voxel_yolonet | Reproducing VoxelNet from Apple , forked from https : //github

by Kiwoo Python Version: Current License: No License

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

kandi X-RAY | voxel_yolonet Summary

voxel_yolonet is a Python library. voxel_yolonet has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Reproducing VoxelNet from Apple, forked from Adding YOLO-structure.

Support

Quality

Security

License

Reuse

Support

voxel_yolonet has a low active ecosystem.

It has 8 star(s) with 3 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

voxel_yolonet has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of voxel_yolonet is current.

Quality

voxel_yolonet has 0 bugs and 0 code smells.

Security

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

voxel_yolonet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

voxel_yolonet 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

voxel_yolonet 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.

It has 3595 lines of code, 147 functions and 21 files.

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

Top functions reviewed by kandi - BETA

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

Perform false - patch step
Run a feature network
Convert a list of labels to 2D boxes
Compute the intersection of two boxes
Convert a box2d box to labels
Perform image augmentation
Distort the image using random distort
Generate a random scale
Flattens an image
Convert a list of label strings to 2D boxes
Calculate volume loss
Run featureNet
Main worker thread
Train a single training step
Calculate the iou angle between two boxes
Calculate NMS of boxes
Draw bbox2d boxes on the given image
Load a single image file
Loads a training image
Convert a corner box to a 3d box
Save a PIL image
Calculate a single training step
Load a set of images
Validate a single step
Evaluate a single step
Predict a single step
Create a worker for a given tag

Get all kandi verified functions for this library.

voxel_yolonet Key Features

No Key Features are available at this moment for voxel_yolonet.

voxel_yolonet Examples and Code Snippets

No Code Snippets are available at this moment for voxel_yolonet.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install voxel_yolonet

You can download it from GitHub.
You can use voxel_yolonet 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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