Spaces:
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Update app.py
Browse files
app.py
CHANGED
@@ -1,205 +1,96 @@
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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 = 'Mango.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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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>Mango Anthracrose</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Mancozeb</li>
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<li>2. Azoxystrobin</li>
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<li>3.
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<li>4. Propiconazole</li>
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<li>5. Thiophanate-methyl</li>
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<li>6. Copper Sulfate</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=='Mango Bacterial Canker':
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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>Mango Bacterial Canker</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 Hydroxide</li>
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<li>2. Copper Oxychloride</li>
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<li>3. Streptomycin</li>
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<li>4. oxytetracycline</li>
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<li>5. Neem oil</li>
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<li>6. Garlic 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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elif predicted_label=='Mango Cutting Weevil':
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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>Mango Cutting Weevil</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. Chlorpyrifos</li>
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<li>4. Lambda-cyhalothrin</li>
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<li>5. Fipronil</li>
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<li>6. 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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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>Mango Die Back</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Carbendazim</li>
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<li>2. Mancozeb</li>
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<li>3. Azoxystrobin</li>
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<li>5. Potassium bicarbonate</li>
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<li>6. Sodium bicarbonate</li>
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</ul>
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<
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<p
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"""
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elif predicted_label=='Mango Gall Midge':
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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>Mango Gall Midge</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. Chlorpyrifos</li>
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<li>5. Spinosad</li>
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<li>6. Pyrethrin</li>
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</ul>
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<p
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"""
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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>Mango Powdery Mildew</b></center></h3>
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<h4>PESTICIDES TO BE USED:</h4>
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<ul>
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<li>1. Sulfur</li>
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<li>2. Bicarbonates</li>
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<li>3. Myclobutanil</li>
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<li>5. Propiconazole</li>
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<li>6. Azoxystrobin</li>
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</ul>
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<
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<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>Mango Sooty Mould</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 (Neonicotinoid)</li>
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<li>2. Thiamethoxam (Neonicotinoid)</li>
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<li>3. Bifenthrin (Pyrethroid)</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
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"""
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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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'Mango Sooty Mould'
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]
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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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)
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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 = 'Mango.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 == 'Mango Anthracrose':
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pesticide_info = """
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<h2><center><b>Mango Anthracrose</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. Mancozeb</li>
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<li>2. Azoxystrobin</li>
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<li>3. Carbendazim</li>
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<li>4. Propiconazole</li>
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<li>5. Thiophanate-methyl</li>
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<li>6. Copper Sulfate</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 == 'Mango Bacterial Canker':
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pesticide_info = """<h2><center><b>Mango Bacterial Canker</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 Hydroxide</li>
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<li>2. Copper Oxychloride</li>
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<li>3. Streptomycin</li>
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<li>4. oxytetracycline</li>
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<li>5. Neem oil</li>
