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Update app.py
Browse files
app.py
CHANGED
@@ -1,463 +1,205 @@
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import gradio as gr
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from tensorflow.keras.utils import img_to_array,load_img
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from keras.models import load_model
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import numpy as np
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# Load the pre-trained model from the local path
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model_path = 'tomato.h5'
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model = load_model(model_path) # Load the model here
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try:
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# Load and preprocess the image
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img_array = img_to_array(img)
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img_array = np.expand_dims(img_array, axis=0) # Add batch dimension
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img_array = img_array / 255.0 # Normalize the image
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# Predict the class
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predictions = model.predict(img_array)
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predicted_class = np.argmax(predictions[0])
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# Get the predicted class label
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predicted_label = all_labels[predicted_class]
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# Print the predicted label to the console
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Yellow Leaf Curl Virus</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. imidacloprid</li>
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<li>2. thiamethoxam</li>
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<li>3. Spinosad</li>
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<li>4. Acetamiprid</li>
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</ul><br>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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elif predicted_label=='Tomato Target Spot':
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Target Spot</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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<p
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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elif predicted_label=='Tomato Spider mites':
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Spider mites</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Abamectin</li>
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<li>2. Spiromesifen</li>
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<li>3. Miticides</li>
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<li>4. insecticidal soap</li>
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<li>5. Neem oil</li>
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</ul>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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margin-left: 90px;
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Septoria leaf spot</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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elif predicted_label=='Tomato Mosaic virus':
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Mosaic virus</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Imidacloprid</li>
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<li>2. Thiamethoxam</li>
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<li>3. Acetamiprid</li>
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<li>4. Dinotefuran</li>
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<li>5. Pyrethrin</li>
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<p
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li{
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font-size: 15px;
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margin-left: 90px;
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Leaf Mold</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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<style>
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li{
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font-size: 15px;
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margin-left: 90px;
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato blight</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. metalaxl</li>
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<li>2. Chlorothalonil</li>
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<li>3. Mancozeb</li>
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<li>4. Copper oxychloride</li>
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<li>5. Azoxystrobin</li>
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<p
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<style>
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li{
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font-size: 15px;
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margin-left: 90px;
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato blight</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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elif predicted_label=='Tomato Bacterial spot':
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margin-top: 15px;
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margin-bottom: 15px;
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}
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h4{
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font-size: 17px;
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margin-top: 15px;
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}
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h4:hover{
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cursor: pointer;
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}
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h3:hover{
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cursor: pointer;
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color: blue;
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transform: scale(1.3);
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}
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.note{
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text-align: center;
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font-size: 16px;
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}
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p{
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font-size: 13px;
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text-align: center;
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}
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</style>
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<h3><center><b>Tomato Bacterial spot</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Copper oxychloride</li>
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<li>2. Streptomycin</li>
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<li>3. tetracycline</li>
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<li>4. Oxytetracline(Terramycin)</li>
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<li>5. Insecticidal soap</li>
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<li>6. Horticultural oil</li>
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</ul>
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<p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
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<p>Be sure to follow local regulations and guidelines for application</p>
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"""
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predicted_label = """<h3 align="center">Tomato Healthy</h3><br><br>
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<center>No need use Pesticides</center>"""
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else:
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except Exception as e:
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print(f"Error: {e}")
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return
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# List of class labels
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all_labels = [
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'Tomato Bacterial spot'
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# Define the Gradio interface
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def gradio_predict(image_file):
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# Create
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gr_interface = gr.Interface(
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fn=gradio_predict,
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inputs=
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title="Tomato Disease Predictor",
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description="Upload an image of a plant to predict the disease."
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)
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# Launch the Gradio app
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gr_interface.launch()
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import h5py
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import gradio as gr
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from tensorflow.keras.utils import img_to_array, load_img
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from keras.models import load_model
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import numpy as np
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from deep_translator import GoogleTranslator
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# Load the pre-trained model from the local path
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model_path = 'tomato.h5'
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# Check if the model is loading correctly
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try:
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with h5py.File(model_path, 'r+') as f:
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if 'groups' in f.attrs['model_config']:
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model_config_string = f.attrs['model_config']
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model_config_string = model_config_string.replace('"groups": 1,', '')
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model_config_string = model_config_string.replace('"groups": 1}', '}')
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f.attrs['model_config'] = model_config_string.encode('utf-8')
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model = load_model(model_path)
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print("Model loaded successfully.")
