mxnet-landmark | landmark regression & data-augumentation

by chenzx921020 Python Version: Current License: No License

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

kandi X-RAY | mxnet-landmark Summary

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

landmark regression & data-augumentation

Support

Quality

Security

License

Reuse

Support

mxnet-landmark has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

mxnet-landmark has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mxnet-landmark is current.

Quality

mxnet-landmark has 0 bugs and 0 code smells.

Security

mxnet-landmark has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

mxnet-landmark code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

mxnet-landmark 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

mxnet-landmark releases are not available. You will need to build from source code and install.

mxnet-landmark has no build file. You will be need to create the build yourself to build the component from source.

It has 1229 lines of code, 67 functions and 17 files.

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

Top functions reviewed by kandi - BETA

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

Generate a symbolic symbol for training
Sp convolutional convolution
Create a pooling layer
Create dense block
Resolution residuals
Transition a block of data
Resolutional residuals
Add layer layer
Project a bounding box onto a bounding box
Normalize lmk
Calculate the metric for each label
Check label and preds
Show the image
Reproject a Lmk matrix
Updates the model
Check if label and pred
Updates the metric
Check if label and preds are valid
Calculate the sum of the metric

Get all kandi verified functions for this library.

mxnet-landmark Key Features

No Key Features are available at this moment for mxnet-landmark.

mxnet-landmark Examples and Code Snippets

No Code Snippets are available at this moment for mxnet-landmark.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install mxnet-landmark

You can download it from GitHub.
You can use mxnet-landmark 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 .

Find more information at: