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app.py

@@ -6,10 +6,20 @@ import numpy as np
 from PIL import Image
 import io
 import uvicorn
+import tensorflow as tf
 
-# Load model
+# Configure TensorFlow to use CPU only
+tf.config.set_visible_devices([], 'GPU')
+
+# Load model with custom_objects to handle version compatibility
 MODEL_PATH = "best_model.keras"
-model = load_model(MODEL_PATH)
+try:
+    model = load_model(MODEL_PATH, compile=False)
+except Exception as e:
+    print(f"Error loading model: {str(e)}")
+    # Try loading with custom_objects
+    model = load_model(MODEL_PATH, compile=False, custom_objects={'tf': tf})
+
 class_names = ["Early Blight", "Late Blight", "Healthy"]
 
 # Preprocess image
@@ -22,7 +32,7 @@ def preprocess(img):
     img = img.resize((256, 256))
     img_array = image.img_to_array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
-    prediction = model.predict(img_array)
+    prediction = model.predict(img_array, verbose=0)  # Added verbose=0 to reduce output
     class_index = np.argmax(prediction[0])
     return class_names[class_index]