deepfitvlife

deepfit package


License
MIT
Install
pip install deepfitvlife==0.3

Documentation

DeepFit

DeepFit is an open source package for creating novel methods that help all the stake holders better manage Patient Engagement. It leverages research technology like Data Shapley, Multi-Accuracy and cPCA from Stanford Artificial Intelligence Labs (SAIL)

DeepFit

Getting Started

Please Install DeepFit package using

!pip install deepfitv

Programming Guide

Incision Object Declaration

deepfitv.incision.Incision(<path of image>)
  1. To identify incision image object detection run the object detection function run
deepfitv.incision.Incision(<path of image>).object_detection()
  1. To classify the incisin image into less than 30 or post 30 days of surgery run
deepfitv.incision.Incision(<path of image>).classify_image()
  1. To use SinGAN feature, use a single image and generate random sample images from it refer :
deepfitv.SinGAN.help()

Prerequisites

deepfitv.incision module requires 'imageai' and 'tensorflow' libraries as dependencies

!pip install tensorflow
!pip install imageai

To run the Incision Object Image use case one would need to download the model h5 files which we have developed and copy in the directory

Incision/models

[https://github.com/Virtusa-vLife/DeepFit/releases/download/deepfit/Image_classification.h5]

[https://github.com/Virtusa-vLife/DeepFit/releases/download/deepfit/detection_model.h5]

[https://github.com/OlafenwaMoses/ImageAI/releases/download/essential-v4/pretrained-yolov3.h5]

download reference json at

 Incision/json

[https://github.com/Virtusa-vLife/DeepFit/releases/download/deepfit/detection_config.json]

License

Coming Soon