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()