updated

app.py

@@ -28,10 +28,10 @@ def predict(img):
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
 title = "EMOTIONAL DAMAGE"
-description = "A EMOTION classifier trained  with fastai. Created as a demo for Gradio and HuggingFace Spaces."
-article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
-examples = ['happylee.jpg','damu.jpeg','angry.jpeg','kili.jpg']
-interpretation='default'
-enable_queue=True
+description = "Find your true  emotions"
+article="<p style='text-align: center'><a href='https://www.linkedin.com/in/ranjith-azad-506201238/' target='_blank'>Linkedin</a></p>"
+examples = ['ha.jpg','damu.jpeg','kili.jpg','sad.jpg','fear.jpg','disg.jpg','anger.jpg']
+interpretation='default'  
+enable_queue=True 
 
 gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=5),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()