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jetson_nano's Issues

install opencv_3.4.8 on jetson nano

Hi,
I installed the opencv_3.4.8 on jetson nano with jetpack-4.3, I get this error:

patching file /usr/local/cuda/include/cuda_gl_interop.h
Reversed (or previously applied) patch detected! Skipping patch.
1 out of 1 hunk ignored
** Download opencv-3.4.8
** ERROR: opencv-3.4.8 directory already exists

keras_python_api_gen_compat_v2 failed

Hello @jkjung-avt !

After 50 hours running , the installation script for Tensorflow 2.3.0 failed with the following message

ERROR: /home/mluser/src/tensorflow-2.3.0/tensorflow/python/keras/api/BUILD:137:1: Executing genrule //tensorflow/python/keras/api:keras_python_api_gen_compat_v2 failed (Exit 1)
Traceback (most recent call last):
File "/home/mluser/.cache/bazel/_bazel_mluser/1833234d02016516876791857fb771d1/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/python/keras/api/create_tensorflow.python_api_keras_python_api_gen_compat_v2.runfiles/org_tensorflow/tensorflow/python/tools/api/generator/create_python_api.py", line 26, in
from tensorflow.python.tools.api.generator import doc_srcs
File "/home/mluser/.cache/bazel/_bazel_mluser/1833234d02016516876791857fb771d1/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/python/keras/api/create_tensorflow.python_api_keras_python_api_gen_compat_v2.runfiles/org_tensorflow/tensorflow/python/init.py", line 40, in
from tensorflow.python.eager import context
File "/home/mluser/.cache/bazel/_bazel_mluser/1833234d02016516876791857fb771d1/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/python/keras/api/create_tensorflow.python_api_keras_python_api_gen_compat_v2.runfiles/org_tensorflow/tensorflow/python/eager/context.py", line 32, in
from tensorflow.core.framework import function_pb2
File "/home/mluser/.cache/bazel/_bazel_mluser/1833234d02016516876791857fb771d1/execroot/org_tensorflow/bazel-out/host/bin/tensorflow/python/keras/api/create_tensorflow.python_api_keras_python_api_gen_compat_v2.runfiles/org_tensorflow/tensorflow/core/framework/function_pb2.py", line 7, in
from google.protobuf import descriptor as _descriptor
ModuleNotFoundError: No module named 'google.protobuf'
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
ERROR: /home/mluser/src/tensorflow-2.3.0/tensorflow/python/tools/BUILD:226:1 Executing genrule //tensorflow/python/keras/api:keras_python_api_gen_compat_v2 failed (Exit 1)

I deleted previous protobuf installations and installed 3.8.0 before starting the script as in you procedure, now I find

pip3 freeze | grep protobuf
protobuf==3.8.0

I verified also that, for some reason, there was a problem in the pip package so I reinstalled it .
I found this post from you that advice to delete init.py file in the google folder and I did it.
jkjung-avt/tensorrt_demos#130 (comment)
Indeed , at least manually import of google.protobuf now works.

My question is if there a way to recover the script without relaunching the full process from the beginning ?
Thanks a lot for your support !
Cheers

build whl tensorflow 1.12 and not tensorflow-gpu-1.12

Hi
when I build the TensorFlow 1.12 from source with your script, after the building whl finished, created TensorFlow-1.12.2-cp36-cp36m-linux_aarch64.whl, and after the package installed and I run pip3 freeze, the terminal shows me tensorflow==1.12.2 and the before installed package TensorFlow-gpu==1.14.0+nv19.10 is also show me, why? are your scripts build the TensorFlow on CPU mode or GPU?

build tensorflow 1.15

Hi,
As Install Tensorflow-1.15 on jetpack-4.2.2, the trt_version=$(echo /usr/lib/aarch64-linux-gnu/libnvinfer.so.? | cut -d '.' -f 3) in the .sh file, I get version 5, but in that directory, I have both 5,6 version, If I want to use version 6, How do i do?
Is compatible Installing Tensorflow-1.15 with jetpack-4.2.2 and protobuf-3.6.1 and bazel-0.26.1?

Error using the script

Hallo,
I get the following error when running the script.

