Update app.py

app.py

@@ -5,9 +5,12 @@ import tensorflow as tf
 from tensorflow.keras.preprocessing import image
 import numpy as np
 
+import gradio as gr
+from transformers import pipeline
+
+# Load image classification model from Hugging Face
+model = pipeline("image-classification", model="icputrd/gelderman_decomposition_classification/head/xception_070523")
 
-# Load your trained Xception model
-model = tf.keras.models.load_model("https://huggingface.co/icputrd/gelderman_decomposition_classification/blob/main/head/xception_070523")
 
 def classify_image(img):
     # Preprocess the image
@@ -22,7 +25,6 @@ def classify_image(img):
     
     return str(predicted_class)  # Return the class index as a string
 
-# Set up Gradio interface
-iface = gr.Interface(fn=classify_image, inputs=gr.inputs.Image(type="pil"), outputs="text")
-
-iface.launch()
+# Gradio interface for image classification
+demo = gr.Interface(fn=classify_image, inputs=gr.inputs.Image(type="pil"), outputs="label")
+demo.launch()