tfmatch | TensorFlow implementation of GeoDesc | Computer Vision library

by lzx551402 Python Version: Current License: BSD-3-Clause

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

kandi X-RAY | tfmatch Summary

tfmatch is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch applications. tfmatch 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.

TFMatch provides a code base that tackles learning-based image matching problems, including local feature detectors and local feature descriptors. Research works below are implemented in this project:.

Support

Quality

Security

License

Reuse

Support

tfmatch has a low active ecosystem.

It has 75 star(s) with 15 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 9 open issues and 1 have been closed. On average issues are closed in 5 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tfmatch is current.

Quality

tfmatch has no bugs reported.

Security

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

License

tfmatch is licensed under the BSD-3-Clause License. This license is Permissive.

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

Reuse

tfmatch releases are not available. You will need to build from source code and install.

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

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

Top functions reviewed by kandi - BETA

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

Prepare match sets
Parse a correlation set to a match set
Convert matrix to quaternion
R Evaluate the velocity of a quaternion
Setup the transformer
Extract k - points from score_map
Apply non - edge filter
Compute d2net score
Train the model
Build a summary op
Creates a joint loss
Performs training
Crop the image
Construct a meshgrid
Setup grid points
Interpolate between two points
Calculate l2 pooling
Setup kernel
Setup the convolutions
Average pooling op
Max pooling layer
Solve tensorflow problem
Convolutional convolution layer
Decorate a layer function
Setup network
DataSpec for geodesc

Get all kandi verified functions for this library.

tfmatch Key Features

No Key Features are available at this moment for tfmatch.

tfmatch Examples and Code Snippets

No Code Snippets are available at this moment for tfmatch.

Community Discussions

Trending Discussions on tfmatch

Regex lookahead logical 'OR' - to exclude certain patterns

QUESTION

Regex lookahead logical 'OR' - to exclude certain patterns

Asked 2019-Apr-12 at 02:26

I've seen a lot of examples of password validation that do a logical AND. For example, password must have

AT LEAST one digit (AND)
AT LEAST one character (AND)
length between 6 and 15

This can be written with regex 'positive lookahead' as:

...

ANSWER

Answered 2019-Apr-12 at 02:26

Just like you can use multiple positive lookaheads to check that a string fulfills multiple positive patterns, you can alternate inside a negative lookahead to check that none of the alternated patterns inside the lookahead are matched by the string. For example, for your

AT LEAST one SPACE FOUND (OR)

at least one single-quote found (OR)

at least one double-quote found (OR)

the string "666" number of the beast

You can use

Source https://stackoverflow.com/questions/55643549

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

Vulnerabilities

No vulnerabilities reported

Install tfmatch

You can download it from GitHub.
You can use tfmatch 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

I will have limited access to maintain this project as I am about to graduate. If you encounter any problem, feel free to open an issue or PR, and I may have other labmates to help to review.

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