geo_prior | Geographical Priors for Fine-Grained Image Classification

by macaodha Python Version: Current License: No License

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

kandi X-RAY | geo_prior Summary

geo_prior is a Python library. geo_prior has no bugs, it has no vulnerabilities and it has low support. However geo_prior build file is not available. You can download it from GitHub.

Presence-Only Geographical Priors for Fine-Grained Image Classification - ICCV 2019

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Quality

Security

License

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Support

geo_prior has a low active ecosystem.

It has 15 star(s) with 5 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

geo_prior has no issues reported. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of geo_prior is current.

Quality

geo_prior has no bugs reported.

Security

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

License

geo_prior does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

geo_prior 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.

Top functions reviewed by kandi - BETA

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

Load a dataset
Load inat data
Load Bird data
Return the path of the variable
Loads features from a file
Compute the accuracy for a set of examples
Compute kernel prior
Compute the nearest neighbor prior
Evaluate the Gaussian distribution
Validate the model
Get hyperparameters for cross validation
Train the model
Evaluate the model
This function creates a k - means grid from the training data
Calculate the prediction for the given model
Plot the GT locations for the given class
Make a dense prediction for the given model
Generate a random sample of background locations
Evaluate bounding box for a given location
Creates a dense prediction for a given model
Wrapper function for dense prediction
Return the path of a variable
Download a pre - trained model
Parse eval_params
Convert location to torch
Adjust the learning rate of an optimizer
Handle pick event

Get all kandi verified functions for this library.

geo_prior Key Features

No Key Features are available at this moment for geo_prior.

geo_prior Examples and Code Snippets

No Code Snippets are available at this moment for geo_prior.

Community Discussions

No Community Discussions are available at this moment for geo_prior.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install geo_prior

You can download it from GitHub.
You can use geo_prior 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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