Update app.py

app.py

@@ -4,15 +4,13 @@ import json
 from streamlit_lottie import st_lottie
 from PIL import Image
 
-st.set_page_config(layout="wide")
-
 def lottiemaker(path):
     with open(path) as f:
         return json.load(f)
 
 def loadimg(path):
     img = Image.open(path)
-    img = img.resize((250,250))
+    img = img.resize((150,150))
     return img
 
 selected = option_menu(
@@ -25,7 +23,7 @@ selected = option_menu(
 if selected == 'About me':
     col1,col2 = st.columns(2)# Display the Lottie animation in the first column
     with col1:
-        st_lottie(lottiemaker('Animation - 1704777936737.json'), speed=1, width=300, height=300)
+        st_lottie(lottiemaker('Animation - 1704777936737.json'), speed=1, width=200, height=200)
     with col2:
         st.write('# Hi, I am Pallab Ghosh')
 
@@ -35,7 +33,7 @@ if selected == 'About me':
     st.write("My passion include Machine Learning, Programming, Gaming, Football, Badminton, Maths, etc")
     st.write('I am currently in High school')
     st.write('I have been learning Machine learning since 2021 and have Made more than 50 projects in the field of Machine Learning')
-
+    st.write('---')
 if selected == 'Tools and Experience':
     st.write('# Tools I use to train AI')
     col1,col2,col3,col4 = st.columns(4)
@@ -77,7 +75,35 @@ if selected == 'Tools and Experience':
         st.write("Deep Convolutional Genertive Adversarial Network")
     with col4:
         st.image(loadimg('Cyclegan.jpg'),use_column_width=False)
-        st.write("Cycle Consistent Generative Adversarial Network")    
+        st.write("Cycle Consistent Generative Adversarial Network") 
+
+    col1,col2,col3,col4 = st.columns(4)
+    with col1:
+        st.image(loadimg('pix2pix.png'),use_column_width=False)
+        st.write("Pix2Pix")
+    with col2:
+        st.image(loadimg('Yolo.jpg'),use_column_width=False)
+        st.write("Object Detection using YOLO")
+    with col3:
+        st.image(loadimg('Unet.png'),use_column_width=False)
+        st.write("Unet model for semantic segmentation")
+    with col4:
+        st.image(loadimg('segyolo.jpg'),use_column_width=False)
+        st.write("Instance Segmentation using YOLO")  
+
+    col1,col2,col3,col4 = st.columns(4)
+    with col1:
+        st.image(loadimg('Linear.png'),use_column_width=False)
+        st.write("Pix2Pix")
+    with col2:
+        st.image(loadimg('Logistic.jpg'),use_column_width=False)
+        st.write("Object Detection using YOLO")
+    with col3:
+        st.image(loadimg('naive bayes.png'),use_column_width=False)
+        st.write("Unet model for semantic segmentation")
+    with col4:
+        st.image(loadimg('DecisionTree.jpg'),use_column_width=False)
+        st.write("Instance Segmentation using YOLO")   
     
 elif selected == 'Projects':
     st.write(selected)