Selecting previously unselected package libjpeg-turbo8-dev:arm64.
(Reading database ... 270229 files and directories currently installed.)
Preparing to unpack .../libjpeg-turbo8-dev_1.5.2-0ubuntu5.18.04.4_arm64.deb ...
Unpacking libjpeg-turbo8-dev:arm64 (1.5.2-0ubuntu5.18.04.4) ...
dpkg: error processing archive /var/cache/apt/archives/libjpeg-turbo8-dev_1.5.2-0ubuntu5.18.04.4_arm64.deb (--unpack):
trying to overwrite '/usr/include/aarch64-linux-gnu/jconfig.h', which is also in package libjpeg62-turbo-dev:arm64 1:1.5.2-2~bionic1.0
dpkg-deb: error: paste subprocess was killed by signal (Broken pipe)
Errors were encountered while processing:
/var/cache/apt/archives/libjpeg-turbo8-dev_1.5.2-0ubuntu5.18.04.4_arm64.deb
E: Sub-process /usr/bin/dpkg returned an error code (1)

Thanks for help

build tensorflow on jetson nano

I want to build tensorflow-1.14.0 with jetpack4.3, Bazel-0.25.2, protobuf-3.8.0 on jetson nano, I get this error:

ERROR: /home/jnano/.cache/bazel/_bazel_root/11848d91bbe32367362bd23b83211c84/external/local_config_cuda/crosstool/BUILD:24:1: in cc_toolchain_suite rule @local_config_cuda//crosstool:toolchain: cc_toolchain_suite '@local_config_cuda//crosstool:toolchain' does not contain a toolchain for cpu 'aarch64'
ERROR: Analysis of target '//tensorflow/tools/pip_package:build_pip_package' failed; build aborted: Analysis of target '@local_config_cuda//crosstool:toolchain' failed; build aborted
INFO: Elapsed time: 20.502s
INFO: 0 processes.
FAILED: Build did NOT complete successfully (114 packages loaded, 175 targets configured)
currently loading: tensorflow/core/kernels ... (2 packages)

I get the same error using jetpack-4.2.2 for building the TensorFlow-1.12.2, for solving the problem I set to disable for TensorRT configure, correclty build the .whl file:

PYTHON_BIN_PATH=$(which python3)
PYTHON_LIB_PATH=$(python3 -c 'import site; print(site.getsitepackages()[0])')
TF_CUDA_COMPUTE_CAPABILITIES=${cuda_compute}
TF_CUDA_VERSION=10.0
TF_CUDA_CLANG=0
TF_CUDNN_VERSION=7
TF_TENSORRT_VERSION=${trt_version} \ -----> remove this line
CUDA_TOOLKIT_PATH=/usr/local/cuda
CUDNN_INSTALL_PATH=/usr/lib/aarch64-linux-gnu
TENSORRT_INSTALL_PATH=/usr/lib/aarch64-linux-gnu \ ---> remove this line
TF_NEED_IGNITE=0
TF_ENABLE_XLA=0
TF_NEED_OPENCL_SYCL=0
TF_NEED_COMPUTECPP=0
TF_NEED_ROCM=0
TF_NEED_CUDA=1
TF_NEED_TENSORRT=1 \ --- > set to 0
TF_NEED_OPENCL=0
TF_NEED_MPI=0 \

Cannot build OpenCV-3.4.6 in Jetson Nano

I was installing OpenCV-3.4.6 according to instructions provided by you and I encountered this error:

[ 49%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/minmax.cpp.o
[ 49%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/norm.cpp.o
[ 49%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/ocl.cpp.o
[ 49%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/opencl/runtime/opencl_clamdblas.cpp.o
[ 49%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/opencl/runtime/opencl_clamdfft.cpp.o
[ 50%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/opencl/runtime/opencl_core.cpp.o
[ 50%] Building CXX object modules/core/CMakeFiles/opencv_core.dir/src/opengl.cpp.o

