Update app.py

app.py

@@ -1,15 +1,28 @@
+!pip install tensorflow==2.11.0
 import gradio as gr
-import tensorflow
+
+# Import tensorflow here
+import tensorflow as tf 
+
 from tensorflow.keras.utils import img_to_array,load_img
-from keras.models import load_model
+from tensorflow.keras.models import load_model # Use tensorflow.keras.models
 import numpy as np
 
 # Load the pre-trained model from the local path
-model_path = 'Mango.h5'
-model = load_model(model_path)  # Load the model here
+model_path = '/content/tomato.h5'
+
+# Define custom objects to handle potential incompatibilities
+custom_objects = {'DepthwiseConv2D': tf.keras.layers.DepthwiseConv2D} 
+
+# Load the model with custom_objects
+model = load_model(model_path, custom_objects=custom_objects)  
+
+# ... (rest of your code) 
+
+# ... (rest of your code)  # Load the model here
 
 def predict_disease(image_file, model, all_labels):
-    
+
     try:
         # Load and preprocess the image
         img = load_img(image_file, target_size=(224, 224))  # Use load_img from tensorflow.keras.utils
@@ -25,8 +38,8 @@ def predict_disease(image_file, model, all_labels):
         predicted_label = all_labels[predicted_class]
 
         # Print the predicted label to the console
-        
-        if predicted_label=='Mango Anthracrose':
+
+        if predicted_label=='Tomato Yellow Leaf Curl Virus':
             predicted_label = """<style>
                       li{
                         font-size: 15px;
@@ -57,21 +70,20 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Anthracrose</b></center></h3>
+                <h3><center><b>Tomato Yellow Leaf Curl Virus</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Mancozeb</li>
-                    <li>2. Azoxystrobin</li>
-                    <li>3. carbendazim</li>
-                    <li>4. Propiconazole</li>
-                    <li>5. Thiophanate-methyl</li>
-                    <li>6. Copper Sulfate</li>
+                    <li>1. imidacloprid</li>
+                    <li>2. thiamethoxam</li>
+                    <li>3. Spinosad</li>
+                    <li>4. Acetamiprid</li>
+
                 </ul><br>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
 
             """
-        elif predicted_label=='Mango Bacterial Canker':
+        elif predicted_label=='Tomato Target Spot':
             predicted_label = """
             <style>
                       li{
@@ -103,22 +115,22 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Bacterial Canker</b></center></h3>
+                <h3><center><b>Tomato Target Spot</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Copper Hydroxide</li>
-                    <li>2. Copper Oxychloride</li>
-                    <li>3. Streptomycin</li>
-                    <li>4. oxytetracycline</li>
-                    <li>5. Neem oil</li>
-                    <li>6. Garlic oil</li>
+                    <li>1. Azoxystrobin</li>
+                    <li>2. Boscalid</li>
+                    <li>3. Mancozeb</li>
+                    <li>4. Chlorothalonil</li>
+                    <li>5. Propiconazole</li>
+
                 </ul>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
 
 
             """
-        elif predicted_label=='Mango Cutting Weevil':
+        elif predicted_label=='Tomato Spider mites':
             predicted_label = """
             <style>
                       li{
@@ -150,15 +162,15 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Cutting Weevil</b></center></h3>
+                <h3><center><b>Tomato Spider mites</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Imidacloprid</li>
-                    <li>2. Thiamethoxam</li>
-                    <li>3. Chlorpyrifos</li>
-                    <li>4. Lambda-cyhalothrin</li>
-                    <li>5. Fipronil</li>
-                    <li>6. Neem oil</li>
+                    <li>1. Abamectin</li>
+                    <li>2. Spiromesifen</li>
+                    <li>3. Miticides</li>
+                    <li>4. insecticidal soap</li>
+
+                    <li>5. Neem oil</li>
                 </ul>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
@@ -166,7 +178,7 @@ def predict_disease(image_file, model, all_labels):
 
             """
 
