019 •
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Hi,

I am running through the examples for this. I'm just wondering if it works correctly, especially for the mnist example, since the predictions are not accurate at all. I get this:

Real label: 0, predicted: 2, Probability: 1
Real label: 1, predicted: 0, Probability: 0.54904
Real label: 2, predicted: 2, Probability: 1
Real label: 3, predicted: 5, Probability: 0.639081
Real label: 4, predicted: 8, Probability: 0.472427
Real label: 5, predicted: 2, Probability: 1
Real label: 6, predicted: 8, Probability: 0.908674
Real label: 7, predicted: 5, Probability: 0.984732
Real label: 8, predicted: 2, Probability: 0.999436
Real label: 9, predicted: 5, Probability: 0.974823

It could be great to indicate what are the expected outputs for each example.

Thanks,

Carl
@serizba
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serizba commented Nov 13, 2019

Hi,

By just running the MNIST code using the provided model (model.pb) my results are the following:

Real label: 0, predicted: 0, Probability: 1
Real label: 1, predicted: 1, Probability: 0.999979
Real label: 2, predicted: 2, Probability: 1
Real label: 3, predicted: 3, Probability: 0.999999
Real label: 4, predicted: 4, Probability: 0.99907
Real label: 5, predicted: 5, Probability: 0.999991
Real label: 6, predicted: 6, Probability: 0.999366
Real label: 7, predicted: 7, Probability: 0.99999
Real label: 8, predicted: 8, Probability: 1
Real label: 9, predicted: 9, Probability: 0.999997

Maybe you retrained the model using different parameters and you got an unconverged solution.

@subramanya2107
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@serizba @CarlPoirier Am trying to run mnist but having problem in cmake.
CMake Error at CMakeLists.txt:5 (find_package):
By not providing "FindOpenCV.cmake" in CMAKE_MODULE_PATH this project has
asked CMake to find a package configuration file provided by "OpenCV", but
CMake did not find one.

Could not find a package configuration file provided by "OpenCV" with any
of the following names:

OpenCVConfig.cmake
opencv-config.cmake

Add the installation prefix of "OpenCV" to CMAKE_PREFIX_PATH or set
"OpenCV_DIR" to a directory containing one of the above files. If "OpenCV"
provides a separate development package or SDK, be sure it has been
installed.

abertoldi added a commit to kirasystems/cppflow that referenced this issue Jun 18, 2021
@abertoldi
[DEV-14011] Fix memory issue detected by ASan
3df6559 
The ASan report is as follows:

AddressSanitizer:DEADLYSIGNAL
=================================================================
==74==ERROR: AddressSanitizer: SEGV on unknown address 0x6030bf3b722e (pc 0x7fc277c6ae10 bp 0x7ffe22b2c9a0 sp 0x7ffe22b2c158 T0)
==74==The signal is caused by a READ memory access.
    #0 0x7fc277c6ae10  /build/glibc-eX1tMB/glibc-2.31/string/../sysdeps/x86_64/multiarch/memmove-vec-unaligned-erms.S:365
    #1 0x49d947 in __asan_memcpy (/home/docker/kiravision/test/clang-memtest+0x49d947)
    serizba#2 0x50e00a in TF_TString_ResizeUninitialized(TF_TString*, unsigned long) /opt/tensorflow/include/tensorflow/core/platform/ctstring_internal.h:278:7
    serizba#3 0x50ba34 in TF_TString_Copy(TF_TString*, char const*, unsigned long) /opt/tensorflow/include/tensorflow/core/platform/ctstring_internal.h:389:17
    serizba#4 0x50bbac in Model::restore(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) /home/docker/kiravision/cppflow/src/Model.cpp:107:5
    serizba#5 0x4e98e2 in KiraVision::LearnedModel::LearnedModel(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&) /home/docker/kiravision/src/LearnedModel.cpp:12:13
    serizba#6 0x4e28ed in KiraVision::TableDetector::TableDetector(std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> > const&, KiraVision::LogLevel const&) /home/docker/kiravision/src/TableDetector.cpp:13:24
    serizba#7 0x4d058a in main /home/docker/kiravision/test/memtest.cpp:16:31
    serizba#8 0x7fc277bd30b2 in __libc_start_main /build/glibc-eX1tMB/glibc-2.31/csu/../csu/libc-start.c:308:16
    serizba#9 0x425ccd in _start (/home/docker/kiravision/test/clang-memtest+0x425ccd)

AddressSanitizer can not provide additional info.
SUMMARY: AddressSanitizer: SEGV /build/glibc-eX1tMB/glibc-2.31/string/../sysdeps/x86_64/multiarch/memmove-vec-unaligned-erms.S:365
==74==ABORTING

The problem was incorrect initalization of a `TF_TString`. The existing
code initialized it as `new TF_Tstring` (which is not really any kind of
initalization, just memory allocation). `TF_TString`'s have to be
initialized with `TF_TString_Initialize` before they an be used. The
fact that the offending code is using a `unique_ptr` to ensure deletion
of the `TF_TString` makes it all a little clunky.
@bmiftah bmiftah mentioned this issue Mar 2, 2023
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3 participants
@CarlPoirier @subramanya2107 @serizba