design

app.py

@@ -13,9 +13,8 @@ def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-title = "<div style='text-align:center;width:100%;display:flex;justify-content:space-evenly'> <div style='color:#ff5a06'> Rock Classifier</div><div style='padding-lef:10%;font-size:small'><a href='https://in.linkedin.com/in/amrutha-kp' target='_blank'>Amrutha KP</a></div></div>"
+title = "<div style='text-align:center;width:100%;display:flex;flex-direction:column;justify-content:space-evenly'> <div style='color:#ff5a06'> Rock Classifier</div><div style='padding-left:10%;font-size:small'><a href='https://in.linkedin.com/in/amrutha-kp' target='_blank'>Amrutha KP</a></div></div>"
 examples = ["basalt.jpeg","coal.jpeg","granite.jpeg", "limestone1.jpg","marble1.jpeg","quartzite.jpeg","sandstone4.jpeg"]
 description = "Rock classification using convolutional neural networks results may not be accurate since trained on small dataset"
-article="<p style='text-align: center'><a href='https://in.linkedin.com/in/amrutha-kp' target='_blank'>Linkedin</a></p>"
 
 gr.Interface(fn=predict, inputs=gr.Image(), outputs=gr.Label(num_top_classes=7),title = title,examples= examples,article=article,description=description).launch(share=True)