Hi,
I am using FaceDetection with MXNet. It is running good with caffe but not with MXNet-HRT.
Procedure i did-

1. followed this link- https://github.com/OAID/MXNet-HRT/blob/master/acl_openailab/installation.md
2. Changed the frame from image to live feed from camera.
3. git status gives me -origin/master, but git status on submodules givre me different versions.

Any suggestion? Is there any specific versions for all needs to be there to work properly?
Thanks.

I follow the instruction of example/ssd and run python demo.py from example/ssd directory and got an error below. My platform is firefly 3399. Is there a reason which ssd example is not working?

[21:15:32] /home/firefly/2TB/src/firefly/mxnetOnACL/dmlc-core/include/dmlc/./logging.h:304: [21:15:32] src/core/symbolic.cc:72: Symbol.ComposeKeyword argument name anchors not found.
Candidate arguments:
[0]cls_prob
[1]loc_pred
[2]anchor

Stack trace returned 7 entries:
[bt] (0) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(_ZN4dmlc15LogMessageFatalD1Ev+0x44) [0x7f7a5b1cb4]
[bt] (1) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(_ZN4nnvm23KeywordArgumentMismatchEPKcRKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaIS8_EERKN4dmlc10array_viewIS8_EE+0x434) [0x7f7b095604]
[bt] (2) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(ZN4nnvm6Symbol7ComposeERKN4dmlc10array_viewIPKS0_EERKSt13unordered_mapINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES4_St4hashISE_ESt8equal_toISE_ESaISt4pairIKSE_S4_EEERSK+0xcc4) [0x7f7b0922cc]
[bt] (3) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(NNSymbolCompose+0x238) [0x7f7b0a1188]
[bt] (4) /usr/lib/aarch64-linux-gnu/libffi.so.6(ffi_call_SYSV+0x64) [0x7f7bfd1e60]
[bt] (5) /usr/lib/aarch64-linux-gnu/libffi.so.6(ffi_call+0xc0) [0x7f7bfd27b8]
[bt] (6) /usr/lib/python2.7/lib-dynload/_ctypes.aarch64-linux-gnu.so(_ctypes_callproc+0x670) [0x7f7bff1b30]

Traceback (most recent call last):
File "demo.py", line 99, in
ctx, args.nms_thresh, args.force_nms)
File "demo.py", line 40, in get_detector
.get_symbol(len(CLASSES), nms_thresh, force_nms)
File "/home/firefly/2TB/src/mxnetOnACL/example/ssd/symbol/symbol_vgg16_ssd_300.py", line 179, in get_symbol
net = get_symbol_train(num_classes)
File "/home/firefly/2TB/src/mxnetOnACL/example/ssd/symbol/symbol_vgg16_ssd_300.py", line 150, in get_symbol_train
variances=(0.1, 0.1, 0.2, 0.2), nms_topk=nms_topk)
File "", line 47, in _contrib_MultiBoxDetection
File "/usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/_ctypes/symbol.py", line 136, in _symbol_creator
s._compose(name=name, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/symbol.py", line 419, in _compose
self.handle, name, num_args, keys, args))
File "/usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/base.py", line 85, in check_call
raise MXNetError(py_str(_LIB.MXGetLastError()))
mxnet.base.MXNetError: [21:15:32] src/core/symbolic.cc:72: Symbol.ComposeKeyword argument name anchors not found.
Candidate arguments:
[0]cls_prob
[1]loc_pred
[2]anchor

Stack trace returned 7 entries:
[bt] (0) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(_ZN4dmlc15LogMessageFatalD1Ev+0x44) [0x7f7a5b1cb4]
[bt] (1) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(_ZN4nnvm23KeywordArgumentMismatchEPKcRKSt6vectorINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEESaIS8_EERKN4dmlc10array_viewIS8_EE+0x434) [0x7f7b095604]
[bt] (2) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(ZN4nnvm6Symbol7ComposeERKN4dmlc10array_viewIPKS0_EERKSt13unordered_mapINSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES4_St4hashISE_ESt8equal_toISE_ESaISt4pairIKSE_S4_EEERSK+0xcc4) [0x7f7b0922cc]
[bt] (3) /usr/local/lib/python2.7/dist-packages/mxnet-0.10.1-py2.7.egg/mxnet/libmxnet.so(NNSymbolCompose+0x238) [0x7f7b0a1188]
[bt] (4) /usr/lib/aarch64-linux-gnu/libffi.so.6(ffi_call_SYSV+0x64) [0x7f7bfd1e60]
[bt] (5) /usr/lib/aarch64-linux-gnu/libffi.so.6(ffi_call+0xc0) [0x7f7bfd27b8]
[bt] (6) /usr/lib/python2.7/lib-dynload/_ctypes.aarch64-linux-gnu.so(_ctypes_callproc+0x670) [0x7f7bff1b30]

Thanks,

I have followed the instruction.
However, it keeps failing during 3.2make mxnet "make" steps.
I have tried to compile computer library again but the library are still not compatible or missing.
Any help would be appreciated. Thanks

Environment info

Operating System: Ubtunu 16.04

Error Message:

/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 当搜索用于 /usr/lib/../lib/libopenblas.so 时跳过不兼容的 -lopenblas
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 当搜索用于 /usr/lib/../lib/libopenblas.a 时跳过不兼容的 -lopenblas
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 当搜索用于 //usr/lib/libopenblas.so 时跳过不兼容的 -lopenblas
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 当搜索用于 //usr/lib/libopenblas.a 时跳过不兼容的 -lopenblas
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 找不到 -lopenblas
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 找不到 -lOpenCL
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 找不到 -lopencv_core
/usr/lib/gcc-cross/aarch64-linux-gnu/5/../../../../aarch64-linux-gnu/bin/ld: 找不到 -lopencv_imgproc
collect2: error: ld returned 1 exit status
Makefile:256: recipe for target 'lib/libmxnet.so' failed
make: *** [lib/libmxnet.so] Error 1

For bugs or installation issues, please provide the following information.
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Environment info

Operating System:

Compiler:

Package used (Python/R/Scala/Julia):

MXNet version:

Or if installed from source:

MXNet commit hash (git rev-parse HEAD):

If you are using python package, please provide

Python version and distribution:

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R sessionInfo():

Error Message:

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What have you tried to solve it?

when i was testin insightface project(a mxnet deep network),i got these errors:
firefly@firefly:~/zzp/insightface/deploy$ python test.py
loading ../models/model-r34-amf/model 0
[02:10:23] /home/firefly/MXNet-HRT/dmlc-core/include/dmlc/./logging.h:304: [02:1 0:23] /home/firefly/MXNet-HRT/nnvm/dmlc-core/include/dmlc/././json.h:838: JSONRe ader: Unknown field attrs, candidates are:
"attr"
"backward_source_id"
"control_deps"
"inputs"
"name"
"op"
"param"

**I guess it's because the mxnet version too low

how can i make the MXNet-HRT to support mxnet of hihger versions?**

Is there benchmark score for VGG or other models?

When trying mxnetOnACL on my ARM64 Linux box, I found that OpenCL was actually not used in the classification demo following the instructions at:

https://github.com/OAID/mxnetOnACL/tree/master/acl_openailab

Did I miss something?