Update app.py

app.py

@@ -1,26 +1,26 @@
-# Import necessary libraries
 from transformers import pipeline
 import gradio as gr
 
-# Load a lightweight image classification model
-model = pipeline("image-classification", model="facebook/deit-tiny-patch16-224", cache_dir="./model_cache")
+# Load a lightweight pre-trained model without specifying cache_dir
+model = pipeline("image-classification", model="facebook/deit-tiny-patch16-224")
 
-# Function to classify an uploaded image
+# Function to classify an image
 def classify_image(image):
-    predictions = model(image)  # Make predictions
-    # Format predictions as a dictionary: Label -> Confidence
+    predictions = model(image)
+    # Format predictions as {label: confidence}
     return {pred["label"]: round(pred["score"], 4) for pred in predictions}
 
-# Create a Gradio interface for the app
+# Gradio interface
 interface = gr.Interface(
-    fn=classify_image,          # Function to call
-    inputs=gr.Image(type="pil"),  # Input: Image (PIL format)
-    outputs=gr.Label(),         # Output: Label with confidence scores
-    title="Image Classification App",
-    description="Upload an image, and the app will classify it using a vision transformer model."
+    fn=classify_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(),
+    title="Image Classifier Test",
+    description="Upload an image to classify."
 )
 
-# Run the app
+# Launch the app
 if __name__ == "__main__":
     interface.launch()
 
+