CountNet | Deep Neural Network for Speaker Count Estimation | Machine Learning library

by faroit Python Version: v2.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | CountNet Summary

CountNet is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Keras applications. CountNet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Deep Neural Network for Speaker Count Estimation

Support

Quality

Security

License

Reuse

Support

CountNet has a low active ecosystem.

It has 106 star(s) with 28 fork(s). There are 10 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 9 have been closed. On average issues are closed in 44 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of CountNet is v2.0

Quality

CountNet has 0 bugs and 0 code smells.

Security

CountNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

CountNet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

CountNet is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

CountNet releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

CountNet saves you 63 person hours of effort in developing the same functionality from scratch.

It has 164 lines of code, 4 functions and 3 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed CountNet and discovered the below as its top functions. This is intended to give you an instant insight into CountNet implemented functionality, and help decide if they suit your requirements.

Calculate the differences between the mean and p
Mean absolute error
Calculate the number of samples from audio
Mean squared error

Get all kandi verified functions for this library.

CountNet Key Features

No Key Features are available at this moment for CountNet.

CountNet Examples and Code Snippets

No Code Snippets are available at this moment for CountNet.

Community Discussions

Trending Discussions on CountNet

Why can't you use a 3D volume input for LSTM?

Not able to fix "PHP Notice: Undefined variable" and "Undefined index" in code

QUESTION

Why can't you use a 3D volume input for LSTM?

Asked 2020-Oct-19 at 19:22

In the paper CountNet: Estimating the Number of Concurrent Speakers Using Supervised Learning I recently read, it specified that the 3D volume output from a CNN layer must be reduced into a 2 dimensional sequence before entering the LSTM layer, why is that? What's wrong with using the 3 dimensional format?

...

ANSWER

Answered 2020-Oct-19 at 09:16

The standard LSTM neural network assumes input of the following size:

Source https://stackoverflow.com/questions/64423545

QUESTION

Not able to fix "PHP Notice: Undefined variable" and "Undefined index" in code

Asked 2019-May-18 at 23:03

I have been running a Web App for quite some time. The app works even after multiple PHP errors but the error log files are constantly taking 1 GB of my space after every few weeks forcing me to manually delete them. The error resides in a faucet.php file

I am not familiar with Php, I have done everything I can to tackle this error and even check the similar questions but none of it prove to be a fixture of my problem.

These are four error messages and keeps repeating throughout the day.

...

ANSWER

Answered 2019-May-18 at 22:51

Use isset to check whether the variable/index of array exist or not.

Source https://stackoverflow.com/questions/56203328

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CountNet

To install the requirements using Anaconda Python, run. You can now run the command line script and process wav files using the pre-trained model CRNN (best peformance).

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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