keras-yolo3-detection | YOLO v3 物体检测算法

by SpikeKing Python Version: Current License: No License

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

kandi X-RAY | keras-yolo3-detection Summary

keras-yolo3-detection is a Python library. keras-yolo3-detection has no vulnerabilities, it has build file available and it has low support. However keras-yolo3-detection has 1 bugs. You can download it from GitHub.

YOLO v3 物体检测算法

Support

Quality

Security

License

Reuse

Support

keras-yolo3-detection has a low active ecosystem.

It has 602 star(s) with 234 fork(s). There are 31 watchers for this library.

It had no major release in the last 6 months.

There are 25 open issues and 11 have been closed. On average issues are closed in 11 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of keras-yolo3-detection is current.

Quality

keras-yolo3-detection has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 32 code smells.

Security

keras-yolo3-detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

keras-yolo3-detection code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

keras-yolo3-detection 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

keras-yolo3-detection 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.

keras-yolo3-detection saves you 586 person hours of effort in developing the same functionality from scratch.

It has 1366 lines of code, 96 functions and 14 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed keras-yolo3-detection and discovered the below as its top functions. This is intended to give you an instant insight into keras-yolo3-detection implemented functionality, and help decide if they suit your requirements.

Calculate yolo loss
Compute the intersection of two boxes
Computes the yolo head
Generate train file
Traverse all files in root_dir
Read data from a file
Sort two lists
Create a pretrained model
Yolo body
Generate data file
Constructs a tiny yolo body
Generate keras model
Generate a stream of unique section names
Test for k - means clustering
Merges all files in folder to merge_file
Find the word positions in the original string
Draws an image
Removes lines from a file
Calculate the percentage of two numbers
Write data to a file
Display a set of data points
Wrapper for data_generator
Convert a list of unicode strings to unicode
Detect image for test
Read anchors from file
Get the list of class names

Get all kandi verified functions for this library.

keras-yolo3-detection Key Features

No Key Features are available at this moment for keras-yolo3-detection.

keras-yolo3-detection Examples and Code Snippets

No Code Snippets are available at this moment for keras-yolo3-detection.

Community Discussions

No Community Discussions are available at this moment for keras-yolo3-detection.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install keras-yolo3-detection

You can download it from GitHub.
You can use keras-yolo3-detection 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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