Update app.py

app.py

@@ -125,8 +125,7 @@ def predict(classification_mode, image):
 
 description = """
 <center><img src="https://huggingface.co/spaces/zklee98/SolarPanelAnomaly/resolve/main/images/dronePV_picture.jpg" width=270px> </center><br>
-<center>This program identifies the type of anomaly found in solar panel using an image classification model and </center> 
-<center> the percentage of the affected area using an image segmentation model.</center><br><br><br>
+<center>This program identifies the type of anomaly found in solar panel using an image classification model and the percentage of the affected area using an image segmentation model.</center><br><br><br>
 <center> Step 1: Choose classification mode >  Step 2: Upload your image >  Step 3: Click Submit </center><br>
 <center><i><b>(Models are trained on <a href="https://ai4earthscience.github.io/iclr-2020-workshop/papers/ai4earth22.pdf">InfraredSolarModules</a> dataset, and hence expect infrared image as input)</b></i></center>
 """
@@ -141,6 +140,6 @@ gr.Interface(fn=predict,
              title='Solar Panel Anomaly Detector',
              description=description,
              examples=[['Binary Classification', '4849.jpg'], ['Multiclass Classification', '4849.jpg'], 
-                       ['Binary Classification', '7016.jpg'], ['Multiclass Classification', '8211.jpg']],
+                       ['Binary Classification', '7016.jpg'], ['Multiclass Classification', '/images/10000.jpg']],
              cache_examples= False,
              article= '<center>by <a href="https://www.linkedin.com/in/lzk/">Lee Zhe Kaai</a></center>').launch()