Closed w0lfzk1n closed 8 months ago
V3 depends only on onnxruntime and opencv, both of which should be there on raspberry pi
V3 depends only on onnxruntime and opencv, both of which should be there on raspberry pi
Oh thats nice to hear :D
I now figured out, that my
pip install nudenet
Is installing version 2.0.6.
When I try install nudenet==3.0.7 It gives me the error
No matching distribution found for onnxruntime
On my Raspi: uname -m aarch64 gcc - v
Using built-in specs.
COLLECT_GCC=gcc
COLLECT_LTO_WRAPPER=/usr/lib/gcc/arm-linux-gnueabihf/10/lto-wrapper
Target: arm-linux-gnueabihf
Configured with: ../src/configure -v --with-pkgversion='Raspbian 10.2.1-6+rpi1' --with-bugurl=file:///usr/share/doc/gcc-10/README.Bugs --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --prefix=/usr --with-gcc-major-version-only --program-suffix=-10 --program-prefix=arm-linux-gnueabihf-
--enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --enable-bootstrap --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-libitm --disable-libquadmath --disable-libquadmath-support --enable-plugin --with-system-zlib --enable-libphobos-checking=release --with-target-system-zlib=auto --enable-objc-gc=auto --enable-multiarch --disable-sjlj-exceptions --with-arch=armv6 --with-fpu=vfp --with-float=hard --disable-werror --enable-checking=release --build=arm-linux-gnueabihf --host=arm-linux-gnueabihf --target=arm-linux-gnueabihf
Thread model: posix
Supported LTO compression algorithms: zlib zstd
gcc version 10.2.1 20210110 (Raspbian 10.2.1-6+rpi1)
I am trying to figure it out for a while now, thats why I came here :/
I managed to fix it, finally :) Now I have to get over the headache i got from it.
Hello all :D I am using a raspberry pi 4 and currently I am working on a python projects that uses nudenet. But I cant install 'tensorflow' since it seems like the OS I installed back then is not capable of running the normal 'tensorflow'.
Can anyone do some magic and help me on this? :)
Many thanks in advance <3 -wolf