Update app.py

app.py

@@ -7,7 +7,7 @@ from PIL import Image
 model = tf.keras.models.load_model('Nutrient-Model.h5')
 
 # Define the class names
-class_names = ['Iron', 'Magnesium', 'Nitrogen', 'Potassium', 'Zinc']
+class_names = ['Magnesium','Nitrogen','Potassium','Phosphorus','Sulfur','Calcium']
 
 # Function to classify the image
 def classify_image(image):
@@ -41,7 +41,7 @@ def classify_image(image):
 # Define the Gradio interface
 inputs = gr.inputs.Image()
 outputs = gr.outputs.Textbox()
-interface = gr.Interface(fn=classify_image, inputs=inputs, outputs=outputs, title="Image Classification", description="Classify an image into one of five classes: Iron, Magnesium, Nitrogen, Potassium, or Zinc.")
+interface = gr.Interface(fn=classify_image, inputs=inputs, outputs=outputs, title="Image Classification", description="Classify an image into one of five classes: Phosphorus, Magnesium, Nitrogen, Potassium, Calcium,Sulfur.")
 
 # Launch the interface
 interface.launch()