Merge pull request #11 from Anantha-Rao12/master

Added blood smear images

Author: Anantha-Rao12

DeleMa_Detect/README.md

@@ -9,6 +9,7 @@
     - [On Desktop](#on-desktop)
     - [On Mobile](#on-mobile)
   - [Running DeleMa Detect Locally](#running-delema-detect-locally)
+  - [Sample Blood Smear Images](#sample-blood-smear-images)
   - [Contact Us](#contact-us)
 
 # DeleMa Detect Documentation
@@ -170,6 +171,10 @@ Activate the Virtual Environment by running the following.
 
 <br><br>
 
+# Sample BLood Smear Images
+
+We have added upto 20 blood smear images for testing purposes at ```./uploads/```. There are two directories called ```Parasitized``` and ```Uninfected```, each containing upto 10 images. These can be downloaded and tested by running the application locally or on our Heroku platform. 
+
 ---
 
 ## Contact Us

DeleMa_Detect/app.py

@@ -5,6 +5,7 @@
 import glob
 import re
 import numpy as np
+import time
 
 # Keras utils
 import tensorflow as tf
@@ -21,14 +22,18 @@
 app = Flask(__name__)
 
 # Model saved with Keras.save()
-MODEL_PATH='./model/VGG_94.52_11102020_8 49.h5'
+#MODEL_PATH='./model/custom_cnn_lenet_val_9539_oct_24_1100.h5' 
+#MODEL_PATH='./model/VGG_94.52_11102020_8 49.h5'
+
+MODEL_PATH = './model/model.h5'
+input_size=(100,100)
+
 model = load_model(MODEL_PATH)
 probability = 0.3
-target_size = (100,100)
 
-def model_predict(img_path,model_path):
+def model_predict(img_path,model_path,input_size):
 
-    img = image.load_img(img_path,target_size=(target_size))
+    img = image.load_img(img_path,target_size=input_size)
     img_array = image.img_to_array(img)
     img_array = np.expand_dims(img_array,axis=0) # changes input shape to a tensor (1,160,160,3)
     #img_array = preprocess_input(img_array) # preprocess input based on mobilenet_v2 conventions
@@ -51,20 +56,26 @@ def upload():
 
         # Save the file to ./uploads
         basepath = os.path.dirname(__file__)
+
+        # Append timestamp to ensure unique filename
         file_path = os.path.join(
-            basepath, 'uploads', secure_filename(f.filename))
+            basepath, 'uploads', secure_filename(f.filename + str(int(time.time()))))
         f.save(file_path)
 
         # Make prediction
-        prediction = model_predict(file_path, MODEL_PATH)
+        prediction = model_predict(file_path, MODEL_PATH, input_size)
 
         # Process your result for human
         # Preserve the 0- and 1- prefixes
         if prediction <= probability:
             result = f"1-The Image looks Parasitized.\nThe probability that the blood smear is uninfected is {prediction:.3} "
         else:
             result=f"0-The Image looks Uninfected.\nThe probability that the blood smear is uninfected is {prediction:.3} "
-        
+
+
+        # Delete the file
+        os.remove(file_path)
+                
         return result
     return None
 

…_Detect/model/VGG_94.52_11102020_8 49.h5 DeleMa_Detect/model/model.h5DeleMa_Detect/model/VGG_94.52_11102020_8 49.h5 renamed to DeleMa_Detect/model/model.h5 DeleMa_Detect/model/VGG_94.52_11102020_8 49.h5 renamed to DeleMa_Detect/model/model.h5

@@ -12,6 +12,48 @@ google-auth-oauthlib==0.4.1
 google-pasta==0.2.0
 greenlet==0.4.17
 grpcio==1.32.0
+h5py==2.10.0
+idna==2.10
+itsdangerous==1.1.0
+Jinja2==2.11.2
+Keras-Preprocessing==1.1.2
+Markdown==3.3
+MarkupSafe==1.1.1
+numpy==1.18.5
+oauthlib==3.1.0
+opt-einsum==3.3.0
+Pillow==7.2.0
+protobuf==3.13.0
+pyasn1==0.4.8
+pyasn1-modules==0.2.8
+requests==2.24.0
+requests-oauthlib==1.3.0
+rsa==4.6
+six==1.15.0
+tensorboard==2.3.0
+tensorboard-plugin-wit==1.7.0
+tensorflow==2.3.1
+tensorflow-estimator==2.3.0
+termcolor==1.1.0
+urllib3==1.25.10
+Werkzeug==1.0.1
+wrapt==1.12.1
+zope.event==4.5.0
+zope.interface==5.1.2
+absl-py==0.10.0
+astunparse==1.6.3
+cachetools==4.1.1
+certifi==2020.6.20
+chardet==3.0.4
+click==7.1.2
+Flask==1.1.2
+gast==0.3.3
+gevent==20.9.0
+google-auth==1.22.1
+google-auth-oauthlib==0.4.1
+google-pasta==0.2.0
+greenlet==0.4.17
+grpcio==1.32.0
 gunicorn==20.0.4
 h5py==2.10.0
 idna==2.10

