rfnet | End Image Matching Network based on Receptive Field | Machine Learning library
kandi X-RAY | rfnet Summary
kandi X-RAY | rfnet Summary
rfnet is a Python library typically used in Artificial Intelligence, Machine Learning, Keras applications. rfnet 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.
RF-Net: An End-to-End Image Matching Network based on Receptive Field
RF-Net: An End-to-End Image Matching Network based on Receptive Field
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Quality
Security
License
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Support
rfnet has a low active ecosystem.
It has 121 star(s) with 19 fork(s). There are 5 watchers for this library.
It had no major release in the last 6 months.
There are 12 open issues and 7 have been closed. On average issues are closed in 21 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of rfnet is current.
Quality
rfnet has no bugs reported.
Security
rfnet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
rfnet 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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rfnet 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 rfnet and discovered the below as its top functions. This is intended to give you an instant insight into rfnet implemented functionality, and help decide if they suit your requirements.
- Forward a batch of images
- Clip a patch
- Pair network
- Apply preprocessing to the image
- Compute the feature map
- Softmax implementation
- Solve log - likelihood
- Evaluate the given model
- Calculate the distance between two points
- Reserve memory
- Return the string representation of gct
- Calculate the loss
- Compute pairwise distances between two matrices
- Generate a visual descriptor for vispy
- Returns the distance matrix between anchor points
- Detects and computes the image
- Rescale image
- Return a human - readable string representation of time
- Compute the feature from the input vector
- Compute the top k components of the top k points
- Pretty print a dictionary
- Compute the distance between two points
- Parse a numpy array from a numpy array
- Creates the optimizer for the optimizer
- Deserialize a Batch object
- Calculate the distance between two images
- Compute the threshold score between two points
- Argument parser
Get all kandi verified functions for this library.
rfnet Key Features
No Key Features are available at this moment for rfnet.
rfnet Examples and Code Snippets
No Code Snippets are available at this moment for rfnet.
Community Discussions
Trending Discussions on rfnet
QUESTION
Why is second generic type information lost when using "infer"?
Asked 2019-Oct-08 at 16:20
So I have a abstract base class which receives a value of ValueType and has a function which is able to transform it to TransformedType. This is solved via two generics:
ANSWER
Answered 2019-Sep-28 at 19:14Okay, for Question 2 first: yes, you can mostly remove the second type parameter and have it default to unknown if you define it like this:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install rfnet
You can download it from GitHub.
You can use rfnet 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 rfnet 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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