calc | Convolutional Autoencoder for Loop Closure | Machine Learning library

We are programmatically creating PDF using our in house lib (C++) by adding all the required objects so that PDF readers can render them properly. Currently we are enhancing the lib to support digital signatures in PDF. Our users will use USB token or Windows certificates to sign the PDF. On studying raw PDF file with digital signature, we were able to make sense of all the objects except for the contents of Sig type object.

I use this formula:

I'm following JetBrains's tutorial on an Apple Silicon computer. I installed boost with MacPorts (sudo port install boost), the version is 1.71 The build of tests.cpp file fails with the following error:

I have trouble finding easy examples how to write simple UDF's (user defined functions) for LO Calc, that uses arrays as arguments or gives arrays as output e.g. array functions.

I need simple example UDF that takes array and gives single number as output, like count() function.

I need simple example where UDF that is array function, that takes two arrays and produces array that is Cartesian product of two arrays.

It would be nice if to have a comment for every step.

i want to remove the values once user select it from dropdown so that the same value doesn't come on to the next dropdown, but the value which is select disappears on adding the next row or dropdown i mean the placeholder of dropdown goes missing. This is all what i have tried yet and you can find the codesandbox link here

So i was working on an python assignment that had this question: Define a function that accepts a sentence and calculate the number of letters(Upper-Lower separately),words,digits,vowels,consonant and special symbols in it. I wrote the following code for this:

I have a Google Sheet (Excel formulas apply) containing 2000 transactions that are structured like below:

Link to Google Sheet with example calcs here.

I need to calculate the Profit (ie. FIFO Capital Gains) for every sell order and place this amount in the 5th column (as pictured). This can be achieved with either traditional formulas or with a Google App Script. Preferably in Google Sheets.

I'm finding it difficult via formulas to match the sell order with the buy as you proceed down the table as some sell orders are split across multiple buy lines. If anyone could help with a formula or solution to tackle this problem it would be much appreciated. This is an updated question to the original here.

i'm trying to track objects with Optical flow in android after using a Haar Cascade detection like in the code below and i have this error can anyone help me with this

E/cv::error(): OpenCV(3.4.12) Error: Assertion failed ((npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0) in virtual void cv::{anonymous}::SparsePyrLKOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputArray, cv::InputOutputArray, cv::OutputArray, cv::OutputArray), file /build/3_4_pack-android/opencv/modules/video/src/lkpyramid.cpp, line 1259 E/org.opencv.video: video::calcOpticalFlowPyrLK_15() caught cv::Exception: OpenCV(3.4.12) /build/3_4_pack-android/opencv/modules/video/src/lkpyramid.cpp:1259: error: (-215:Assertion failed) (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 in function 'virtual void cv::{anonymous}::SparsePyrLKOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputArray, cv::InputOutputArray, cv::OutputArray, cv::OutputArray)' E/AndroidRuntime: FATAL EXCEPTION: Thread-2 Process: opencv.org, PID: 31380 CvException [org.opencv.core.CvException: cv::Exception: OpenCV(3.4.12) /build/3_4_pack-android/opencv/modules/video/src/lkpyramid.cpp:1259: error: (-215:Assertion failed) (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 in function 'virtual void cv::{anonymous}::SparsePyrLKOpticalFlowImpl::calc(cv::InputArray, cv::InputArray, cv::InputArray, cv::InputOutputArray, cv::OutputArray, cv::OutputArray)' ]

I'm trying to train some ML algorithms on some data that I collected, but I received an error for input variables with inconsistent numbers of samples. I'm not really sure what variables needs to be changed or not. I've posted my code below to give you a better understanding of what I'm trying to accomplish: