predict.py

import tensorflow as tf
import numpy as np
from PIL import Image
import sys

# Load the trained Keras model (adjust path as needed)
model = tf.keras.models.load_model('plantvillage_model.keras', compile=False)

# Class names matching the model output order
class_names = [
    'Pepper__bell___Bacterial_spot',
    'Pepper__bell___healthy',
    'Potato___Early_blight',
    'Potato___healthy'
]


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python predict.py <image_path>")
        sys.exit(1)
    
    image_path = sys.argv[1]
    
    try:
        image = Image.open(image_path)
    except Exception as e:
        print(f"Error opening image: {e}")
        sys.exit(1)
    
    result = predict(image)
    print("Prediction:", result)