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Skin Disease Detection web app predict the skin disease from a single image in less than one second.

License: Apache License 2.0

Python 7.31% CSS 28.24% HTML 18.10% JavaScript 46.34%
flask flask-application openvino opencv edge-detection edge intel-openvino web-app skin-lesion-classification skin-disease

skin-disease-detection-edge's Introduction

Skin Disease Detection using AI at the Edge

Skin Disease Detection at edge predicts the disease of skin from the image of that infected part in less than one second and that's where AI at the Edge come.

This web app simply take a disease image using a web interface and give the disease name with accuracy and time taken for prediction.

Getting Started

Prerequisites

Prerequisite 1

Prerequisite 2

First make sure that you have installed the anaconda.
See this page for installing anaconda.

Prerequisite 3

Install the OpenVINO toolkit developed by Intel. OpenVINO toolkit is the secret behind AI at the Edge.
See this page for installing anaconda.

Installing

Step 1

Create a new environment using anaconda:-

conda create -n <envname> python=3.7

For more information see here

Step 2

Activate the environment:-

conda activate <envname>

Step 3

Go to the project directory.
Install all the requirements:-

pip install -r requirements.txt

Running the app

Step 1

Activate the created environment:-

conda activate <envname>

Step 2

Activate the openvino source:-

<put your own openvino installation directory in the below command>

source </opt/intel/openvino/bin>/setupvars.sh

Step 3

Open the terminal/cmd in project directory or use


cd <project_directory>

Step 4

Open the edge_app.py file and change the CPU_EXTENSION as per your installation directoty of openvino.

Step 5

Now finally run the app.py file using python:-

python app.py

Step 6

Open the link as specified in terminal which would be like as shown in the picture:-

terminal

So open the link shown as terminal here which is:- http://127.0.0.1:5000/

Home page will be like this:-

home

Click on the identify button of the page.

It will redirect you to upload page:-

upload

Upload the skin disease image:-

uploading

Now click on the upload button.

It will give the result as shown in below picture:-

prediction

Demo video

Demo_Video

Comparision

Comparision of Time taken for prediction Skin disease detection at edge with normal skin disease detection system (https://github.com/denilDG/skin-disease-detection).

Skin Disease Detection using tensorflow weight files

Skin_Disease

Skin Disease Detection at edge

Skin_Disease Detection_Edge

Note:

This model is not that much accurate. It's only for leaning the deployment of an web app using openvino and flask.

skin-disease-detection-edge's People

Contributors

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Watchers

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skin-disease-detection-edge's Issues

Report

Hi do u have a report for this project ?
can u please mail it to me [email protected]
for my mini project it will be very helpful. please

Source code

Hello and thank you for sharing your work!
Would it be possible to run the source code prediction without running the app? How?
Thank you in advance, Lucia

program on loading .so file sir the file is missing sir can you please help me sir

File "ie_api.pyx", line 592, in openvino.inference_engine.ie_api.IECore.add_extension
RuntimeError: Cannot load library '/opt/intel/openvino/deployment_tools/inference_engine/lib/intel64/libcpu_extension_sse4.so': 126 from cwd: C:\Users\jagan\Downloads\skin-disease-detection-edge-master\skin-disease-detection-edge-master

app.py working good sir please help me sir

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