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| import h5py | |
| import gradio as gr | |
| from tensorflow.keras.utils import img_to_array, load_img | |
| from keras.models import load_model | |
| import numpy as np | |
| from deep_translator import GoogleTranslator | |
| # Load the pre-trained model from the local path | |
| model_path = 'tomato.h5' | |
| # Check if the model is loading correctly | |
| try: | |
| with h5py.File(model_path, 'r+') as f: | |
| if 'groups' in f.attrs['model_config']: | |
| model_config_string = f.attrs['model_config'] | |
| model_config_string = model_config_string.replace('"groups": 1,', '') | |
| model_config_string = model_config_string.replace('"groups": 1}', '}') | |
| f.attrs['model_config'] = model_config_string.encode('utf-8') | |
| model = load_model(model_path) | |
| print("Model loaded successfully.") | |
| except Exception as e: | |
| print(f"Error loading model: {e}") | |
| def predict_disease(image_file, model, all_labels, target_language): | |
| try: | |
| # Load and preprocess the image | |
| print(f"Received image file: {image_file}") | |
| img = load_img(image_file, target_size=(224, 224)) # Ensure image size matches model input | |
| img_array = img_to_array(img) | |
| img_array = np.expand_dims(img_array, axis=0) # Add batch dimension | |
| img_array = img_array / 255.0 # Normalize the image | |
| # Predict the class | |
| predictions = model.predict(img_array) | |
| # Validate predictions | |
| confidence_threshold = 0.7 # Require at least 98% confidence | |
| confidence_scores = predictions[0] | |
| max_confidence = np.max(confidence_scores) | |
| if max_confidence < confidence_threshold: | |
| print(f"Prediction confidence ({max_confidence:.2f}) is too low.") | |
| return f""" | |
| <h3 style="color:red; text-align:center;"> | |
| Please upload a clearer image of the plant. | |
| </h3> | |
| """ | |
| predicted_class = np.argmax(predictions[0]) | |
| # Get the predicted class label | |
| predicted_label = all_labels[predicted_class] | |
| # Translate the predicted label to the selected language | |
| translated_label = GoogleTranslator(source='en', target=target_language).translate(predicted_label) | |
| # Provide pesticide information based on the predicted label | |
| if predicted_label == 'Tomato Yellow Leaf Curl Virus': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Yellow Leaf Curl Virus</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. imidacloprid</li> | |
| <li>2. thiamethoxam</li> | |
| <li>3. Spinosad</li> | |
| <li>4. Acetamiprid</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Target Spot': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Target Spot</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Azoxystrobin</li> | |
| <li>2. Boscalid</li> | |
| <li>3. Mancozeb</li> | |
| <li>4. Chlorothalonil</li> | |
| <li>5. Propiconazole</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Spider mites': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Spider mites</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Abamectin</li> | |
| <li>2. Spiromesifen</li> | |
| <li>3. Miticides</li> | |
| <li>4. insecticidal soap</li> | |
| <li>5. Neem oil</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Septoria leaf spot': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Septoria leaf spot</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Azoxystrobin</li> | |
| <li>2. Boscalid</li> | |
| <li>3. Mancozeb</li> | |
| <li>4. Chlorothalonil</li> | |
| <li>5. Propiconazole</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Mosaic virus': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Mosaic virus</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Imidacloprid</li> | |
| <li>2. Thiamethoxam</li> | |
| <li>3. Acetamiprid</li> | |
| <li>4. Dinotefuran</li> | |
| <li>5. Pyrethrin</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Leaf Mold': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Leaf Mold</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Azoxystrobin</li> | |
| <li>2. Boscalid</li> | |
| <li>3. Mancozeb</li> | |
| <li>4. Chlorothalonil</li> | |
| <li>5. Propiconazole</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Late blight': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Late blight</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. metalaxl</li> | |
| <li>2. Chlorothalonil</li> | |
| <li>3. Mancozeb</li> | |
| <li>4. Copper oxychloride</li> | |
| <li>5. Azoxystrobin</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Early blight': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Early blight</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <li>1. Azoxystrobin</li> | |
| <li>2. Boscalid</li> | |
| <li>3. Mancozeb</li> | |
| <li>4. Chlorothalonil</li> | |
| <li>5. Propiconazole</li> | |
| </ul><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Bacterial spot': | |
| pesticide_info = """ | |
| <h2><center><b>Tomato Bacterial spot</b></center></h2> | |
| <h4>PESTICIDES TO BE USED:</h4><br> | |
| <ul style="font-size:17px;margin-left:40px;"> | |
| <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><br> | |
| <center><p class="note" style="font-size:15px;"><b>* * * IMPORTANT NOTE * * *</b></p></center><br> | |
| <center><p style="font-size:13px;">Be sure to follow local regulations and guidelines for application</p></center> | |
| """ | |
| elif predicted_label == 'Tomato Healthy': | |
| pesticide_info = """<h2><center><b>Tomato Healthy</b></center></h2> | |
| <h5> No pesticides needed""" | |
| else: | |
| pesticide_info = 'No pesticide information available.' | |
| print(f"Pesticide Info (Before Translation): {pesticide_info}") | |
| # Translate the pesticide information to the selected language | |
| translated_pesticide_info = GoogleTranslator(source='en', target=target_language).translate(pesticide_info) | |
| print(f"Translated Pesticide Info: {translated_pesticide_info}") | |
| # Return translated label and pesticide information with associated styling | |
| predicted_label_html = f""" | |
| {translated_pesticide_info} | |
| """ | |
| return predicted_label_html | |
| except Exception as e: | |
| print(f"Error during prediction: {e}") | |
| return f"<h3>Error: {e}</h3>" | |
| # List of class labels | |
| all_labels = [ | |
| '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' | |
| ] | |
| # Language codes and their full names (display full names in dropdown) | |
| language_choices = { | |
| 'hi': 'Hindi', | |
| 'te': 'Telugu', | |
| 'en': 'English', | |
| 'ml': 'Malayalam', | |
| 'ta': 'Tamil', | |
| 'bn': 'Bengali', | |
| 'gu': 'Gujarati', | |
| 'kn': 'Kannada', | |
| 'mr': 'Marathi' | |
| } | |
| # Mapping full names back to their corresponding language code | |
| full_to_code = {value: key for key, value in language_choices.items()} | |
| # Create a dropdown of full language names, using the full name in the UI | |
| languages = list(language_choices.values()) # List of full language names | |
| # Define the Gradio interface | |
| def gradio_predict(image_file, target_language): | |
| # Map full name back to language code for translation | |
| language_code = full_to_code.get(target_language, 'en') | |
| return predict_disease(image_file, model, all_labels, language_code) | |
| # Create the Gradio interface | |
| gr_interface = gr.Interface( | |
| fn=gradio_predict, | |
| inputs=[ | |
| gr.Image(type="filepath"), # Image input for disease prediction | |
| gr.Dropdown(label="Select language", choices=languages, value='English') # Language selection dropdown with full names | |
| ], | |
| outputs="html", # Output will be in HTML (translated text) | |
| title="Tomato Disease Predictor", | |
| description="Upload an image of a plant to predict the disease and get the translated label and pesticide information in the selected language." | |
| ) | |
| # Launch the Gradio app | |
| gr_interface.launch() | |