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<li>6. Garlic 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 == 'Mango Cutting Weevil':
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+
pesticide_info = """<h2><center><b>Mango Cutting Weevil</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. Chlorpyrifos</li>
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<li>4. Lambda-cyhalothrin</li>
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<li>5. Fipronil</li>
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<li>6. Neem oil</li>
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84 |
+
</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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|
88 |
|
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"""
|
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+
elif predicted_label == 'Mango Die Back':
|
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+
pesticide_info = """<h2><center><b>Mango Die Back</b></center></h2>
|
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+
<h4>PESTICIDES TO BE USED:</h4><br>
|
93 |
+
<ul style="font-size:17px;margin-left:40px;">
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94 |
<li>1. Carbendazim</li>
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<li>2. Mancozeb</li>
|
96 |
<li>3. Azoxystrobin</li>
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|
98 |
<li>5. Potassium bicarbonate</li>
|
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<li>6. Sodium bicarbonate</li>
|
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</ul>
|
101 |
+
<br>
|
102 |
+
<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
|
103 |
+
<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
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|
104 |
"""
|
105 |
+
elif predicted_label == 'Mango Gall Midge':
|
106 |
+
pesticide_info = """<h2><center><b>Mango Gall Midge</b></center></h2>
|
107 |
+
<h4>PESTICIDES TO BE USED:</h4><br>
|
108 |
+
<ul style="font-size:17px;margin-left:40px;">
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109 |
<li>1. Imidacloprid</li>
|
110 |
<li>2. Thiamethoxam</li>
|
111 |
<li>3. Chlorpyrifos</li>
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|
113 |
<li>5. Spinosad</li>
|
114 |
<li>6. Pyrethrin</li>
|
115 |
</ul>
|
116 |
+
<br>
|
117 |
+
<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
|
118 |
+
<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
|
119 |
|
120 |
|
121 |
"""
|
122 |
+
|
123 |
+
elif predicted_label == 'Mango Healthy':
|
124 |
+
pesticide_info = 'No pesticides needed'
|
125 |
+
elif predicted_label == 'Mango Powdery Mildew':
|
126 |
+
pesticide_info = """<h2><center><b>Mango Powdery Mildew</b></center></h2>
|
127 |
+
<h4>PESTICIDES TO BE USED:</h4><br>
|
128 |
+
<ul style="font-size:17px;margin-left:40px;">
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|
129 |
<li>1. Sulfur</li>
|
130 |
<li>2. Bicarbonates</li>
|
131 |
<li>3. Myclobutanil</li>
|
|
|
133 |
<li>5. Propiconazole</li>
|
134 |
<li>6. Azoxystrobin</li>
|
135 |
</ul>
|
136 |
+
<br>
|
137 |
+
<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
|
138 |
+
<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>
|
|
|
139 |
"""
|
140 |
+
elif predicted_label == 'Mango Sooty Mould':
|
141 |
+
pesticide_info = """<h2><center><b>Mango Sooty Mould</b></center></h2>
|
142 |
+
<h4>PESTICIDES TO BE USED:</h4><br>
|
143 |
+
<ul style="font-size:17px;margin-left:40px;">
|
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|
144 |
<li>1. Imidacloprid (Neonicotinoid)</li>
|
145 |
<li>2. Thiamethoxam (Neonicotinoid)</li>
|
146 |
<li>3. Bifenthrin (Pyrethroid)</li>
|
|
|
148 |
<li>5. Insecticidal soap</li>
|
149 |
<li>6. Horticultural oil</li>
|
150 |
</ul>
|
151 |
+
<br>
|
152 |
+
<center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br>
|
153 |
+
<center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center>"""
|
|
|
|
|
154 |
else:
|
155 |
+
pesticide_info = 'No pesticide information available.'
|
156 |
+
|
157 |
+
print(f"Pesticide Info (Before Translation): {pesticide_info}")
|
158 |
|
159 |
+
# Translate the pesticide information to the selected language
|
160 |
+
translated_pesticide_info = GoogleTranslator(source='en', target=target_language).translate(pesticide_info)
|
161 |
+
print(f"Translated Pesticide Info: {translated_pesticide_info}")
|
162 |
|
163 |
+
# Return translated label and pesticide information with associated styling
|
164 |
+
predicted_label_html = f"""
|
165 |
+
|
166 |
+
{translated_pesticide_info}
|
167 |
+
"""
|
168 |
+
return predicted_label_html
|
169 |
|
170 |
except Exception as e:
|
171 |
+
print(f"Error during prediction: {e}")
|
172 |
+
return f"<h3>Error: {e}</h3>"
|
173 |
|
174 |
# List of class labels
|
175 |
all_labels = [
|
|
|
183 |
'Mango Sooty Mould'
|
184 |
]
|
185 |
|
186 |
+
# Language codes and their full names (display full names in dropdown)
|
187 |
+
language_choices = {
|
188 |
+
'hi': 'Hindi',
|
189 |
+
'te': 'Telugu',
|
190 |
+
'en': 'English',
|
191 |
+
'ml': 'Malayalam',
|
192 |
+
'ta': 'Tamil',
|
193 |
+
'or': 'Odia/Odisi',
|
194 |
+
'bn': 'Bengali',
|
195 |
+
'gu': 'Gujarati',
|
196 |
+
'kn': 'Kannada',
|
197 |
+
'mr': 'Marathi'
|
198 |
+
}
|
199 |
+
|
200 |
+
# Mapping full names back to their corresponding language code
|
201 |
+
full_to_code = {value: key for key, value in language_choices.items()}
|
202 |
+
|
203 |
+
# Create a dropdown of full language names, using the full name in the UI
|
204 |
+
languages = list(language_choices.values()) # List of full language names
|
205 |
+
|
206 |
# Define the Gradio interface
|
207 |
+
def gradio_predict(image_file, target_language):
|
208 |
+
# Map full name back to language code for translation
|
209 |
+
language_code = full_to_code.get(target_language, 'en')
|
210 |
+
return predict_disease(image_file, model, all_labels, language_code)
|
211 |
|
212 |
+
# Create the Gradio interface
|
213 |
gr_interface = gr.Interface(
|
214 |
+
fn=gradio_predict,
|
215 |
+
inputs=[
|
216 |
+
gr.Image(type="filepath"), # Image input for disease prediction
|
217 |
+
gr.Dropdown(label="Select language", choices=languages, value='Choose language') # Language selection dropdown with full names
|
218 |
+
],
|
219 |
+
outputs="html", # Output will be in HTML (translated text)
|
220 |
+
title="Plant Disease Predictor",
|
221 |
+
description="Upload an image of a plant to predict the disease and get the translated label and pesticide information in the selected language."
|
222 |
)
|
223 |
|
224 |
# Launch the Gradio app
|
225 |
+
gr_interface.launch()
|