Could some one tell me what is the equivalent of gfortran -fallow-argument-mismatch in intel ifort?
thank you
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I am trying to use OpenCV with target OpenCL in a Ubuntu 16.04 system with intel UHD 620 graphics. I have installed ocl-icd-opencl-dev for OpenCL but cv::ocl::haveOpenCL() tells me that I do not have OpenCL
clinfo gives me
Number of platforms 0
Then I tried installing beignet as this answer proposes. Still cv::ocl::haveOpenCL() tells me that I do not have OpenCL and now clinfo says
Number of platforms 1
Platform Name Intel Gen OCL Driver
Platform Vendor Intel
Platform Version OpenCL 1.2 beignet 1.1.1
Platform Profile FULL_PROFILE
Platform Extensions cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_spir cl_khr_icd
Platform Extensions function suffix Intel
beignet-opencl-icd: no supported GPU found, this is probably the wrong opencl-icd package for this hardware
Can anybody help?
ocl-icd-opencl-dev are development files for OCL-ICD loader. You'll need that if you want to develop (compile) against libOpenCL. If you don't want to develop, only use OpenCL programs, then you just need ocl-icd-libopencl1.
cv::ocl::haveOpenCL() tells me that I do not have OpenCL
ocl-icd is just a loader; you need an actual implementation. As explained on Khronos:
The OpenCL Installable Client Driver (ICD) is a mechanism to allow OpenCL implementations from multiple vendors to coexist on a system
Then I tried installing beignet
beignet is an implementation, but it's too old for your GPU. You need either their proprietary implementation, or Intel NEO.
Trying to load ssdlite v2 model with intel inference engine on raspberry Pi 3. For this, I need to build opencv-4.0 with Intel Inference API engine. I am unable to build open CV using CMAKE with -DWITH_INF_ENGINE=ON ^
-DENABLE_CXX11=ON flags. Does anyone know how to do it?
First you need install or compile this engine, see you Intel OpenVINO documentation.
Is the Vala/Genie compiler available on the Windows and Mac OS X platforms? I know that it is possible to use GLib and GTK on Windows and Mac OS X, but there are no official downloads of Vala for either platform.
Vala 0.28 is currently available on Mac OS X in just the same way as the rest of the GLib/GTK platform is. Here are the official instructions for setting up a GLib/GTK development environment on Mac OS X. To build the Vala/Genie compiler, run jhbuild build vala after completing those instructions.
I don't know the answer for Windows.
There are no "official" builds of Vala as such. Vala is officially released as source code only. The source is then built by various distributors who package and distribute the builds.
On Linux this is done by distributions like Fedora and Ubuntu. On Mac OS X probably the most relevant is Brew and on Windows MSYS2. For more details on all of these ways see the Installing Vala section of the Vala wiki.
There are several ways of getting Vala compiler to work on Windows. The easiest solution would be installing MSYS2 which always provides fresh version of vala as one of it's packages.
How do I find out what DLLs an executable depends on?
On systems with the GNU development toolchain (gcc &c) I use ldd for that, but what about the clang systems, like, e.g., Mac OS X (which does not have ldd)?
On Mac OSX, you'd use otool -L instead of ldd. This works regardless of the compiler you used. Other operating systems may have yet other tools; e.g. on Windows you'd use Dependency Walker.
llvm-readelf ---needed-libs is the clang analogue of ldd. Here's is the official documentation
~/weechat $ llvm-readelf --needed-libs bin/weechat
NeededLibraries [
libc.so
libcurl.so
libdl.so
libgcrypt.so
libgnutls.so
libgpg-error.so
libiconv.so
libm.so
libncursesw.so.6
]
The Accelerate framework is a Mac-specific framework that provides things like image convolutions and LAPACK, supposedly optimized to be as fast as possible on Macs. My question: Does OpenCV take advantage of this? Specifically, does the function "filter2D" use Accelerate?
It does not use the Accelerate framework, but it looks like it has been speeded up using the CUDA stuff in 2.2
The relevant files in OpenCV2.2 ...
/modules/gpu/include/opencv2/gpu/gpu.hpp
/modules/gpu/src/filtering.cpp
and
modules/imgproc/src/filter.cpp
for the non-gpu stuff
Not a mac expert but AFAIK openCV uses IPP (if installed) TBB (build option) and NVidia-CUDA (build option)
If you use the MacPorts version, you can specify the options
$ port variants opencv
opencv has the variants:
debug: Enable debug binaries
python26: Add Python 2.6 bindings
* conflicts with python27
python27: Add Python 2.7 bindings
* conflicts with python26
tbb: Use Intel TBB
universal: Build for multiple architectures
I have used
sudo port install py26-numpy
sudo port install opencv +python26 +tbb
with success. Concerning the Accelerate.framework specifically, this blog entry says "# Add Accelerate.framework which is used internally from OpenCV library.", but I have no clue as to know if it is the case here.