-        elif predicted_label=='Mango Die Back':
+        elif predicted_label=='Tomato Septoria leaf spot':
             predicted_label = """
             <style>
                       li{
@@ -198,22 +210,21 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Die Back</b></center></h3>
+                <h3><center><b>Tomato Septoria leaf spot</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Carbendazim</li>
-                    <li>2. Mancozeb</li>
-                    <li>3. Azoxystrobin</li>
-                    <li>4. Triazole</li>
-                    <li>5. Potassium bicarbonate</li>
-                    <li>6. Sodium bicarbonate</li>
+                    <li>1. Azoxystrobin</li>
+                    <li>2. Boscalid</li>
+                    <li>3. Mancozeb</li>
+                    <li>4. Chlorothalonil</li>
+                    <li>5. Propiconazole</li>
                 </ul>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
 
 
             """
-        elif predicted_label=='Mango Gall Midge':
+        elif predicted_label=='Tomato Mosaic virus':
             predicted_label = """
             <style>
                       li{
@@ -245,22 +256,22 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Gall Midge</b></center></h3>
+                <h3><center><b>Tomato Mosaic virus</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
                     <li>1. Imidacloprid</li>
                     <li>2. Thiamethoxam</li>
-                    <li>3. Chlorpyrifos</li>
-                    <li>4. Lambda-cyhalothrin</li>
-                    <li>5. Spinosad</li>
-                    <li>6. Pyrethrin</li>
+                    <li>3. Acetamiprid</li>
+                    <li>4. Dinotefuran</li>
+                    <li>5. Pyrethrin</li>
+
                 </ul>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
 
 
             """
-        elif predicted_label=='Mango Powdery Mildew':
+        elif predicted_label=='Tomato Leaf Mold':
             predicted_label = """
             <style>
                       li{
@@ -292,15 +303,14 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Powdery Mildew</b></center></h3>
+                <h3><center><b>Tomato Leaf Mold</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Sulfur</li>
-                    <li>2. Bicarbonates</li>
-                    <li>3. Myclobutanil</li>
-                    <li>4. Triadimefon</li>
+                    <li>1. Azoxystrobin</li>
+                    <li>2. Boscalid</li>
+                    <li>3. Mancozeb</li>
+                    <li>4. Chlorothalonil</li>
                     <li>5. Propiconazole</li>
-                    <li>6. Azoxystrobin</li>
                 </ul>
                 <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
                 <p>Be sure to follow local regulations and guidelines for application</p>
@@ -308,7 +318,7 @@ def predict_disease(image_file, model, all_labels):
 
             """
 
-        elif predicted_label=='Mango Sooty Mould':
+        elif predicted_label=='Tomato Late blight':
             predicted_label = """
                 <style>
                       li{
@@ -340,13 +350,106 @@ def predict_disease(image_file, model, all_labels):
                       }
 