In file included from /home/jetson-beta/src/opencv-3.4.6/modules/core/src/opengl.cpp:48:0:
/usr/local/cuda/include/cuda_gl_interop.h:63:2: error: #error Please include the appropriate gl headers before including cuda_gl_interop.h
 #error Please include the appropriate gl headers before including cuda_gl_interop.h
  ^~~~~
In file included from /home/jetson-beta/src/opencv-3.4.6/modules/core/include/opencv2/core/private.cuda.hpp:73:0,
                 from /home/jetson-beta/src/opencv-3.4.6/build/modules/core/precomp.hpp:56:
/home/jetson-beta/src/opencv-3.4.6/modules/core/src/opengl.cpp: In function ‘void cv::cuda::setGlDevice(int)’:
/home/jetson-beta/src/opencv-3.4.6/modules/core/src/opengl.cpp:118:47: warning: ‘cudaError_t cudaGLSetGLDevice(int)’ is deprecated [-Wdeprecated-declarations]
         cudaSafeCall( cudaGLSetGLDevice(device) );
                                               ^
/home/jetson-beta/src/opencv-3.4.6/modules/core/include/opencv2/core/cuda/common.hpp:74:58: note: in definition of macro ‘cudaSafeCall’
     #define cudaSafeCall(expr)  cv::cuda::checkCudaError(expr, __FILE__, __LINE__, CV_Func)
                                                          ^~~~
In file included from /home/jetson-beta/src/opencv-3.4.6/modules/core/src/opengl.cpp:48:0:
/usr/local/cuda/include/cuda_gl_interop.h:305:57: note: declared here
 extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaGLSetGLDevice(int device);
                                                         ^~~~~~~~~~~~~~~~~
modules/core/CMakeFiles/opencv_core.dir/build.make:1344: recipe for target 'modules/core/CMakeFiles/opencv_core.dir/src/opengl.cpp.o' failed
make[2]: *** [modules/core/CMakeFiles/opencv_core.dir/src/opengl.cpp.o] Error 1
make[2]: *** Waiting for unfinished jobs....
CMakeFiles/Makefile2:1755: recipe for target 'modules/core/CMakeFiles/opencv_core.dir/all' failed
make[1]: *** [modules/core/CMakeFiles/opencv_core.dir/all] Error 2
Makefile:162: recipe for target 'all' failed
make: *** [all] Error 2

Only edits I made to the cmake command was removing -D ENABLE_FAST_MATH=ON -D CUDA_FAST_MATH=ON as I wanted precise calculations for OpenCV. How can I resolve this build error?

請問您是否有調整過camera獲取的圖像的亮度

首先非常感謝您的shell

如題

我的camera是CSI的, 也就是直接排線插在板子上

import cv2

def gstreamer_pipeline(
capture_width=1280,
capture_height=720,
display_width=1280,
display_height=720,
framerate=60,
flip_method=0,
):
return (
"nvarguscamerasrc ! "
"video/x-raw(memory:NVMM), "
"width=(int)%d, height=(int)%d, "
"format=(string)NV12, framerate=(fraction)%d/1 ! "
"nvvidconv flip-method=%d ! "
"video/x-raw, width=(int)%d, height=(int)%d, format=(string)BGRx ! "
"videoconvert ! "
"video/x-raw, format=(string)BGR ! appsink"
% (
capture_width,
capture_height,
framerate,
flip_method,
display_width,
display_height,
)
)

cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=0), cv2.CAP_GSTREAMER)
brightness=0.8
cap.set(cv2.CAP_PROP_BRIGHTNESS,brightness)
while(True):
ret, frame = cap.read()
rgb = frame
cv2.imshow('frame', rgb)
key = cv2.waitKey(1)
if key == ord('x'):
break

cap.release

不過確報了以下錯誤

Traceback (most recent call last):
File "brightness.py", line 74, in <module>
show_camera()
File "brightness.py", line 61, in show_camera
cv2.imshow("CSI Camera", img)
cv2.error: /home/nvidia/build_opencv/opencv/modules/highgui/src/window.cpp:331: error: (-215) size.width>0 && size.height>0 in function imshow

明顯拿掉cap.set(cv2.CAP_PROP_BRIGHTNESS,brightness) 這個語句就不會報錯, 攝像頭正常開啟
不曉得您有沒有試過改變獲取的圖像亮度過的經驗可以分享呢 ?

十分感謝你 !

tf2.0, tx2 or xavier and --local_resources

Thanks for this useful contribution,

Just to notice ; That should be nice to add a condition for the --local_resources=x,y,z in the script install_tensorflow-2.0.0.sh according to the target where tf is built

For instance, with the current parameters 2048.0,1.0,1.0 - on a tx2 or xavier, the compilation time can lead to more than 48 hours for the ~21427 targets to build.

However, with --local_resources=3072,6.0,1.0 the compilation time will drop significantly on a tx2 (if nvpmodel=0) and --local_ressources=4096,16,1.0 for xavier.

If this is something interesting for the users I can prepare a PR.

testing out demo 5 YOLOv4

Hi,

I want to thank you for all the tutorials. It has been really helpful for a beginner like myself. I am running into this issue on the jetson Nano at this step on Demo 5

$ python3 yolo_to_onnx.py -m yolov4-416

i got an Illegal instruction (core dumped) error on the terminal. Any idea what may cause this?

