Update app.py

app.py

@@ -1,22 +1,37 @@
 import streamlit as st
+
 from transformers import pipeline
 
-# Load the Hugging Face model
-model = pipeline("image-classification", model="models/ombhojane/healthyPlantsModel")
+pipe = pipeline("image-classification", model="ombhojane/healthyPlantsModel")
+
+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."""
 
-# Create a Streamlit app
-st.title("Plant Disease Detection")
+  st.title("Plant Disease Detection App")
 
-# Add a file uploader to allow the user to upload an image
-uploaded_file = st.file_uploader("Upload an image of your plant")
+  # Upload an image
+  image = st.file_uploader("Upload an image of a plant")
 
-# If the user has uploaded an image, make a prediction
-if uploaded_file is not None:
-    prediction = model(uploaded_file)
+  # Predict the disease
+  if image is not None:
+    disease = predict_disease(image)
 
     # Display the prediction
-    st.write("Prediction:")
-    st.text(prediction[0]["label"])
+    st.markdown(f"Predicted disease: {disease}")
 
-else:
-    st.write("Please upload an image of your plant")
+if __name__ == "__main__":
+  main()