Upload app.py

app.py

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+
+from gradio import Interface, Image, Label
+import tensorflow as tf
+# Load your TensorFlow model
+model = tf.keras.models.load_model("mango_leaf_disease_model.h5")
+
+# Define your class names if needed
+class_names = ['Anthracnose', 'Bacterial Canker', 'Cutting Weevil', 'Die Back', 'Gall Midge','Healthy','Powdery Mildew','Sooty Mould']
+
+
+# Function to make predictions
+def classify_image(image):
+    # Preprocess the image
+    img = tf.image.resize(image, (224, 224))
+    img = tf.expand_dims(img, 0)  # Add batch dimension
+    # Make prediction
+    prediction = model.predict(img)
+    predicted_class = class_names[prediction.argmax()]
+    return predicted_class
+
+# Gradio interface
+image = Image()  # Remove the `shape` argument
+label = Label()
+
+# Create interface
+interface = Interface(classify_image, image, label,
+                      title="Mango leaf disease detection",
+                      description="Upload an image of a leaf.").launch()