Thanks!

patch of tensorflow/opencv

Hi,
What's these patch files? why you use these patch? If I want to insatll tensorflow-15 on jetpack 4.4, Is it compatibile with this version?

Could not find any cuda.h matching version '10.0' in any subdirectory

Hi.
I was trying to build tensorflow-1.15.0 for Xavier NX. But it said "Could not find any cuda.h matching version '10.0' in any subdirectory".
My NX Jetpack verison is 4.3. It only has CUDA 10.2. I noticed that you have built tensorflow-1.15.0 with Jetpack 4.3. So could you please share more information about how to build tensorflow-1.15.0 with Jetpack 4.3?

tensorflow 2.0.0 build error

Hi,
Thanks for sharing your work!

I followed your instruction and tried to install tensorflow 2.0.0 on my jetson nano, however it gave below error after a long time compilation.

tensorflow/python/lib/core/bfloat16.cc:608:60: note:   no known conversion for argument 2 from '<unresolved overloaded function type>' to 'PyUFuncGenericFunction {aka void (*)(char**, const long int*, const long int*, void*)}'
Target //tensorflow/tools/pip_package:build_pip_package failed to build
Use --verbose_failures to see the command lines of failed build steps.
INFO: Elapsed time: 52964.953s, Critical Path: 1102.32s
INFO: 5632 processes: 5632 local.
FAILED: Build did NOT complete successfully

my system setup is:
jetpack 4.3
tensorrt 6.0.1
cuda 10.0.326
python 3.7

Could you please suggest how can fix this issue?

can not import

can not import caffe
I follow caffe ssd installation。But after make i still can not import caffe

Latest Tensor Flow version

Hi,

I am looking to build latest TF supported version with CUDA 10. I am trying to make a base docker image with Ubuntu 20.04 to be used on Jetson nano.

Could you please guide me

not installed numpy on jetpack 4.4 on jetson nano2

Hi Dear,
I a few day spent for installation numpy on jetpack4.4, but I get this error, please guidance me:

sudo pip3 install numpy
WARNING: The directory '/home/jnano/.cache/pip' or its parent directory is not owned or is not writable by the current user. The cache has been disabled. Check the permissions and owner of that directory. If executing pip with sudo, you may want sudo's -H flag.
Collecting numpy
  Downloading numpy-1.18.4.zip (5.4 MB)
     |████████████████████████████████| 5.4 MB 35 kB/s 
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
    Preparing wheel metadata ... error
    ERROR: Command errored out with exit status 1:
     command: /usr/bin/python3 /usr/local/lib/python3.6/dist-packages/pip/_vendor/pep517/_in_process.py prepare_metadata_for_build_wheel /tmp/tmpovsoyp_z
         cwd: /tmp/pip-install-sroqb4bl/numpy
    Complete output (158 lines):
    Processing numpy/random/_bounded_integers.pxd.in
    Processing numpy/random/_mt19937.pyx
    Processing numpy/random/_philox.pyx
    Processing numpy/random/_generator.pyx
    Processing numpy/random/_bounded_integers.pyx.in
    Processing numpy/random/mtrand.pyx
    Processing numpy/random/_sfc64.pyx
    Processing numpy/random/_pcg64.pyx
    Processing numpy/random/_common.pyx
    Processing numpy/random/_bit_generator.pyx
    Cythonizing sources
    blas_opt_info:
    blas_mkl_info:
    customize UnixCCompiler
      libraries mkl_rt not found in ['/usr/local/lib', '/usr/lib', '/usr/lib/aarch64-linux-gnu']
      NOT AVAILABLE
    
    blis_info:
      libraries blis not found in ['/usr/local/lib', '/usr/lib', '/usr/lib/aarch64-linux-gnu']
      NOT AVAILABLE
    
    openblas_info:
    C compiler: aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC
    
    creating /tmp/tmpw7ja6mty/tmp
    creating /tmp/tmpw7ja6mty/tmp/tmpw7ja6mty
    compile options: '-c'
    aarch64-linux-gnu-gcc: /tmp/tmpw7ja6mty/source.c
    aarch64-linux-gnu-gcc -pthread /tmp/tmpw7ja6mty/tmp/tmpw7ja6mty/source.o -lopenblas -o /tmp/tmpw7ja6mty/a.out
      FOUND:
        libraries = ['openblas', 'openblas']
        library_dirs = ['/usr/lib/aarch64-linux-gnu']
        language = c
        define_macros = [('HAVE_CBLAS', None)]
    
