affnet | Code and weights for local feature affine shape estimation | Machine Learning library

by ducha-aiki Python Version: Current License: MIT

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

kandi X-RAY | affnet Summary

affnet is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. affnet has no vulnerabilities, it has a Permissive License and it has low support. However affnet has 4 bugs and it build file is not available. You can download it from GitHub.

CNN-based affine shape estimator. AffNet model implementation in PyTorch for ECCV2018 paper "Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability".

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Quality

Security

License

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affnet has a low active ecosystem.

It has 197 star(s) with 38 fork(s). There are 16 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 27 have been closed. On average issues are closed in 37 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of affnet is current.

Quality

affnet has 4 bugs (0 blocker, 0 critical, 4 major, 0 minor) and 1185 code smells.

Security

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

affnet code analysis shows 0 unresolved vulnerabilities.

There are 10 security hotspots that need review.

License

affnet 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

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

affnet 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.

affnet saves you 4858 person hours of effort in developing the same functionality from scratch.

It has 10240 lines of code, 684 functions and 47 files.

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

Top functions reviewed by kandi - BETA

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

Convenience function for forward computation
Generate a 3d grid
Convert a scipy data to LAFs
Generate a 2d grid
R Compute the relationship between two LAFs
Resolve the affine transformation of the affine transform
Computes the distance between two vectors
Converts LAFs to h_frames
Convert LAFs to ellipses
Convert a list of LAFs to an ellipsis
Convert ellipse to LAFs
Forward computation
Extract the patches from the pyramid
Compute the SNN between two points
Compute the correlation index of two FFTs
Compute the affine transformation
Forward transformation
Prepends line before writing
Download and save dataset
Calculate the features from low and high to low
Affine an affine transform
Compute the similarity between two LAFs
Calculate L2Net loss
Calculate random sampling
Perform the forward computation
Detect the affine shape

Get all kandi verified functions for this library.

affnet Key Features

No Key Features are available at this moment for affnet.

affnet Examples and Code Snippets

No Code Snippets are available at this moment for affnet.

Community Discussions

Trending Discussions on affnet

pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 0

using replace for a column of a pandas df TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'

QUESTION

pandas._libs.hashtable.PyObjectHashTable.get_item KeyError: 0

Asked 2019-Nov-04 at 20:31

I am trying to map emotions from one dataset to another and drop everything that is bigger than 6 in the current dataset. How should I fix this error?

...

ANSWER

Answered 2017-Dec-02 at 04:32

I think this error comes from your [i] notation, which is trying to look for the DataFrame index value of 0, which doesn't exist. Try replacing every instance of [i] with .iloc[i].

Also, you should be able to replace the for loop with much more compact, readable, and less error-prone code, especially since you define emotion_map but use it only for output. Try changing the mapping from strings to integers with emotion_map = { 0:6, 1:3, 2:4, 3:5, 4:2, 5:1, 6:0}, then move it to just under filtered_csv = ..., and replace that for loop with

Source https://stackoverflow.com/questions/47603430

QUESTION

using replace for a column of a pandas df TypeError: Cannot compare types 'ndarray(dtype=int64)' and 'str'

Asked 2017-Dec-03 at 18:30

How should I fix this?

...

ANSWER

Answered 2017-Dec-03 at 18:30

Changing the emotion_map to the following fixed the problem:

Source https://stackoverflow.com/questions/47621671

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

Vulnerabilities

No vulnerabilities reported

Install affnet

You can download it from GitHub.
You can use affnet 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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