keras-frcnn | Keras Implementation of Faster R-CNN | Machine Learning library

by kbardool Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | keras-frcnn Summary

keras-frcnn is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras applications. keras-frcnn has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However keras-frcnn build file is not available. You can download it from GitHub.

Keras Implementation of Faster R-CNN

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Quality

Security

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keras-frcnn has a low active ecosystem.

It has 308 star(s) with 275 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 70 open issues and 25 have been closed. On average issues are closed in 79 days. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of keras-frcnn is current.

Quality

keras-frcnn has 0 bugs and 0 code smells.

Security

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

keras-frcnn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

keras-frcnn is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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

keras-frcnn saves you 642 person hours of effort in developing the same functionality from scratch.

It has 1492 lines of code, 57 functions and 15 files.

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

Top functions reviewed by kandi - BETA

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

Calculate the IOU angle
Return the intersection of two intersections
Return the intersection between two two arrays
Compute the intersection of two areas
Calculate new image size
Calculate the anchor region
Skip sample from img_data
Calculate rpn features for the network
Augment image
Convert an RPN layer to a ROI
Linear interpolation
Generate a list of non - maximum suppression
Base function
Convolution block
Constructs the identity block
Classifier for training
Time distributed convolution layer
Classifier layer
Compute the map of bounding boxes
Format an image

Get all kandi verified functions for this library.

keras-frcnn Key Features

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

keras-frcnn Examples and Code Snippets

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

Community Discussions

Trending Discussions on keras-frcnn

Can't train faster rcnn model in my custom dataset

QUESTION

Can't train faster rcnn model in my custom dataset

Asked 2021-Jan-16 at 05:31

So, I am trying to train faster rcnn model for my malaria data. I cloned the repository from https://github.com/kbardool/keras-frcnn.git . I added all the image file and the script itself inside the cloned folder but whenever I try to run the train_frcnn.py script, it shows me syntax error when there is no syntax error anywhere. What could the reason be?

The Error

...

ANSWER

Answered 2021-Jan-16 at 05:31

To run any command from jupyter notebook or colab notebook, you should always make it followed by '!' exclaimation symbol.

Try following,

Source https://stackoverflow.com/questions/65746648

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

Vulnerabilities

No vulnerabilities reported

Install keras-frcnn

You can download it from GitHub.
You can use keras-frcnn 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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