Image url : https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh_wmpkWpwViqcc9QN3mh2El8XaefZORTzLnP-1A_trSlaeJl7dx_OL8uqz6ntmUdLsShhsEclQb3LMsGIKYTXX2pZAWVQ2tSqCTBUqT196TW7aG_zBp4MALZZy6rqC2GfI4OcINJCdFd0/s2048/example.jpg
6/30/2021
6/28/2021
CUDA_ARCH_BIN Table for gpu type
CUDA_ARCH_BIN Table for gpu type
Jetson Products
GPU | Compute Capability |
---|---|
Jetson AGX Xavier | 7.2 |
Jetson Nano | 5.3 |
Jetson TX2 | 6.2 |
Jetson TX1 | 5.3 |
Tegra X1 | 5.3 |
Tesla Workstation Products
GPU | Compute Capability |
---|---|
Tesla K80 | 3.7 |
Tesla K40 | 3.5 |
Tesla K20 | 3.5 |
Tesla C2075 | 2.0 |
Tesla C2050/C2070 | 2.0 |
Tesla NVIDIA Data Center Products
GPU | Compute Capability |
---|---|
NVIDIA A100 | 8.0 |
NVIDIA T4 | 7.5 |
NVIDIA V100 | 7.0 |
Tesla P100 | 6.0 |
Tesla P40 | 6.1 |
Tesla P4 | 6.1 |
Tesla M60 | 5.2 |
Tesla M40 | 5.2 |
Tesla K80 | 3.7 |
Tesla K40 | 3.5 |
Tesla K20 | 3.5 |
Tesla K10 | 3.0 |
Quadro Desktop Products
GPU | Compute Capability |
---|---|
Quadro RTX 8000 | 7.5 |
Quadro RTX 6000 | 7.5 |
Quadro RTX 5000 | 7.5 |
Quadro RTX 4000 | 7.5 |
Quadro GV100 | 7.0 |
Quadro GP100 | 6.0 |
Quadro P6000 | 6.1 |
Quadro P5000 | 6.1 |
Quadro P4000 | 6.1 |
Quadro P2200 | 6.1 |
Quadro P2000 | 6.1 |
Quadro P1000 | 6.1 |
Quadro P620 | 6.1 |
Quadro P600 | 6.1 |
Quadro P400 | 6.1 |
Quadro M6000 24GB | 5.2 |
Quadro M6000 | 5.2 |
Quadro K6000 | 3.5 |
Quadro M5000 | 5.2 |
Quadro K5200 | 3.5 |
Quadro K5000 | 3.0 |
Quadro M4000 | 5.2 |
Quadro K4200 | 3.0 |
Quadro K4000 | 3.0 |
Quadro M2000 | 5.2 |
Quadro K2200 | 3.0 |
Quadro K2000 | 3.0 |
Quadro K2000D | 3.0 |
Quadro K1200 | 5.0 |
Quadro K620 | 5.0 |
Quadro K600 | 3.0 |
Quadro K420 | 3.0 |
Quadro 410 | 3.0 |
Quadro Plex 7000 | 2.0 |
Quadro Mobile Products
GPU | Compute Capability |
---|---|
RTX 5000 | 7.5 |
RTX 4000 | 7.5 |
RTX 3000 | 7.5 |
T2000 | 7.5 |
T1000 | 7.5 |
P620 | 6.1 |
P520 | 6.1 |
Quadro P5200 | 6.1 |
Quadro P4200 | 6.1 |
Quadro P3200 | 6.1 |
Quadro P5000 | 6.1 |
Quadro P4000 | 6.1 |
Quadro P3000 | 6.1 |
Quadro P2000 | 6.1 |
Quadro P1000 | 6.1 |
Quadro P600 | 6.1 |
Quadro P500 | 6.1 |
Quadro M5500M | 5.2 |
Quadro M2200 | 5.2 |
Quadro M1200 | 5.0 |
Quadro M620 | 5.2 |
Quadro M520 | 5.0 |
Quadro K6000M | 3.0 |
Quadro K5200M | 3.0 |
Quadro K5100M | 3.0 |
Quadro M5000M | 5.0 |
Quadro K500M | 3.0 |
Quadro K4200M | 3.0 |
Quadro K4100M | 3.0 |
Quadro M4000M | 5.0 |
Quadro K3100M | 3.0 |
Quadro M3000M | 5.0 |
Quadro K2200M | 3.0 |
Quadro K2100M | 3.0 |
Quadro M2000M | 5.0 |
Quadro K1100M | 3.0 |
Quadro M1000M | 5.0 |
Quadro K620M | 5.0 |
Quadro K610M | 3.5 |
Quadro M600M | 5.0 |
Quadro K510M | 3.5 |
Quadro M500M | 5.0 |
NVS Desktop Products
GPU | Compute Capability |
---|---|
NVIDIA NVS 810 | 5.0 |
NVIDIA NVS 510 | 3.0 |
NVIDIA NVS 315 | 2.1 |
NVIDIA NVS 310 | 2.1 |
NVS Mobile Products
GeForce and TITAN Products
GeForce Notebook Products
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As you can see in the following video, I created a class that stitching n cameras in real time. https://www.youtube.com/user/feelmare/sear...
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I use MOG2 algorithm to background subtraction. The process is resize to small for more fast processing to blur for avoid noise affectio...
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Created Date : 2009.10. Language : C++ Tool : Visual Studio C++ 2008 Library & Utilized : Point Grey-FlyCapture, Triclops, OpenCV...
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RTSP(Real Time Streaming Protocol) is video streaming, it usually sent from network camera. VideoCapture function in opencv also can get r...
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Created Date : 2011.10 Language : C/C++ Tool : Microsoft Visual C++ 2008 Library & Utilized : OpenCV 2.3 Reference : SIFT referenc...
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OpenCV has AdaBoost algorithm function. And gpu version also is provided. For using detection, we prepare the trained xml file. Although...
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After training SVM, we should test the trained XML data is reliable or not.. The method to extract HOG feature is refer to -> http://fe...
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* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm...
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This is example of SVM learning method. This example is I already have explained in past time. See the this page - > http://feelmare.bl...
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fig 1. Left: set 4 points (Left Top, Right Top, Right Bottom, Left Bottom), right:warped image to (0,0) (300,0), (300,300), (0,300) Fi...