                 </style>
-                <h3><center><b>Mango Sooty Mould</b></center></h3>
+                <h3><center><b>Tomato blight</b></center></h3>
                 <h4>PESTICIDES TO BE USED:</h4>
                 <ul>
-                    <li>1. Imidacloprid (Neonicotinoid)</li>
-                    <li>2. Thiamethoxam (Neonicotinoid)</li>
-                    <li>3. Bifenthrin (Pyrethroid)</li>
-                    <li>4. Lambda-cyhalothrin (Pyrethroid)</li>
+                    <li>1. metalaxl</li>
+                    <li>2. Chlorothalonil</li>
+                    <li>3. Mancozeb</li>
+                    <li>4. Copper oxychloride</li>
+                    <li>5. Azoxystrobin</li>
+
+                </ul>
+                <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
+                <p>Be sure to follow local regulations and guidelines for application</p>
+
+
+            """
+        elif predicted_label=='Tomato Early blight':
+            predicted_label = """
+                <style>
+                      li{
+                        font-size: 15px;
+                        margin-left: 90px;
+                        margin-top: 15px;
+                        margin-bottom: 15px;
+                      }
+                      h4{
+                        font-size: 17px;
+                        margin-top: 15px;
+                      }
+                      h4:hover{
+                        cursor: pointer;
+                      }
+
+                      h3:hover{
+                        cursor: pointer;
+                        color: blue;
+                        transform: scale(1.3);
+                      }
+                      .note{
+                        text-align: center;
+                        font-size: 16px;
+                      }
+                      p{
+                        font-size: 13px;
+                        text-align: center;
+                      }
+
+                </style>
+                <h3><center><b>Tomato blight</b></center></h3>
+                <h4>PESTICIDES TO BE USED:</h4>
+                <ul>
+                    <li>1. Azoxystrobin</li>
+                    <li>2. Boscalid</li>
+                    <li>3. Mancozeb</li>
+                    <li>4. Chlorothalonil</li>
+                    <li>5. Propiconazole</li>
+                </ul>
+                <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
+                <p>Be sure to follow local regulations and guidelines for application</p>
+
+
+            """
+        elif predicted_label=='Tomato Bacterial spot':
+            predicted_label = """
+                <style>
+                      li{
+                        font-size: 15px;
+                        margin-left: 90px;
+                        margin-top: 15px;
+                        margin-bottom: 15px;
+                      }
+                      h4{
+                        font-size: 17px;
+                        margin-top: 15px;
+                      }
+                      h4:hover{
+                        cursor: pointer;
+                      }
+
+                      h3:hover{
+                        cursor: pointer;
+                        color: blue;
+                        transform: scale(1.3);
+                      }
+                      .note{
+                        text-align: center;
+                        font-size: 16px;
+                      }
+                      p{
+                        font-size: 13px;
+                        text-align: center;
+                      }
+
+                </style>
+                <h3><center><b>Tomato Bacterial spot</b></center></h3>
+                <h4>PESTICIDES TO BE USED:</h4>
+                <ul>
+                    <li>1. Copper oxychloride</li>
+                    <li>2. Streptomycin</li>
+                    <li>3. tetracycline</li>
+                    <li>4. Oxytetracline(Terramycin)</li>
                     <li>5. Insecticidal soap</li>
                     <li>6. Horticultural oil</li>
                 </ul>
@@ -355,9 +458,13 @@ def predict_disease(image_file, model, all_labels):
 
 
             """
-        else:
-          predicted_label = """<h3 align="center">Mango Healthy</h3><br><br>
+
+        elif predicted_label=='Tomato Healthy':
+
+          predicted_label = """<h3 align="center">Tomato Healthy</h3><br><br>
           <center>No need use Pesticides</center>"""
+        else:
+          predict_label="choose correct image"
 
         return predicted_label
 
@@ -368,14 +475,16 @@ def predict_disease(image_file, model, all_labels):
 
 # List of class labels
 all_labels = [
-    'Mango Anthracrose',
-    'Mango Bacterial Canker',
-    'Mango Cutting Weevil',
-    'Mango Die Back',
-    'Mango Gall Midge',
-    'Mango Healthy',
-    'Mango Powdery Mildew',
-    'Mango Sooty Mould'
+    'Tomato Yellow Leaf Curl Virus',
+    'Tomato Target Spot',
+    'Tomato Spider mites',
+    'Tomato Septoria leaf spot',
+    'Tomato Mosaic virus',
+    'Tomato Leaf Mold',
+    'Tomato Late blight',
+    'Tomato Healthy',
+    'Tomato Early blight',
+    'Tomato Bacterial spot'
 ]
 
 # Define the Gradio interface
@@ -387,9 +496,10 @@ gr_interface = gr.Interface(
     fn=gradio_predict,  # Function to call for predictions
     inputs=gr.Image(type="filepath"),  # Upload image as file path
     outputs="html",  # Output will be the class label as text
-    title="Plant Disease Predictor",
+    title="Tomato Disease Predictor",
     description="Upload an image of a plant to predict the disease.",
 )
 
 # Launch the Gradio app
+
 gr_interface.launch(share=True)