DeleMa_Detect/model/model_mobilenetv2.h5 DeleMa_Detect/model/model1.h5DeleMa_Detect/model/model_mobilenetv2.h5 renamed to DeleMa_Detect/model/model1.h5

@@ -8,6 +8,10 @@
     background-color: #333333;
 }
 
+.navbar-brand {
+    font-size: 4vmin;
+}
+
 .card {
     height: 600px;
     margin-bottom: 60px;
@@ -135,6 +139,9 @@ h3 span {
     height: 100%;
 }
 
+a {
+    white-space: nowrap;
+}
 
 /* Footer */
 

DeleMa_Detect/requirements.txt

@@ -26,12 +26,16 @@
     <meta name="msapplication-TileColor" content="#00aba9">
     <meta name="msapplication-config" content="{{ url_for('static', filename='favicon/browserconfig.xml') }}">
     <meta name="theme-color" content="#ffffff">
+
+    <meta name="author" content="Anantha Rao, Purva Parmar">
+    <meta name="description" content="Malaria Diagnosis from Blood Smear Images">
+    <meta name="keywords" content="DeleMa Detect, Malaria Diagnosis, Deep Learning, iGEM, IISER Pune">
 </head>
 
 <body>
     <nav class="navbar navbar-dark">
         <div class="container justify-content-end">
-            <a class="navbar-brand" href="#">DeleMa Detect</a>
+            <a class="navbar-brand" href="#">DeleMa Detect | iGEM IISER Pune 2020</a>
         </div>
     </nav>
     <div class="container">
@@ -47,8 +51,7 @@
     <footer class="footer">
             <div class="container-fluid pb-5 text-center">
                 <div class="credits">
-                    <p class="github">Server Developed by Anantha Rao (<a href="https://github.com/Anantha-Rao12" target="_blank" rel="noopener noreferrer"><svg class="github-icon" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> Anantha-Rao12</a>)</p>
-                    <p class="github">Designed by Purva Parmar (<a href="https://github.com/TheReconPilot" target="_blank" rel="noopener noreferrer"><svg class="github-icon" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> TheReconPilot</a>)</p>
+                    <p class="github">Designed and Developed by Anantha Rao (<a href="https://github.com/Anantha-Rao12" target="_blank" rel="noopener noreferrer"><svg class="github-icon" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> Anantha-Rao12</a>) and Purva Parmar (<a href="https://github.com/TheReconPilot" target="_blank" rel="noopener noreferrer"><svg class="github-icon" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 496 512"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> TheReconPilot</a>)</p>
                     <p>As a part of iGEM IISER Pune 2020</p>
                 </div>
                 <div class="row align-items-center">

DeleMa_Detect/static/css/main.css

@@ -40,7 +40,7 @@ <h2>About DeleMa Detect</h2>
 
     <p>This is a part of iGEM IISER Pune '20 Project. More details can be found on our <a href="https://2020.igem.org/Team:IISER-Pune-India" target="_blank" rel="noopener noreferrer">Wiki Page</a>.</p>
 
-    <p>This Demo Web App is a part of DeleMa Detect, a deep learning framework for malaria diagnosis. Information about the Software and the usage protocol can be found on the <a href="https://2020.igem.org/Team:IISER-Pune-India/DeLeMa_Detect" target="_blank" rel="noopener noreferrer">DeleMa Detect Wiki Page</a>.</p>
+    <p>This Demo Web App is a part of DeleMa Detect, a deep learning framework for malaria diagnosis. Information about the Software and the usage protocol can be found on the <a href="https://2020.igem.org/Team:IISER-Pune-India/Software" target="_blank" rel="noopener noreferrer">DeleMa Detect Wiki Page</a>.</p>
 
     <p>The Server Code can be found on <a href="https://github.com/igemsoftware2020/IISER-Pune-India" target="_blank" rel="noopener noreferrer">iGEM IISER Pune's GitHub Repo</a>.</p>
 </div>