import streamlit as st

from transformers import pipeline

pipe = pipeline("image-classification", model="ombhojane/healthyPlantsModel", backend="pytorch")

def predict_disease(image):
  """Predicts the disease of a plant from an image.

  Args:
    image: A NumPy array representing the image.

  Returns:
    A string representing the predicted disease.
  """

  prediction = pipe(image)
  label = prediction[0]["label"]
  return label

def main():
  """Creates the Streamlit app."""

  st.title("Plant Disease Detection App")

  # Upload an image
  image = st.file_uploader("Upload an image of a plant")

  # Predict the disease
  if image is not None:
    disease = predict_disease(image)

    # Display the prediction
    st.markdown(f"Predicted disease: {disease}")

if __name__ == "__main__":
  main()