app.py

import streamlit as st
from tensorflow.keras.models import load_model
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

model = load_model('cnn_model.h5')

def process_image(img):
    img = img.convert('RGB')  
    img = img.resize((64, 64)) 
    img = np.array(img)  
    img = img / 255.0  
    img = np.expand_dims(img, axis=0) 
    return img

st.title('Grape Disease Detection :grapes:')
st.write('Upload a grape leaf image and the model will predict the disease category.')

file = st.file_uploader('Select an image', type=['jpg', 'jpeg', 'png'])

if file is not None:
    img = Image.open(file)
    st.image(img, caption='Uploaded Image', use_column_width=True)

    image = process_image(img)
    
    
    with st.spinner('Classifying the image...'):
        predictions = model.predict(image)
        predicted_class = np.argmax(predictions)  
        predicted_prob = predictions[0][predicted_class]  

    class_names = ['ESCA', 'Healthy', 'Leaf Blight', 'Black Rot']
    
    st.subheader(f"Prediction: {class_names[predicted_class]}")
    st.write(f"Confidence: {predicted_prob * 100:.2f}%")

    st.write("Prediction Probabilities for Each Class:")
    probabilities = predictions[0]
    
    prob_dict = {class_names[i]: probabilities[i] for i in range(len(class_names))}
    
    sns.set(style="whitegrid")
    
    fig, ax = plt.subplots(figsize=(10, 6))
    
    ax.bar(list(prob_dict.keys()), list(prob_dict.values()), color='skyblue', edgecolor='black')
    ax.set_ylabel('Probability', fontsize=14)
    ax.set_title('Prediction Probabilities for Each Class', fontsize=16)
    
    for index, value in enumerate(prob_dict.values()):
        ax.text(index, value, f'{value * 100:.2f}%', va='bottom', ha='center', color='black', fontsize=12)

    st.pyplot(fig)

    st.write("This is the model's classification of the uploaded image based on the given grape leaf disease categories.")
    
    st.markdown("""
        ### Grape Disease Categories:
        - **ESCA**: A fungal disease affecting grapevines, causing leaf and wood symptoms.
        - **Healthy**: No visible symptoms of disease.
        - **Leaf Blight**: A condition causing necrotic lesions on the leaves of grapevines.
        - **Black Rot**: A disease causing blackening and shriveling of grape berries.
    """)