weakalign | End-to-end weakly-supervised semantic alignment
kandi X-RAY | weakalign Summary
kandi X-RAY | weakalign Summary
weakalign is a Python library. weakalign has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However weakalign build file is not available. You can download it from GitHub.
This is the implementation of the paper "End-to-end weakly-supervised semantic alignment" by I. Rocco, R. Arandjelović and J. Sivic. For more information check out the project [website] and the paper on [arXiv].
This is the implementation of the paper "End-to-end weakly-supervised semantic alignment" by I. Rocco, R. Arandjelović and J. Sivic. For more information check out the project [website] and the paper on [arXiv].
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Quality
Security
License
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weakalign has a low active ecosystem.
It has 183 star(s) with 42 fork(s). There are 10 watchers for this library.
It had no major release in the last 6 months.
There are 6 open issues and 8 have been closed. On average issues are closed in 225 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of weakalign is current.
Quality
weakalign has 0 bugs and 169 code smells.
Security
weakalign has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
weakalign code analysis shows 0 unresolved vulnerabilities.
There are 14 security hotspots that need review.
License
weakalign 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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weakalign releases are not available. You will need to build from source code and install.
weakalign 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.
weakalign saves you 1302 person hours of effort in developing the same functionality from scratch.
It has 2923 lines of code, 156 functions and 23 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed weakalign and discovered the below as its top functions. This is intended to give you an instant insight into weakalign implemented functionality, and help decide if they suit your requirements.
- Calculate pascal parts
- Compute the PCK metric
- Compute the precentage of source points
- Calculates the intersection of the intersection between two masks
- Calculate area and target area
- Calculate the localization error
- Computes the image coordinates of a bounding box
- Compute a metric for a given dataset
- Calculate the inlier count
- Download TSSS dataset
- Downloads PFOW and test pairs
- Parse command line arguments
- Calculate loss function
- Warp an image
- Download the Pascal dataset
- Iterate through in_memory and put batches into batches
- Constructs the affine tensorflow tensorflow model
- Compute the MSE loss
- Compute the Fourier transform
- Normalize an image
- Calculate the point distance metric
- Process a single epoch
- Calculate flow metrics for a given batch
- Compute the correlation between two features
- Downloads Caltech -101 dataset
- Compute the FFT of the image
Get all kandi verified functions for this library.
weakalign Key Features
No Key Features are available at this moment for weakalign.
weakalign Examples and Code Snippets
No Code Snippets are available at this moment for weakalign.
Community Discussions
No Community Discussions are available at this moment for weakalign.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install weakalign
You can download it from GitHub.
You can use weakalign 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.
You can use weakalign 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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