I need to check if my autocorrelation result is single or double dip before visualizing it on the figure for reference, I add ACF different figure
enter image description here
enter image description here
Related
Win 11 Pro
PCL 1.12.1
Visual Studio
I want to segment a plane within point cloud using SACsegmentation module and get some unexpected result. Though I solve this problem then, I want to know the reason causing the problem. I want to segment the ground(as blue line set showed), but the code returns the gross one as showed with red lines.
enter image description here
here is the code and pcd file.
https://github.com/PointCloudLibrary/pcl/files/8101342/compress.zip
And after sampling down the point cloud with UniformSample module, it generates the right result. Is it possible that the size of point cloud has some influence
I'm trying to OCR an image in order to read the text on it. Original image is of 300 dpi.But all the ROI parts that are used as input parameters for Tesseract call are 96 dpi. I want to find out when is the quality drop happens. It will be possible if there is a way to calculate the DPI value of each vectors that are passed to Tesseract. Tesseract requires minimum 300 DPI for OCR.
Any idea?
I need something like a class or function or whatever that can take a wav file as an input an give me the vloums value.
if something like this is not Exist, how should I get those values ?
is there any way at all ?
I got the frequencies, I want the Volume.
by the way Im coding in C++.
Thank u for ur answers.
explanation: by volume I mean sound intensity and amplitude.
Volume is related to a measurable quantity : Root Mean Square (RMS). Once you gain access to the audio curve RMS can be calculated for a chosen audio buffer size (entire clip or some portion) Conceptually, you simply walk across a set of samples (each entry of a buffer) where for example the audio curve values may vary from -1 to +1 and you square each value then add to a running total then take the square root of this total. RMS is just the average value of the source values. Short of rolling your own algorithm checkout implementations : ReplayGain
Considering http://soundfile.sapp.org/doc/WaveFormat/ I dont think volume information can be retrieved from the wav file itself. Also, generally, "volume" is subject to the hardware playing the wav file and not the wav file itself if im not mistaken.
I have an image. I resized it i obtain another with a size greater than the first .
resize(roi,zoom,Size(2274,70),(0.0),(0.0),3);
i also test all the method of interpplation but it don't give a good result.
CV_INTER_NN (default)
CV_INTER_LINEAR
CV_INTER_CUBIC
CV_INTER_AREA
The image contain text when i zoomed it it becomes so fuzzy and i can not recognize the text.
I ask for an algorithm or method to make the image more clear
Thanks for the help
It might be an easy question but i am bit confuse so hope some one guide me properly.
i am using face recognition library of openCV libfacerec , it gives good result but i need to estimate the percentage of similarity. If i use unknown image as an input then still it predict as if the person exist in the system on the basis of last distance value
if(dist < minDist) {
minDist = dist;
minClass = _labels[sampleIdx];
}
I need to define some threshold and then validate/invalidate the user picture based on that threshold against some percentage or distance value, does any one know how to do that using libfacerec library because in this library there is no public variable to see distance or percentage value? Otherwise do i need to code inside the library for it because as far as i understand it does not contain this feature???
Please make sure you are working on the latest revision! The latest revision of libfacerec allows you to get a predicition AND a confidence value for the prediction. You can see the signature of the methods here:
https://github.com/bytefish/libfacerec/blob/master/include/facerec.hpp
It is shown in the demo application I ship with the library, please see:
https://github.com/bytefish/libfacerec/blob/master/samples/facerec_demo.cpp
It's as simple as calling:
FaceRecognizer::predict(InputArray src, int &label, double &confidence);
on a computed model. So in your application you would simply write:
Mat testSample; // of course this is set somewhere in your application
int predictedLabel = -1;
double confidence = 0.0;
model.predict(testSample, predictedLabel, confidence);
Then you have the predicted label in predictedLabel AND the confidence value for this prediction in confidence.
Second, and this probably fits your question even more, you now have the possibility to set a threshold, below which an input image is regarded as unknown. You can either set the threshold in the constructor of a model or with a setter/getter method:
https://github.com/bytefish/libfacerec/blob/master/include/facerec.hpp (see createEigenFaceRecognizer, createFisherFaceRecognizer, createLBPHFaceRecognizer)
It is also shown in the demo application I ship with the library:
https://github.com/bytefish/libfacerec/blob/master/samples/facerec_demo.cpp