<p align="center">
  <img src="https://user-images.githubusercontent.com/46085301/183135654-42cb6a4b-bf27-4e10-b2de-e6be196b2b96.png" height="150"/>
  <br/>
A Disease Detection Web App to assist radiologists to detect the presence of COVID-19.
</P>

<h2 id="description">Description</h2>
<blockquote>
<p>This project is a part of <a href="https://www.kuhackfest.com">KU HackFest 2022</a></p>
</blockquote>
<p>The main purpose of this project is to automate the process of COVID-19 diagnosis
and help radiologists, doctors and patients in their process by saving their precious time.
So, by using a trained model on COVID chest-X-ray images, It assists medical staff and radiologists
to detect the presence/sign of COVID in the chest-x-ray images reducing the workloads and speeding up the
diagnosis.</p>
<h2 id="installation">Installation</h2>
<p>Run my Project</p>
<pre><code class="language-shell">    # clone the repo and check into the dir
    git clone https://github.com/bhimrazy/covidologist
    cd covidologist

    # Setup environment and install all the requirements
    python -m venv venv
    source venv/bin/activate
    pip install -r requirements.txt

    # Setup kaggle key or download kaggle.json key file and place it in &quot;~/.kaggle&quot;
    export KAGGLE_USERNAME=&quot;your kaggle username&quot;
    export KAGGLE_KEY=&quot;your kaggle api key&quot;

    # Download Datasets from kaggle (https://www.kaggle.com/datasets/andyczhao/covidx-cxr2)
    kaggle datasets download -d andyczhao/covidx-cxr2

    # unzip to temp folder
    unzip covidx-cxr2.zip -d temp

    # remove zip file
    rm -rf covidx-cxr2.zip


    # prepare dataset folder
    python main.py prepare

    # train model
    python main.py train

    # generate metrics
    # python main.py generate


    # Run fast api app
    cd app &amp;&amp; uvicorn main:app --reload
</code></pre>
<h2 id="deployment-architecture">Deployment Architecture</h2>
<p><img src="https://user-images.githubusercontent.com/46085301/183252817-43d5a542-4f0f-4f11-ba62-d6b26cd0a816.png" alt="image"></p>
<p align="center">
Figure : Deployment Architeture of Covidologist
</P>

<h2 id="sample-images">Sample images</h2>
<table>
  <tr>
    <td>COVID Positive</td>
     <td>COVID Positive</td>
     <td>COVID Negative</td>
  </tr>
  <tr>
    <td><img src="https://user-images.githubusercontent.com/46085301/183252884-12c123bb-4611-4fd4-9a98-6d69389c5650.jpg" width=300 height=300></td>
    <td><img src="https://user-images.githubusercontent.com/46085301/183252895-b60d4106-2f55-46cd-93fd-673bae34b9f6.jpg" width=300 height=300></td>
    <td><img src="https://user-images.githubusercontent.com/46085301/183252943-c429de0f-bf21-4551-bbd8-ea7afbb1c76c.png" width=300 height=300></td>
  </tr>
 </table>

<h2 id="preview">Preview</h2>
<p><a href="https://covidologist.herokuapp.com/"><img src="https://user-images.githubusercontent.com/46085301/183138564-bdaaa457-5f31-47e5-889d-f7331a8ffebb.png" alt="covid 19 disease detection"></a></p>
<h2 id="📚-resources">📚 RESOURCES</h2>
<p>◆ PyTorch: <a href="https://pytorch.org">https://pytorch.org</a> <br/>
◆ FastAPI: <a href="https://fastapi.tiangolo.com">https://fastapi.tiangolo.com</a> <br/>
◆ COVIDx CXR-2 Dataset: <a href="https://www.kaggle.com/datasets/andyczhao/covidx-cxr2">https://www.kaggle.com/datasets/andyczhao/covidx-cxr2</a></p>
<h2 id="author">Author</h2>
<ul>
<li><a href="https://www.github.com/bhimrazy">@bhimrazy</a></li>
</ul>


The main purpose of this project is to automate the process of COVID-19 diagnosis and help radiologists, doctors and patients in their process by saving their precious time. So, by using a trained model on COVID chest-X-ray images, It assists medical staff and radiologists to detect the presence/sign of COVID in the chest-x-ray images reducing the workloads and speeding up the diagnosis.

Covidologist : A Disease Detection Web App to assist radiologists to detect the presence of COVID-19.

<h1 id="ocr-with-tesseract-opencv-fastapi--and-python">OCR with Tesseract, OpenCV, FastAPI , and Python</h1>


This is an OCR project which is used to extract text from images using Tesseract.

