Update app.py

app.py

@@ -3,35 +3,12 @@ import numpy as np
 import tensorflow as tf
 from tensorflow.keras.models import load_model
 from PIL import Image
-import requests
-import tempfile
 import os
 
-def download_model_from_gdrive():
-    """Downloads the model from Google Drive."""
-    gdrive_url = "https://drive.google.com/uc?id=1EnokggrC6ymrSibtj2t7IHWb9QVtrehS"
-    output_path = "final_meta_model.keras"
-
-    with requests.get(gdrive_url, stream=True) as r:
-        r.raise_for_status()
-        with open(output_path, "wb") as f:
-            for chunk in r.iter_content(chunk_size=8192):
-                f.write(chunk)
-
-    return output_path
-
-def load_or_download_model():
-    """Loads the model from Hugging Face or Google Drive."""
-    hf_model_path = "final_meta_model.keras"
-
-    # Check if model exists locally (from Hugging Face Space storage)
-    if os.path.exists(hf_model_path):
-        model = load_model(hf_model_path)
-    else:
-        st.write("Model not found locally. Downloading from Google Drive...")
-        model_path = download_model_from_gdrive()
-        model = load_model(model_path)
-
+def load_model_from_huggingface():
+    """Loads the model from Hugging Face Hub."""
+    from huggingface_hub import from_pretrained_keras
+    model = from_pretrained_keras("shaheer-data/Yellow-Rust-Prediction")
     return model
 
 def preprocess_image(image):
@@ -61,7 +38,7 @@ if uploaded_image:
 
     # Load model
     with st.spinner("Loading model..."):
-        model = load_or_download_model()
+        model = load_model_from_huggingface()
 
     # Preprocess image
     image = Image.open(uploaded_image)