Update app.py

app.py

@@ -74,14 +74,23 @@ def predict_emotion(image):
     emotion = idx2label[predicted]
     emoji = emotion_emoji.get(emotion, "❓")  # Default to "?" if no emoji found
     return f"{emotion} {emoji}"
-    
+
+# Example images (provide local file paths or URLs)
+example_images = [
+    "https://img.freepik.com/free-photo/emotive-excited-female-with-dark-skin-crisp-hair-keeps-hands-clenched-fists-exclaims-with-positiveness-as-achieved-success-her-career-opens-mouth-widely-isolated-white-wall_273609-16443.jpg",
+    "https://t4.ftcdn.net/jpg/01/18/44/59/360_F_118445958_NtP7tIsD0CBPyG7Uad7Z2KxVWrsfCPjP.jpg", 
+    "https://apnapestcontrol.ca/wp-content/uploads/2019/02/9.jpg",  
+    "https://images.pexels.com/photos/1107717/pexels-photo-1107717.jpeg?cs=srgb&dl=pexels-fotios-photos-1107717.jpg&fm=jpg"
+]
+
 # Create Gradio interface
 iface = gr.Interface(
     fn=predict_emotion,
-    inputs=gr.Image(type="pil", label="Upload an Image"),  # Updated line
-    outputs=gr.Textbox(label="Emotion"),  # Updated line
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.Textbox(label="Emotion"),
     title="PerceptCLIP-Emotions",
-    description="This model predicts the emotion evoked by an image and returns the corresponding emoji along with the emotion name."
+    description="This model predicts the emotion evoked by an image and returns the corresponding emoji along with the emotion name.",
+    examples=example_images  # Add example images here
 )
 
 if __name__ == "__main__":