keras-coordconv | Keras implementation of CoordConv | Machine Learning library

by titu1994 Python Version: Current License: MIT

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kandi X-RAY | keras-coordconv Summary

keras-coordconv is a Python library typically used in Artificial Intelligence, Machine Learning, Tensorflow, Keras applications. keras-coordconv has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However keras-coordconv build file is not available. You can download it from GitHub.

Keras implementation of CoordConv for all Convolution layers

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keras-coordconv has a low active ecosystem.

It has 139 star(s) with 30 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 12 have been closed. On average issues are closed in 7 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of keras-coordconv is current.

Quality

keras-coordconv has 0 bugs and 2 code smells.

Security

keras-coordconv has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

keras-coordconv code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

keras-coordconv is licensed under the MIT License. This license is Permissive.

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

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keras-coordconv releases are not available. You will need to build from source code and install.

keras-coordconv has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

keras-coordconv saves you 264 person hours of effort in developing the same functionality from scratch.

It has 641 lines of code, 22 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Call the function .
Initialize the coordinate channel .
Compute output shape .
Get the configuration for the coordinate channel .
Builds the model .

Get all kandi verified functions for this library.

keras-coordconv Key Features

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keras-coordconv Examples and Code Snippets

No Code Snippets are available at this moment for keras-coordconv.

Community Discussions

Trending Discussions on keras-coordconv

Keras / TensorFlow: concatenating layer of constants to a convolution

QUESTION

Keras / TensorFlow: concatenating layer of constants to a convolution

Asked 2018-Jul-17 at 21:22

For each convolution activation map, I want to concatenate a layer of constants -- more particularly, I want to concatenate a meshgrid. (This is to reproduce a paper from Uber.)

For example, say I have an activation map of (?, 256, 256, 32); then I want to concatenate a constants layer of shape (?, 256, 256, 1).

This is how I am doing this:

...

ANSWER

Answered 2018-Jul-16 at 09:15

The problem is that tf.reshape can't infer the shape of more than one dimension (i.e. using -1 for more than one dimension results in undefined dimensions ?). Since you want the shapes of xx and yy to be (?, 256, 256, 1), you could reshape these tensors as follows:

Source https://stackoverflow.com/questions/51352685

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

Vulnerabilities

No vulnerabilities reported

Install keras-coordconv

You can download it from GitHub.
You can use keras-coordconv 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.