      FOUND:
        libraries = ['openblas', 'openblas']
        library_dirs = ['/usr/lib/aarch64-linux-gnu']
        language = c
        define_macros = [('HAVE_CBLAS', None)]
    
    non-existing path in 'numpy/distutils': 'site.cfg'
    lapack_opt_info:
    lapack_mkl_info:
      libraries mkl_rt not found in ['/usr/local/lib', '/usr/lib', '/usr/lib/aarch64-linux-gnu']
      NOT AVAILABLE
    
    openblas_lapack_info:
    C compiler: aarch64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC
    
    creating /tmp/tmpcl5ce_q6/tmp
    creating /tmp/tmpcl5ce_q6/tmp/tmpcl5ce_q6
    compile options: '-c'
    aarch64-linux-gnu-gcc: /tmp/tmpcl5ce_q6/source.c
    aarch64-linux-gnu-gcc -pthread /tmp/tmpcl5ce_q6/tmp/tmpcl5ce_q6/source.o -lopenblas -o /tmp/tmpcl5ce_q6/a.out
      FOUND:
        libraries = ['openblas', 'openblas']
        library_dirs = ['/usr/lib/aarch64-linux-gnu']
        language = c
        define_macros = [('HAVE_CBLAS', None)]
    
      FOUND:
        libraries = ['openblas', 'openblas']
        library_dirs = ['/usr/lib/aarch64-linux-gnu']
        language = c
        define_macros = [('HAVE_CBLAS', None)]
    
