X-ray-classification | ray Images | Machine Learning library

by bendidi Python Version: Current License: MIT

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

kandi X-RAY | X-ray-classification Summary

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

X-ray Images (Chest images) analysis and anomaly detection using Transfer learning with inception v2

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Quality

Security

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X-ray-classification has a low active ecosystem.

It has 83 star(s) with 44 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 2 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of X-ray-classification is current.

Quality

X-ray-classification has 0 bugs and 0 code smells.

Security

X-ray-classification has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

X-ray-classification code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

X-ray-classification is licensed under the MIT License. This license is Permissive.

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

Reuse

X-ray-classification releases are not available. You will need to build from source code and install.

X-ray-classification has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

X-ray-classification saves you 323 person hours of effort in developing the same functionality from scratch.

It has 775 lines of code, 35 functions and 8 files.

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

Top functions reviewed by kandi - BETA

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

Inception ResNet v2 .
Runs the model .
Preprocess the image .
Gets a single split .
Randomly crop a bounding box .
Distort the color .
Convert a dataset to a single dataset .
Loads a single image .
Main function .
Prepare image for evaluation .

Get all kandi verified functions for this library.

X-ray-classification Key Features

No Key Features are available at this moment for X-ray-classification.

X-ray-classification Examples and Code Snippets

No Code Snippets are available at this moment for X-ray-classification.

Community Discussions

Trending Discussions on X-ray-classification

Finding missing lines in file

QUESTION

Finding missing lines in file

Asked 2018-Jan-20 at 14:45

I have a 7000+ lines .txt file, containing description and ordered path to image. Example:

...

ANSWER

Answered 2018-Jan-20 at 14:33

You can try this:

Source https://stackoverflow.com/questions/48356973

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

Vulnerabilities

No vulnerabilities reported

Install X-ray-classification

In the data folder (cd data/) :. 1 - Use python get_data.py to download scrapped image data from openi.nlm.nih.gov. It has a large base of Xray,MRI, CT scan images publically available.Specifically Chest Xray Images have been scraped.The images will be downloaded and saved in images/ and the labels in data_new.json (it might take a while).

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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