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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:

This question is an extension of my previous question: Fast python algorithm to find all possible partitions from a list of numbers that has subset sums equal to a ratio . I want to divide a list of numbers so that the ratios of subset sums equal to given values. The difference is now I have a long list of 200 numbers so that a enumeration is infeasible. Note that although there are of course same numbers in the list, every number is distinguishable.

I have created and trained one very simple network in pytorch as shown below:

Selecting nested dictionaries and turning them to a DataFrame in Python

From the nested 'biblio' data below, is there a way of sorting this into a data frame with each key as a column? For example, where 'classifications_cpc' is a column header with the codes as the subsequent values?

I have an application that uses Blazor and Docker that can run in multiple modes for multiple customers (loading various configurations and modules). I use the Profile feature in Visual Studio 2019 to change the environment variables, that decide which version of the application to run.

As standard the Docker profile is the active one. When I run the application in this mode, it starts no problem and the development SSL certificate is valid.

I have created some new profiles (and belonging appsettings.*.json files) that I can select here

When I do select one of these profiles they load up fine and the application runs, but for some reason they won't reuse the same development certificate that was working when I am running it in the 'Docker' Profile. How do I fix this?

I have tried the following:

1. In the secrets.json i have tried to add a line like so: "Kestrel:Certificates:#####Staging:Password": "" () is the same number as the Kestrel:Certificates:Development:Password one, that already exists in the file, without any changes to the behavior.
2. From this URL: https://docs.microsoft.com/en-us/dotnet/core/additional-tools/self-signed-certificates-guide I have tried to create a new certificate by doing this: "dotnet dev-certs https -ep $env:USERPROFILE.aspnet\https\aspnetapp.pfx -p crypticpassword" in the terminal (in VS). I switched USERPROFILE to the name of the environment variable, and crypticpassword to a new random guid. It said it already had a valid certificate.

• Do I have to generate a certificate per profile?
• Can I reuse the one that is already working for 'Docker'?
• How is this done?

I am writing a regular expression that should match some graphic files (non-hidden) So I came up with the following expression

I have modified VGG16 in pytorch to insert things like BN and dropout within the feature extractor. By chance I now noticed something strange when I changed the definition of the forward method from: