upadted and deployed flask server

Author: soumyajit4419

.gitignore

@@ -0,0 +1 @@
+*/__pycache__

Assets/web.gif

@@ -0,0 +1,29 @@
+from flask import Flask, render_template, jsonify, request, Markup
+from model import predict_image
+import utils
+
+app = Flask(__name__)
+
+
+@app.route('/', methods=['GET'])
+def home():
+    return render_template('index.html')
+
+
+@app.route('/predict', methods=['GET', 'POST'])
+def predict():
+    if request.method == 'POST':
+        try:
+            file = request.files['file']
+            img = file.read()
+            prediction = predict_image(img)
+            print(prediction)
+            res = Markup(utils.disease_dic[prediction])
+            return render_template('display.html', status=200, result=res)
+        except:
+            pass
+    return render_template('index.html', status=500, res="Internal Server Error")
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

Flask/Models/plantDisease-resnet34.pth

@@ -0,0 +1,42 @@
+import torch
+import torch.nn as nn
+import torchvision.models as models
+import torchvision.transforms as transforms
+from PIL import Image
+import io
+
+
+class Plant_Disease_Model(nn.Module):
+
+    def __init__(self):
+        super().__init__()
+        self.network = models.resnet34(pretrained=True)
+        num_ftrs = self.network.fc.in_features
+        self.network.fc = nn.Linear(num_ftrs, 38)
+
+    def forward(self, xb):
+        out = self.network(xb)
+        return out
+
+
+transform = transforms.Compose(
+    [transforms.Resize(size=128),
+     transforms.ToTensor()])
+
+num_classes = ['Apple___Apple_scab', 'Apple___Black_rot', 'Apple___Cedar_apple_rust', 'Apple___healthy', 'Blueberry___healthy', 'Cherry_(including_sour)___Powdery_mildew', 'Cherry_(including_sour)___healthy', 'Corn_(maize)___Cercospora_leaf_spot Gray_leaf_spot', 'Corn_(maize)___Common_rust_', 'Corn_(maize)___Northern_Leaf_Blight', 'Corn_(maize)___healthy', 'Grape___Black_rot', 'Grape___Esca_(Black_Measles)', 'Grape___Leaf_blight_(Isariopsis_Leaf_Spot)', 'Grape___healthy', 'Orange___Haunglongbing_(Citrus_greening)', 'Peach___Bacterial_spot', 'Peach___healthy',
+               'Pepper,_bell___Bacterial_spot', 'Pepper,_bell___healthy', 'Potato___Early_blight', 'Potato___Late_blight', 'Potato___healthy', 'Raspberry___healthy', 'Soybean___healthy', 'Squash___Powdery_mildew', 'Strawberry___Leaf_scorch', 'Strawberry___healthy', 'Tomato___Bacterial_spot', 'Tomato___Early_blight', 'Tomato___Late_blight', 'Tomato___Leaf_Mold', 'Tomato___Septoria_leaf_spot', 'Tomato___Spider_mites Two-spotted_spider_mite', 'Tomato___Target_Spot', 'Tomato___Tomato_Yellow_Leaf_Curl_Virus', 'Tomato___Tomato_mosaic_virus', 'Tomato___healthy']
+
+
+model = Plant_Disease_Model()
+model.load_state_dict(torch.load(
+    './Models/plantDisease-resnet34.pth', map_location=torch.device('cpu')))
+model.eval()
+
+
+def predict_image(img):
+    img_pil = Image.open(io.BytesIO(img))
+    tensor = transform(img_pil)
+    xb = tensor.unsqueeze(0)
+    yb = model(xb)
+    _, preds = torch.max(yb, dim=1)
+    return num_classes[preds[0].item()]

Flask/Template/images/b3.jpg

@@ -0,0 +1,7 @@
+numpy
+pandas
+Flask
+Pillow
+gunicorn == 20.0.4
+https://download.pytorch.org/whl/cpu/torch-1.8.0%2Bcpu-cp36-cp36m-linux_x86_64.whl
+https://download.pytorch.org/whl/cpu/torchvision-0.9.0%2Bcpu-cp36-cp36m-linux_x86_64.whl

Flask/Template/images/b6.jpg

@@ -469,7 +469,7 @@ background-color: #212121;
 /* banner */
 
 .main-top {
-  background: linear-gradient(rgba(46, 46, 46, 0.418), rgba(27, 27, 27, 0.349)),
+  background: linear-gradient(rgba(46, 46, 46, 0.493), rgba(27, 27, 27, 0.466)),
     url(../images/b7.jpg) no-repeat bottom;
   background-size: cover;
   -webkit-background-size: cover;
@@ -532,9 +532,34 @@ button.btn1:hover,
 }
 
 /* //banner */
+/*--inner-banner -- */
+.inner_page-banner {
+  text-align: center;
+  background: url(../images/b7.jpg) no-repeat center;
+  background-size: cover;
+  -webkit-background-size: cover;
+  -moz-background-size: cover;
+  -o-background-size: cover;
+  -ms-background-size: cover;
+  min-height: 300px;
+}
 
-/* about */
+.using-border {
+  width: 100%;
+  border: none;
+  background: #7d5dba;
+  text-align: center;
+}
 
+ul.short_ls li a {
+  color: #ffffff;
+  text-decoration: none;
+}
+
+/* about */
+.about-two-grids{
+color: rgb(129, 40, 189);
+}
 .about-oil-w3layouts {
   padding: 3em 1em;
   color: #000;
@@ -600,10 +625,10 @@ a.move-top {
     font-size: 31px;
   }
   #logo a {
-    font-size: 32px;
+    font-size: 30px;
   }
   .title {
-    font-size: 35px;
+    font-size: 30px;
   }
   .collection-w3layouts h4,
   .ser-sevice-grid h4,

Flask/app.py

@@ -0,0 +1,99 @@
+<!DOCTYPE html>
+<html>
+
+<head>
+  <title>Plant AI</title>
+  <!--meta tags -->
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <!--//meta tags ends here-->
+  <!--booststrap-->
+  <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css"
+    integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
+  <!--//booststrap end-->
+
+  <!-- font-awesome icons -->
+  <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css"
+    integrity="sha512-SfTiTlX6kk+qitfevl/7LibUOeJWlt9rbyDn92a1DqWOw9vWG2MFoays0sgObmWazO5BQPiFucnnEAjpAB+/Sw=="
+    crossorigin="anonymous" />
+  <!-- //font-awesome icons -->
+
+  <!--stylesheets-->
+  <link href="../static/styles/style.css" rel='stylesheet' type='text/css' media="all">
+  <!--//stylesheets-->
+
+</head>
+
+<body>
+  <!--headder-->
+  <div class="header-outs inner_page-banner" id="home">
+    <div class="headder-top">
+      <!-- nav -->
+      <nav>
+        <div id="logo">
+          <h1><a href="/">Plant-AI</a></h1>
+        </div>
+
+      </nav>
+      <!-- //nav -->
+    </div>
+  </div>
+  <!--//headder-->
+  <!-- short -->
+  <div class="using-border py-3">
+    <div class="inner_breadcrumb  ml-4">
+      <ul class="short_ls">
+        <li>
+          <a href="/">Home</a>
+      </ul>
+    </div>
+  </div>
+  <!-- //short-->
+  <!-- about -->
+  <section class="about py-lg-4 py-md-3 py-sm-3 py-3" id="about">
+    <div class="container py-lg-5 py-md-4 py-sm-4 py-3">
+      <div class="row" style="justify-content: center;">
+        <div class="col-md-10 about-two-grids">
+          <h3 class="mb-md-4 mb-sm-3 mb-3 text-center">Result</h3>
+          <div class="about-para-txt text-justify">
+            {{result}}
+
+          </div>
+        </div>
+      </div>
+    </div>
+  </section>
+  <!-- //about -->
+
+  <!-- footer -->
+  <footer>
+    <div class="container pt-5 pb-3">
+      <div class="footer-w3layouts-head text-center">
+        <h2><a href="/">Plant-AI</a></h2>
+      </div>
+      <div class="bottem-wthree-footer text-center pt-md-4 pt-3">
+        <p>
+          All Rights Reserved | Design by Soumyajit
+        </p>
+      </div>
+      <!-- move icon -->
+      <div class="text-center">
+        <a href="#home" class="move-top text-center mt-3"><i class="fa fa-arrow-up" aria-hidden="true"></i></a>
+      </div>
+      <!--//move icon -->
+    </div>
+  </footer>
+  <!--//footer -->
+
+  <script src="https://code.jquery.com/jquery-3.2.1.slim.min.js"
+    integrity="sha384-KJ3o2DKtIkvYIK3UENzmM7KCkRr/rE9/Qpg6aAZGJwFDMVNA/GpGFF93hXpG5KkN"
+    crossorigin="anonymous"></script>
+  <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js"
+    integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q"
+    crossorigin="anonymous"></script>
+  <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js"
+    integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl"
+    crossorigin="anonymous"></script>
+</body>
+
+</html>

Flask/model.py

@@ -19,7 +19,7 @@
   <!-- //font-awesome icons -->
 
   <!--stylesheets-->
-  <link href="css/style.css" rel='stylesheet' type='text/css' media="all">
+  <link href="../static/styles/style.css" rel='stylesheet' type='text/css' media="all">
   <!--//stylesheets-->
 
 </head>
@@ -54,7 +54,8 @@ <h5>Offering Farming Solutions Worldwide
           </h5>
         </div>
         <div class="two-demo-button mt-md-4 mt-3">
-          <p> Developing models for making disease detection easy and imporving crop production</p>
+          <p> Developing models for making disease detection easy and providing solutions for improving crop production
+          </p>
         </div>
 
       </div>
@@ -66,15 +67,19 @@ <h5>Offering Farming Solutions Worldwide
   <section class="about py-lg-4 py-md-3 py-sm-3 py-3" id="about">
     <div class="container py-lg-5 py-md-4 py-sm-4 py-3">
       <div class="row">
-        <div class="col-lg-6 about-imgs-txt pt-10">
-          <img src="images/4.jpg" alt="news image" class="img-fluid" style="border-radius: 8px;">
+        <div class="col-lg-6 about-imgs-txt pt-3">
+          <img src="../static/images/4.jpg" alt="news image" class="img-fluid" style="border-radius: 8px;">
         </div>
-        <div class="col-lg-6 text-justify about-two-grids pt-5">
-          <h3 class="title  mb-md-4 mb-sm-3 mb-3 text-center">About</h3>
+        <div class="col-lg-6 text-justify about-two-grids pt-3">
+          <h3 class="title text-center">About</h3>
           <div class="about-para-txt">
-            <p>sed do eiusmod tempor incididunt ut Lorem ipsum dolor sit amet Lorem ipsum dolor sit amet, eiusmod tempor
-              incididunt ut labore et consectetur adipiscing sed do eiusmod tempor incididunt ut Lorem ipsum dolor sit
-              amet Lorem ipsum dolor sit amet, eiusmod tempor incididunt ut labore et consectetur adipiscing</p>
+            <p>Food security for billions of people on earth requires minimizing crop damage by timely detection of
+              diseases.Developing methods for detection of plant diseases serves the dual purpose of increasing crop
+              yield and reducing pesticide use without knowing about the proper disease. Along with development of
+              better crop varieties, disease detection is thus paramount goal for achieving food security. The
+              traditional method of disease detection has been to use manual examination by either farmers or experts,
+              which can be time consuming and costly, proving infeasible for millions of small and medium sized farms
+              around the world.</p>
           </div>
         </div>
       </div>
@@ -104,8 +109,8 @@ <h4 class="pb-3">Easy Detection</h4>
               <span class="fa fa-pagelines" aria-hidden="true"></span>
             </div>
             <div class="ser-sevice-grid">
-              <h4 class="pb-3">High Accuracy</h4>
-              <p>The Accuracy of correct detection is about 98%.</p>
+              <h4 class="pb-3">Cause and Solution</h4>
+              <p>Provides the cause and solution of the identified diseases.</p>
             </div>
           </div>
         </div>
@@ -128,9 +133,19 @@ <h4 class="pb-3">Large Plant Support</h4>
   <section class="blog_w3ls py-3 pb-5 pt-10" id="test">
     <div class="container pb-xl-5 pb-lg-3">
       <h3 class="title text-center mb-lg-5 mb-md-4 mb-sm-4 mb-3"> Test Your Plants</h3>
-      <div class="row">
-
+      <div class="row" style="justify-content: center;">
+        <form action="{{ url_for('predict') }}" method="POST" enctype=multipart/form-data>
+          <div class="form-group text-center">
+            <label for="exampleFormControlFile1"><b>Input a file</b></label>
+            <input type="file" name="file" class="form-control-file" id="inputImage" onchange=previewImage(event)
+              required>
+            <br />
+            <button class="btn btn-primary" type="submit"> Predict </button>
+          </div>
+        </form>
       </div>
+      <img id="output-image" class="rounded mx-auto d-block" />
+      <br />
     </div>
 
   </section>
@@ -164,6 +179,17 @@ <h2><a href="index.html">Plant-AI</a></h2>
   <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js"
     integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl"
     crossorigin="anonymous"></script>
+
+  <script>
+    function previewImage(event) {
+      var reader = new FileReader();
+      reader.onload = function () {
+        var output = document.getElementById('output-image')
+        output.src = reader.result;
+      }
+      reader.readAsDataURL(event.target.files[0]);
+    }
+  </script>
 </body>
 
 </html>