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a yolo windows version(for object detection)
This project forked from frischzenger/yolo-windows
a yolo windows version(for object detection)
when initialization with 1 GB model yolo.weights & yolo.cfg
it shows as follows:
Cannot load image "data/labels/aeroplane.png"
STB Reason: can't fopen
hello guys,
I know the GPU is very very good at YOLO, but.... I want to know how compiler it without GPU. When I delete GPU in precompiler, it will show a lot of error such as "identifier BLOCK is undefined" and "check_error" is undefined and so on.
Hi, I compiled YOLO on windows and it works well. I am using it for object detection using webcam in real-time.
But, the memory usage by Darknet (YOLO) in Windows slowly keeps on increasing and about after 10 minutes my computer runs out of memory (16 GB RAM). I was wondering if you faced similar issue.
I'm sorry, I'm relatively new to Visual Studio and am unsure of what steps I should take to compile. Is there a step by step guide? If not, currently I have CUDA 6.5 x64 installed (as well as 7.5) and OpenCV 2.4.9, and I'm trying to load the yolo-windows-master\build\darknet\darknet.sln with VS 2013, but to no luck.
C:\Users(username)\Downloads\yolo-windows-master (vs2013, Cuda 6.5, Git AlexeyAB)\yolo-windows-master\build\darknet\darknet\darknet.vcxproj : error : Unable to read the project file "darknet.vcxproj".
C:\Users(username)\Downloads\yolo-windows-master (vs2013, Cuda 6.5, Git AlexeyAB)\yolo-windows-master\build\darknet\darknet\darknet.vcxproj(55,5): The imported project "C:\Program Files (x86)\MSBuild\Microsoft.Cpp\v4.0\V120\BuildCustomizations\CUDA 6.5.props" was not found. Confirm that the path in the declaration is correct, and that the file exists on disk.
Any help is much appreciated. Thank you for your time.
EDIT: I wanted to add that I've installed YOLO on Ubuntu, so I have a (very vague) idea of how it should work. Main problem with that installation is, I could get my GPU to function within Virtual Box, and because I need web cam real-time detection in my work, I'm trying to install YOLO on windows instead.
I noticed that a lot of classes has changed ?
the most important changed that the code now dosen't support CUDNN,
that's why the training and testing is slow?
Hello
I'm using yolo_cpp_dll_no_gpu.dll in a secondary c++ project. If I have one thread using this Dll every thing is OK, but how can I use darknet functions in multiple threads?
I'm using c++ and not much familiar with C.
I tried to make an Interface c++ object, in which I can use the dll in multiple threads but, only with mutexes and lockes, but of course the performance will be compromised.
Thanks.
How can I select a specific region of image (manually) to perform all the operations on that region and ignore the rest of the image?
Using CUDA 8.0 and Visual Studio 2015, OpenCV 3.3.0:
Anyone else having this error when compiling?
cannot open source file 'opencv2/highgui/highgui_c.h'
cannot open source file 'opencv2/imgproc/imgproc_c.h'
I've set the additional directories in the project settings and the linker.
when i compile the darknet.it comes out many errors such as
错误 114 error : this declaration may not have extern "C" linkage C:\Program Files (x86)\Microsoft Visual Studio 12.0\VC\include\limits 78 1 darknet2
in limits iosfwd and type_traits
and something wrong in avgpool_layer
I trained new data using "train_yolo" method,
I changed the 'CLASSNUM' in yolo.c and 'classes' in .cfg file
Then changed output in .cfg in [connected] based on this equation (5 * 2 + C) * S * S
after training 600 batches I tested the "yolo_600.weight" file and It didn't detect anything
I used same .cfg file of training for testing..
how many batches I should train until I start get any result?
is there any another steps I should made?
I even put "-thresh 0" and didn't get any box??
there is an article said that I should change CLS_NUM in yolo_kernels.cu as well .. but I didn't see this parameter?
Thank you for your project. It runs good on Windows. I’m working on ssd (Single Shot MultiBox Detector)now. Accuracy rate of ssd is as same as that of faster Rcnn while its speed is as quick as yolo’s. But some problems occur when migrating it to Windows(boost lib problems ). Have you thought about migrating ssd to Window?
This is home page of the ssd project: https://github.com/weiliu89/caffe/tree/ssd
System VOC2007 mAP FPS (Titan X)
Faster R-CNN (VGG16) 73.2 7 7
YOLO 63.4 45
SSD300 (VGG16) 72.1 58
SSD500 (VGG16) 75.1 23
I have some trouble with yolo2_light,
in README.md, it says
To compile for CPU just do make
on Linux
when I do that it turns out
find . -name "*.sh" -exec chmod +x {} \;
gcc -Wall -Wfatal-errors -Ofast obj/main.o obj/additionally.o obj/box.o obj/yolov2_forward_network.o -o bin/darknet -lm -pthread
obj/main.o: In function `test_detector_cpu':
main.c:(.text+0x4e0): undefined reference to `network_predict_quantized'
collect2: error: ld returned 1 exit status
make: *** [bin/darknet] Error 1
I wonder if I should do sth. to Makefile or there're any other solutions?
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