How to OCR with Tesseract, OpenCV, FastAPI , and Python

<h1 id="how-to-build-and-deploy-an-image-recognition-app-using-fastapi-and-pytorch-">How to Build and Deploy an Image Recognition App using FastAPI and PyTorch ?</h1>
<p>This is an image recognition application based on the FastAPI framework and PyTorch which uses pretrained DenseNet 121 model to detect the Image.</p>
<p align="center">
  <img src="https://user-images.githubusercontent.com/46085301/139594375-790141df-482f-4a21-9b19-c0e47f2033f2.png" height="150"/>
  <br/>
  <b>Image Recognition App using FastAPI and PyTorch</b><br/>
In this project, I have tried to build and deploy an Image Recognition App using FastAPI and
PyTorch.
</P>

<h2 id="tutorial-">Tutorial <img src="https://user-images.githubusercontent.com/46085301/143214249-d6244995-1fdb-4c3f-b721-e65403a89607.gif" alt="Youtube gif" height="30"/></h2>
<p><a href="https://youtu.be/7Rm5mGhYWVI"><img src="https://user-images.githubusercontent.com/46085301/143211855-fe73e3b0-fc8c-4aa4-8428-e93cc16d6dfd.png" alt="fastapi pytorch image recognition"></a></p>
<h2 id="installation">Installation</h2>
<p>Run my Project</p>
<pre><code class="language-bash">  git clone https://github.com/bhimrazy/Image-Recognition-App-using-FastAPI-and-PyTorch
  cd Image-Recognition-App-using-FastAPI-and-PyTorch
  python -m venv venv
  source venv/bin/activate
  pip install -r requirements.txt
  uvicorn main:app --reload
</code></pre>
<h2 id="image-recognition-app-using-fastapi-and-pytorch-todo">Image Recognition App using FastAPI and PyTorch: TODO</h2>
<ul>
<li><p><input checked="" disabled="" type="checkbox"> 
Create a virtual environment</p>
</li>
<li><p><input checked="" disabled="" type="checkbox"> 
Create FastAPI App</p>
<ul>
<li>Install fast API</li>
<li>Install Uvicorn</li>
<li>Install Pytest</li>
<li>Install Jinja2</li>
<li>Install python-multipart</li>
<li>Install requests</li>
<li>Create a main file with some routes</li>
<li>Create a main test file to test the home page route</li>
</ul>
</li>
<li><p><input checked="" disabled="" type="checkbox"> 
Pytorch Setup</p>
<ul>
<li>Install torch &amp; torchvision (use cpu version for small size)</li>
</ul>
</li>
<li><p><input checked="" disabled="" type="checkbox"> 
Prediction</p>
<ul>
<li>Create a predict post route</li>
<li>Create a file utils.py</li>
<li>Test predict route</li>
<li>Create some helper function</li>
<li>Put some test images inside static folder</li>
<li>Create a test to upload an image in predict route</li>
<li>Predict</li>
</ul>
</li>
<li><p><input checked="" disabled="" type="checkbox"> 
Create a home page for prediction</p>
<ul>
<li>Create an index.html file inside the templates directory</li>
<li>Setup template and static directory in the main app</li>
<li>Initial HTML for home page</li>
<li>Use Tailwind CSS cdn link for css</li>
<li>Google Fonts</li>
<li>Create a form to predict</li>
<li>update homepage route for prediction</li>
<li>Update UI of the page</li>
<li>Add Some javascript to autoload the image</li>
<li>Add logo and favicon</li>
<li>Add meta tags</li>
<li>Add response image for preview as base64 data</li>
</ul>
</li>
</ul>
<h2 id="📚-resources">📚 RESOURCES:</h2>
<p>◆ PyTorch: <a href="https://pytorch.org/tutorials/intermediate/flask_rest_api_tutorial.html">https://pytorch.org/tutorials/intermediate/flask_rest_api_tutorial.html</a> <br/>
◆ FastAPI: <a href="https://fastapi.tiangolo.com">https://fastapi.tiangolo.com</a></p>
<h2 id="author">Author</h2>
<ul>
<li><a href="https://www.github.com/bhimrazy">@bhimrazy</a></li>
</ul>


Learn how to create an image recognition application based on the FastAPI framework and PyTorch which uses pretrained DenseNet 121 model to detect the Image.

How to Build and Deploy an Image Recognition App using FastAPI and PyTorch ?

Hi👋, I am Bhimraj Yadav. I like to explore Machine Learning, Data Science and Computer Vision and apply these skills to develop some cool projects.

Projects

Covidologist : A Disease Detection Web App to assist radiologists to detect the presence of COVID-19.

How to OCR with Tesseract, OpenCV, FastAPI , and Python

How to Build and Deploy an Image Recognition App using FastAPI and PyTorch ?