Update app.py

app.py

@@ -5,21 +5,14 @@ from PIL import Image
 import numpy as np
 import cv2
 from huggingface_hub import from_pretrained_keras
-
-
 try:
     model=from_pretrained_keras("SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net")
 except:
     model=tf.keras.models.load_model("dental_xray_seg.h5")
     pass
-    
 st.header("Segmentation of Teeth in Panoramic X-ray Image Using UNet")
 
-examples=["107.png","108.png","109.png"]
-link='Check Out Our Github Repo ! [link](https://github.com/SerdarHelli/Segmentation-of-Teeth-in-Panoramic-X-ray-Image-Using-U-Net)'
-st.markdown(link,unsafe_allow_html=True)
-
-
+examples=["107.png"]
 def load_image(image_file):
 	img = Image.open(image_file)
 	return img
@@ -45,31 +38,14 @@ st.subheader("Upload Dental Panoramic X-ray Image Image")
 image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])
 
 
-col1, col2, col3 = st.columns(3)
+col1 = st.columns(0)
 with col1:
     ex=load_image(examples[0])
     st.image(ex,width=200)
     if st.button('Example 1'):
-        image_file=examples[0]
-
-with col2:
-    ex1=load_image(examples[1])
-    st.image(ex1,width=200)
-    if st.button('Example 2'):
-        image_file=examples[1]
-
-
-with col3:
-    ex2=load_image(examples[2])
-    st.image(ex2,width=200)
-    if st.button('Example 3'):
-        image_file=examples[2]
-    
-    
+        image_file=examples[0]  
 if image_file is not None:
-
       img=load_image(image_file)
-      
       st.text("Making A Prediction ....")
       st.image(img,width=850)