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except Exception as e:
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print(f"Error loading model: {e}")
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def predict_disease(image_file, model, all_labels, target_language):
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try:
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# Load and preprocess the image
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print(f"Received image file: {image_file}")
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img = load_img(image_file, target_size=(224, 224)) # Ensure image size matches model input
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img_array = img_to_array(img)
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img_array = np.expand_dims(img_array, axis=0) # Add batch dimension
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img_array = img_array / 255.0 # Normalize the image
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# Predict the class
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predictions = model.predict(img_array)
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predicted_class = np.argmax(predictions[0])
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# Get the predicted class label
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predicted_label = all_labels[predicted_class]
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# Translate the predicted label to the selected language
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translated_label = GoogleTranslator(source='en', target=target_language).translate(predicted_label)
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# Provide pesticide information based on the predicted label
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if predicted_label == 'Tomato Yellow Leaf Curl Virus':
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pesticide_info = """
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<h2><center><b>Tomato Yellow Leaf Curl Virus</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. imidacloprid</li>
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<li>2. thiamethoxam</li>
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<li>3. Spinosad</li>
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<li>4. Acetamiprid</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Target Spot':
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pesticide_info = """
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<h2><center><b>Tomato Target Spot</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Spider mites':
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pesticide_info = """
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<h2><center><b>Tomato Spider mites</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Abamectin</li>
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<li>2. Spiromesifen</li>
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<li>3. Miticides</li>
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<li>4. insecticidal soap</li>
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<li>5. Neem oil</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Septoria leaf spot':
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pesticide_info = """
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<h2><center><b>Tomato Septoria leaf spot</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Mosaic virus':
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pesticide_info = """
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<h2><center><b>Tomato Mosaic virus</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Imidacloprid</li>
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<li>2. Thiamethoxam</li>
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<li>3. Acetamiprid</li>
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<li>4. Dinotefuran</li>
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<li>5. Pyrethrin</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Leaf Mold':
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pesticide_info = """
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<h2><center><b>Tomato Leaf Mold</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Late blight':
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pesticide_info = """
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<h2><center><b>Tomato Late blight</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. metalaxl</li>
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<li>2. Chlorothalonil</li>
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<li>3. Mancozeb</li>
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<li>4. Copper oxychloride</li>
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<li>5. Azoxystrobin</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Early blight':
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pesticide_info = """
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<h2><center><b>Tomato Early blight</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Azoxystrobin</li>
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<li>2. Boscalid</li>
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<li>3. Mancozeb</li>
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<li>4. Chlorothalonil</li>
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<li>5. Propiconazole</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Bacterial spot':
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pesticide_info = """
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<h2><center><b>Tomato Bacterial spot</b></center></h2>
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<h4>PESTICIDES TO BE USED:</h4><br>
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<ul style="font-size:17px;margin-left:40px;">
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<li>1. Copper oxychloride</li>
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<li>2. Streptomycin</li>
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<li>3. tetracycline</li>
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<li>4. Oxytetracline(Terramycin)</li>
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<li>5. Insecticidal soap</li>
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<li>6. Horticultural oil</li>
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</ul><br>
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<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
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<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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"""
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elif predicted_label == 'Tomato Healthy':
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pesticide_info = """<h2><center><b>Tomato Healthy</b></center></h2>
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<h5> No pesticides needed"""
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else:
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pesticide_info = 'No pesticide information available.'
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print(f"Pesticide Info (Before Translation): {pesticide_info}")
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# Translate the pesticide information to the selected language
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translated_pesticide_info = GoogleTranslator(source='en', target=target_language).translate(pesticide_info)
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print(f"Translated Pesticide Info: {translated_pesticide_info}")
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# Return translated label and pesticide information with associated styling
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predicted_label_html = f"""
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{translated_pesticide_info}
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"""
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return predicted_label_html
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except Exception as e:
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print(f"Error during prediction: {e}")
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return f"<h3>Error: {e}</h3>"
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# List of class labels
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all_labels = [
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'Tomato Bacterial spot'
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]
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# Language codes and their full names (display full names in dropdown)
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language_choices = {
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'hi': 'Hindi',
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'te': 'Telugu',
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'en': 'English',
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'ml': 'Malayalam',
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'ta': 'Tamil',
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'bn': 'Bengali',
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'gu': 'Gujarati',
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'kn': 'Kannada',
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'mr': 'Marathi'
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}
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# Mapping full names back to their corresponding language code
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full_to_code = {value: key for key, value in language_choices.items()}
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# Create a dropdown of full language names, using the full name in the UI
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languages = list(language_choices.values()) # List of full language names
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# Define the Gradio interface
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def gradio_predict(image_file, target_language):
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# Map full name back to language code for translation
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language_code = full_to_code.get(target_language, 'en')
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return predict_disease(image_file, model, all_labels, language_code)
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# Create the Gradio interface
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gr_interface = gr.Interface(
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fn=gradio_predict,
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inputs=[
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gr.Image(type="filepath"), # Image input for disease prediction
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gr.Dropdown(label="Select language", choices=languages, value='English') # Language selection dropdown with full names
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],
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outputs="html", # Output will be in HTML (translated text)
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title="Tomato Disease Predictor",
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description="Upload an image of a plant to predict the disease and get the translated label and pesticide information in the selected language."
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)
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# Launch the Gradio app
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gr_interface.launch()
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