I have been doing object detection with Yolo with the darknet git repository and wanted to start with video, I instaled OpenCV and try to run darknet for videos as:
$ ./darknet detector demo cfg/coco.data cfg/yolov3.cfg yolov3.weights <video file>
but I have the following message:
$ demo needs opencv for webcam images
I changed the second line in the makefile to:
OpenCV=1
but the message continue showing, and in the forums only. I followed a tutorial (https://pjreddie.com/darknet/install/#cuda), but I do not not what re-make the project is and the test at the end shows that it is not compiling with opencv. I tried to remake it with:
remake darknet
but I have the following error with the libraries:
include/darknet.h:11:30: fatal error: cuda_runtime.h: No such file or directory
compilation terminated.
Edit: I think is the instalation of CUDA as the comand nvidia-smi does not anything
Related
I tried to test Tensorflow's vid2depth inference (https://github.com/tensorflow/models/tree/master/research/vid2depth).
I followed the instruction of the README. However, I got the below error:
ValueError: Couldn't find 'checkpoint' file or checkpoints in given directory vid2depth/trained-model/model-119496
I test with tf 0.12, 1.0.0. 1.8 and 1.15.
I used the below command:
python3.6 inference.py --kitti_dir ~/vid2depth/kitti-raw-uncompressed --output_dir ~/vid2depth/inference --kitti_video 2011_09_26/2011_09_26_drive_0009_sync --model_ckpt ~/vid2depth/trained-model/model-119496/
The content of the checkpoint folder I downloaded is:
model-119496.data-00000-of-00001 model-119496.index model-119496.meta
It seems provided files are not in the correct format, but I followed the link of the README.
It seems to be an old checkpoint format (Loading older checkpoint in tensorflow).
Could anyone make vid2depth works?
Thank you.
I'm new in c++, and I want to use a static library of tensorflow lite to load and run a model of tensorflow on a c++ program. But after I built the library and run the program ( with the library.a include inside), there is a problem :
./libtensorflow-lite.a:1:1: error: expected unqualified-id
!<arch>
^
./libtensorflow-lite.a:2:3: error: invalid filename for line marker directive
#1/20 1595980892 0 0 100644 664268 `
^
[....]
If you could give me a clue of how to import this library with no errors it's would be awesome.
PS: I built the library with ./build_lib.sh which is on the git of tensorflow at the address tensorflow/tensorflow/lite/tools/make/build_lib.sh
In order to load and run a TFLite model in C++, use the TFLite C++ Inference API
I am trying to run the tensorflow DeepLab tutorial on the cityscapes dataset. I downloaded the gtFine dataset and cloned into the cityscapesScripts folder, and set up the directories as recommended in the tutorial. When I ran the following line from the tutorial,
sh convert_cityscapes.sh,
I received an error message stating "Failed to find all Cityscapes modules".
I checked the cityscapesScripts documentation and I think I am missing the labels module, which is likely causing the error. Where can I clone or download the missing module(s)?
In the dependencies for sh convert_cityscapes.sh, there's a file with invalid syntax.
You can get it to work on Python3 by commenting out the line
print type(obj).name
from cityscapeScripts/helpers/annotation.py line 238
I am follow instruction to build Android application with Tensorflow engine on Hexagon DSP.
My device is Pixel 1.
libhexagon_controller.so - there is no compilation problem with android_Release mode , but when I trying to build android_Release_aarch6 i have linkage problem :
warning: libadsprpc.so, needed by /Tensorflow_Hexagon/tensorflow-master/tensorflow/contrib/makefile/downloads/hexagon/libs/libhexagon_controller.so, not found (try using -rpath or -rpath-link)
I resolve it with adding -ladsprpc to Makefile in tensorflow/contrib/makefile.
If ladsprpc nedeed for android_Release_aarch64 why in android_Release it's ok ?
2.I follow steps to generate sign test shared library -${QUALCOMM_SDK}/docs/Tools_Signing.html
my problem is with adb push output/testsig-0x<serial number> /system/lib/rfsa/adsp/
I am getting adb: error: failed to copy 'testsig-xxxx.so' to '/system/lib/rfsa/adsp/': remote couldn't create file: Is a directory
What to do?
Thanks.
I am learning transfer learning according to How to Retrain Inception's Final Layer for New Categories however, when I build 'retrain.py' using bazel, the following error ocures:
The error message is:
python configuration error:'PYTHON_BIN_PATH' environment variable is not set and referenced by '//third_party/py/numpy:headers'
I am so sorry, I have done my best to display the error image.unfortunately, I failed.
I use python2.7, anaconda2 and bazel0.6.1, tensorflow1.3.
appreciate for your any reply !