focal-loss | TensorFlow implementation of focal loss | Machine Learning library

by artemmavrin Python Version: 0.0.7 License: Apache-2.0

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | focal-loss Summary

focal-loss is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. focal-loss has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install focal-loss' or download it from GitHub, PyPI.

TensorFlow implementation of focal loss

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Quality

Security

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Support

focal-loss has a low active ecosystem.

It has 71 star(s) with 20 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 5 open issues and 4 have been closed. On average issues are closed in 0 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of focal-loss is 0.0.7

Quality

focal-loss has 0 bugs and 0 code smells.

Security

focal-loss has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

focal-loss code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

focal-loss is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

focal-loss releases are available to install and integrate.

Deployable package is available in PyPI.

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

focal-loss saves you 413 person hours of effort in developing the same functionality from scratch.

It has 1013 lines of code, 57 functions and 13 files.

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

Top functions reviewed by kandi - BETA

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

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Get all kandi verified functions for this library.

focal-loss Key Features

No Key Features are available at this moment for focal-loss.

focal-loss Examples and Code Snippets

Calculate the loss of the loss function .

python

Lines of Code : 26

License : Permissive (MIT License)

Copy

def _neg_loss(pred, gt):
  ''' Modified focal loss. Exactly the same as CornerNet.
      Runs faster and costs a little bit more memory
    Arguments:
      pred (batch x c x h x w)
      gt_regr (batch x c x h x w)
  '''
  pos_inds = gt.eq(1).float(

Compute negative loss .

python

Lines of Code : 23

License : Permissive (MIT License)

Copy

def _slow_neg_loss(pred, gt):
  '''focal loss from CornerNet'''
  pos_inds = gt.eq(1)
  neg_inds = gt.lt(1)

  neg_weights = torch.pow(1 - gt[neg_inds], 4)

  loss = 0
  pos_pred = pred[pos_inds]
  neg_pred = pred[neg_inds]

  pos_loss = torch.log(po

Community Discussions

Trending Discussions on focal-loss

Docker: Cannot install specific pip packages

QUESTION

Docker: Cannot install specific pip packages

Asked 2021-Oct-12 at 10:16

I want to install specific packages in a docker container. For most of them, the pip installation works fine. However, it seems like some of the versions of the packages cannot be found.

Here's the requirements.txt file from which I'm installing the packages. It was obtained from pip freeze done in PyCharm from Windows.

Currently, I am trying to install them in Docker working on Ubuntu 20.04.

...

ANSWER

Answered 2021-Oct-12 at 09:25

Try to use some other version of ipython.

Replace the python version in your requirements.txt with:

ipython==7.24.1

However, it doesn't have anything to do with docker configuration i.e. --network=host

Source https://stackoverflow.com/questions/69537812

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

Vulnerabilities

No vulnerabilities reported

Install focal-loss

You can install using 'pip install focal-loss' or download it from GitHub, PyPI.
You can use focal-loss like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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