    running dist_info
    running build_src
    build_src
    building py_modules sources
    creating build
    creating build/src.linux-aarch64-3.6
    creating build/src.linux-aarch64-3.6/numpy
    creating build/src.linux-aarch64-3.6/numpy/distutils
    building library "npymath" sources
    creating build/src.linux-aarch64-3.6/numpy/core
    creating build/src.linux-aarch64-3.6/numpy/core/src
    creating build/src.linux-aarch64-3.6/numpy/core/src/npymath
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npymath/npy_math_internal.h
      adding 'build/src.linux-aarch64-3.6/numpy/core/src/npymath' to include_dirs.
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npymath/ieee754.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npymath/npy_math_complex.c
    None - nothing done with h_files = ['build/src.linux-aarch64-3.6/numpy/core/src/npymath/npy_math_internal.h']
    building library "npysort" sources
    creating build/src.linux-aarch64-3.6/numpy/core/src/common
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/common/npy_sort.h
      adding 'build/src.linux-aarch64-3.6/numpy/core/src/common' to include_dirs.
    creating build/src.linux-aarch64-3.6/numpy/core/src/npysort
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/quicksort.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/mergesort.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/timsort.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/heapsort.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/radixsort.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/common/npy_partition.h
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/selection.c
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/common/npy_binsearch.h
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/npysort/binsearch.c
    None - nothing done with h_files = ['build/src.linux-aarch64-3.6/numpy/core/src/common/npy_sort.h', 'build/src.linux-aarch64-3.6/numpy/core/src/common/npy_partition.h', 'build/src.linux-aarch64-3.6/numpy/core/src/common/npy_binsearch.h']
    building extension "numpy.core._multiarray_tests" sources
    creating build/src.linux-aarch64-3.6/numpy/core/src/multiarray
    conv_template:> build/src.linux-aarch64-3.6/numpy/core/src/multiarray/_multiarray_tests.c
    building extension "numpy.core._multiarray_umath" sources
    Running from numpy source directory.
    setup.py:461: UserWarning: Unrecognized setuptools command, proceeding with generating Cython sources and expanding templates
      run_build = parse_setuppy_commands()
    /usr/lib/python3.6/distutils/dist.py:261: UserWarning: Unknown distribution option: 'define_macros'
      warnings.warn(msg)
    Traceback (most recent call last):
      File "/usr/local/lib/python3.6/dist-packages/pip/_vendor/pep517/_in_process.py", line 280, in <module>
        main()
      File "/usr/local/lib/python3.6/dist-packages/pip/_vendor/pep517/_in_process.py", line 263, in main
        json_out['return_val'] = hook(**hook_input['kwargs'])
      File "/usr/local/lib/python3.6/dist-packages/pip/_vendor/pep517/_in_process.py", line 133, in prepare_metadata_for_build_wheel
        return hook(metadata_directory, config_settings)
      File "/usr/local/lib/python3.6/dist-packages/setuptools/build_meta.py", line 158, in prepare_metadata_for_build_wheel
        self.run_setup()
      File "/usr/local/lib/python3.6/dist-packages/setuptools/build_meta.py", line 250, in run_setup
        self).run_setup(setup_script=setup_script)
      File "/usr/local/lib/python3.6/dist-packages/setuptools/build_meta.py", line 143, in run_setup
        exec(compile(code, __file__, 'exec'), locals())
      File "setup.py", line 488, in <module>
        setup_package()
      File "setup.py", line 480, in setup_package
        setup(**metadata)
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/core.py", line 171, in setup
        return old_setup(**new_attr)
      File "/usr/local/lib/python3.6/dist-packages/setuptools/__init__.py", line 144, in setup
        return distutils.core.setup(**attrs)
      File "/usr/lib/python3.6/distutils/core.py", line 148, in setup
        dist.run_commands()
      File "/usr/lib/python3.6/distutils/dist.py", line 955, in run_commands
        self.run_command(cmd)
      File "/usr/lib/python3.6/distutils/dist.py", line 974, in run_command
        cmd_obj.run()
      File "/usr/local/lib/python3.6/dist-packages/setuptools/command/dist_info.py", line 31, in run
        egg_info.run()
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/command/egg_info.py", line 26, in run
        self.run_command("build_src")
      File "/usr/lib/python3.6/distutils/cmd.py", line 313, in run_command
        self.distribution.run_command(command)
      File "/usr/lib/python3.6/distutils/dist.py", line 974, in run_command
        cmd_obj.run()
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/command/build_src.py", line 146, in run
        self.build_sources()
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/command/build_src.py", line 163, in build_sources
        self.build_extension_sources(ext)
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/command/build_src.py", line 320, in build_extension_sources
        sources = self.generate_sources(sources, ext)
      File "/tmp/pip-install-sroqb4bl/numpy/numpy/distutils/command/build_src.py", line 380, in generate_sources
        source = func(extension, build_dir)
      File "numpy/core/setup.py", line 430, in generate_config_h
        moredefs, ignored = cocache.check_types(config_cmd, ext, build_dir)
      File "numpy/core/setup.py", line 49, in check_types
        out = check_types(*a, **kw)
      File "numpy/core/setup.py", line 288, in check_types
        "install {0}-dev|{0}-devel.".format(python))
    SystemError: Cannot compile 'Python.h'. Perhaps you need to install python-dev|python-devel.
    ----------------------------------------
ERROR: Command errored out with exit status 1: /usr/bin/python3 /usr/local/lib/python3.6/dist-packages/pip/_vendor/pep517/_in_process.py prepare_metadata_for_build_wheel /tmp/tmpovsoyp_z Check the logs for full command output.

Missing protobuf

File "/usr/local/lib/python3.6/dist-packages/tensorflow_core/core/framework/graph_pb2.py", line 7, in
from google.protobuf import descriptor as _descriptor
ModuleNotFoundError: No module named 'google.protobuf'

Issues during installing TF 1.15

First of all, wonderful blog and repository. You are a life saver!!

The install script couldn't successfully complete the build of TF 1.15. However I tried a different solution.

I changed the below packages in the script with these versions

sudo apt-get install -y libhdf5-serial-dev hdf5-tools
sudo pip3 install -U pip six wheel setuptools mock
sudo pip3 install -U 'numpy<1.19.0'
sudo pip3 install -U h5py==2.10.0
sudo pip3 install pandas
sudo pip3 install future
sudo pip3 install -U keras_applications==1.0.8 --no-deps
sudo pip3 install -U keras_preprocessing==1.1.2 --no-deps

Plus the patch in the code didn't help me either. I tried without applying the patch after checking out TF branch 1.15 from the TF github repository and it worked.

Did you try to install TF2.4 from source with GPU accel on Nano or NX?

I am considering installing TF2.4 from source, and I will leverage your script for 2.3 to get there I think.
Not really an issue but I was wondering if you tried it already?
I need TF2.4 nightly installed from source to get TTS fastspeech with TFlight optim to work on the NX, I think. (I get the regular tf model to work on the jetson but not the tflight one due to some operators missing under my TF2.2 current install.

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