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Image size of origin is 320*240. Processing time is 30.96 second took. The result of stitching The resul... -
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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Background subtractor example souce code. OpenCV support about 3 types subtraction algorithm. Those are MOG, MOG2, GMG algorithms. Det... -
Created Date : 2009.10. Language : C++ Tool : Visual Studio C++ 2008 Library & Utilized : Point Grey-FlyCapture, Triclops, OpenCV... -
This is data acquisition source code of LMS511(SICK co.) Source code is made by MFC(vs 2008). The sensor is communicated by TCP/IP. ... -
Created Date : 2011.10 Language : C/C++ Tool : Microsoft Visual C++ 2008 Library & Utilized : OpenCV 2.3 Reference : SIFT referenc... -
The MNIST dataset is a dataset of handwritten digits, comprising 60 000 training examples and 10 000 test examples. The dataset can be downl... -
* Introduction - The solution shows panorama image from multi images. The panorama images is processing by real-time stitching algorithm... -
yolo v5 data coordinate format ex) str_v = "32 0.262 0.7878 0.314 0.385" #read image cvmat = cv2.imread(img_path) #get height, w... -
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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ReplyDeleteThis one is better than "More stringent pedestrian detection by Deep learning verification" and "More stringent pedestrian detection by HOG verification". Do you use OpenCV to achieve such result?
ReplyDeleteDetecting pedestrian using Deep learning is recorded high rate false positive, but not sensitive variable pedestrian pose. and processing speed is not good.
DeleteHog is fast, but to detect typical appearance when training data pose.
So, I can not say yet, which way is better..
Thank you.
can you share this source code! Thank you
ReplyDelete