Update app.py

app.py

@@ -1,14 +1,19 @@
 from transformers import pipeline
 import gradio as gr
 
+# Load image classification pipeline from Hugging Face Transformers
 image_classifier = pipeline("image-classification")
-image_path = "https://www.skinewgen.com/wp-content/uploads/20210301-New-Generation-91-2.jpg"
-result = image_classifier(image_path)
-print(result)
 
-model = gr.Interface.load("huggingface/google/vit-base-patch16-224")
+# Define a function for image classification using Gradio
+def classify_image(image_path):
+    result = image_classifier(image_path)
+    return result[0]['label']  # Return the label of the top prediction
 
-model.launch()
+# Create a Gradio interface
+iface = gr.Interface(fn=classify_image, inputs="image", outputs="text")
+
+# Launch the Gradio interface
+iface.launch()