I bought a machine with Nvidia Geforce GTX 1650ti GPU and now I came to know that it is not listed under the CUDA GPUs.
I want to install TensorFlow on my machine. But I have seen on the web that TF doesn't support 1650ti. Can someone tell me what versions of the TensorFlow, CUDA toolkit, drivers needed to be installed to train my models?
Thanks in advance.
Edit: Installed successfully.
Related
I am trying to run a DNN model using OpenCV on NVIDIA GPUs. Cuda works fine.
I am trying to run models using OpenCL:
network.setPreferableBackend(cv::dnn::DNN_BACKEND_OPENCV);
network.setPreferableTarget(cv::dnn::DNN_TARGET_OPENCL);
I got lower fps than the CPU. The task manager shows no increase in GPU usage.
Does the OpenCV dnn module utilize NVIDIA GPU if I select OpenCL?
I'm using Windows with a GTX 1050.
Currently I'm working with OpenCV in object detecting using yolo model. I found it's quite slow at ~7fps. I tried to install OpenCV with GPU support but it's only run when I execute the Python script in cmd, i mean not in Anaconda.
Is there any possible way to install OpenCV with GPU support?
First off: there is a similar question but it is ten years old. Obviously hardware changes in that time span ;) Is OpenCV 2.0 optimized for AMD processors?.
My intention is to nuke the windoze 10 on an AMD machine with AMD Ryzen 7 R7-3750H cpu and install ubuntu 18.0.4 LTS. Will opencv work -i.e. will it compile and run? What would I expect in terms of performance vs a bit older core i7 ?
I builded OpenCV 3.4 with CUDA, Intel TBB, Intel MKL in VS 2015 like this
When I run traincascade for classifier training, 100% of CPU is used, but the GPU is not used 0%.
Does the OpenCV-traincascade use the functions of the library CUDA for calculations on the GPU?
No
https://devtalk.nvidia.com/default/topic/951477/jetson-tk1/are-tools-like-opencv_traincascade-gpu-accelerated-in-opencv4tegra-/
To train cascade is meant to be used as an offline tool to create a cascade detector, you should try using a powerful desktop system for training, and then use OpenCV4Tegra on Jetson to run the trained classifier on the device.
There is a CUDA accelerated version of the cascade training tool available in the Ubuntu Desktop x64 version of the OpenCV4Tegra package, which can be downloaded here:
http://developer.nvidia.com/embedded/dlc/l4t-24-1-opencv4tegra-ubuntu
Which sums it up more eloquantly than I could.
Also No - answered here
In Summary
The opencv_traincascade functionality is not developed using GPU code, for reasons I do not know. This tool however is meant to be run offline, and then the results from this training used in your actual detection run-time code which can be GPU optimised.
I am trying to run the CUDA GPU Toolkit 7.5 built with OpenCV 3.1.0 .
My graphic card is : Nvidia Quadro FX 5800 . Driver version : 341.92 (Latest available version for the same)
Nvidia classifies my Graphics card in the legacy category with the 1.3 compute capability.
I keep getting the error in the title. and can understand the driver mismatch.
I updated to the latest driver for the graphics card.
My question is what version of the GPU toolkit should i build opencv with ? that would also be compatible with VS 2013 C++ env. I tried building it with CUDA toolkit 6.0 and its not compatible with VS 2013.
Sticky situation any advice would be appreciated.
This was fixed by building OpenCV with 1.3 compute capability. Dont let Cmake choose it automatically. CUDA_ARCH_PTX was set to 1.3 ->(which is the compute capability of my legacy graphics card).