Update app.py

app.py

@@ -39,15 +39,15 @@ def predict(model, labels, img):
     return flower, closeness
 
 def main():
-    st.title('Oxford 102 Flower Classification Demo')
+    st.title('Flower Classification Using Deep Learning ')
     st.markdown('### NAME:')
-    st.write('Oxford 102 Flower Classification')
+    st.write('TOLULOPE')
     st.markdown('### CLASS:')
-    st.write('Deep Learning')
+    st.write('HND2')
     st.markdown('### LEVEL:')
-    st.write('Beginner')
+    st.write('400L')
     st.markdown('---')
-    st.write("This is a demo of an image classification model trained on the Oxford 102 Flower Dataset. It can identify 102 different types of flowers. To test the model, upload an image of a flower and click the 'Run on image' button.")
+    st.write("This is a demo of an image classification model trained on the Oxford Flower Dataset. The Oxford Flower Dataset, consisting of 102 flower categories. The images have large scale, pose and light variations. In addition, there are categories that have large variations within the category and several very similar categories. The dataset is visualized using isomap with shape and colour features. Link to the dataset is available  @ https://www.kaggle.com/datasets/yousefmohamed20/oxford-102-flower-dataset.. . To test the model, upload an image of a flower and click the 'Run on image' button.")
     st.markdown('---')
     model = load_model()
     labels = load_labels()