Update app.py

app.py

@@ -1,6 +1,6 @@
 # Available backend options are: "jax", "torch", "tensorflow".
 import os
-os.environ["KERAS_BACKEND"] = "tensorflow"
+#os.environ["KERAS_BACKEND"] = "tensorflow"
 #pip install -U keras huggingface_hub
 
 #import keras
@@ -13,7 +13,7 @@ import numpy as np
 from PIL import Image
 
 # Load the model
-@st.cache_resource
+#@st.cache_resource
 def load_model():
     model = tf.keras.models.load_model("cassava_leaf_disease_model.keras") #tf.keras.saving.load_model("hf://Fluospark128/Cassava_Disease_Classifier") cassava_model.h5
     return model
@@ -24,8 +24,8 @@ model = load_model()
 CLASS_NAMES = ["Cassava Bacterial Blight Disease", "Cassava Brown Streak Disease", "Cassava Green Mottle Disease",  "Cassava Mosaic Disease", "Healthy"]
 
 # Streamlit UI
-st.title("Cassava Leaf Disease Classifier")
-st.write("Upload an image of a cassava leaf to classify its disease.")
+st.title("Cassava Leaf Disease Identifier")
+st.write("Upload an image of a cassava leaf to identify its disease.")
 
 # File uploader
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])