| import tensorflow as tf | |
| model=tf.keras.models.load_model('model.h5') | |
| import streamlit as st | |
| st.header("Wonderful Wonders Classification") | |
| st.markdown("This model takes in the image input of any wonder of the world and tries to classify it.") | |
| categories=['Roman Colosseum', | |
| 'Stonehenge', | |
| 'Machu Pichu', | |
| 'Chichen Itza', | |
| 'Christ The Reedemer', | |
| 'Eiffel Tower', | |
| 'Taj Mahal', | |
| 'Pyramids Of Giza', | |
| 'Statue of Liberty', | |
| 'Burj Khalifa', | |
| 'Venezuela Angel Falls', | |
| 'Great Wall of China'] | |
| from PIL import Image | |
| uploaded_image=st.file_uploader("Upload image",type=["jpg","jpeg","webp"]) | |
| import numpy as np | |
| import cv2 | |
| if(uploaded_image!=None): | |
| display_image=Image.open(uploaded_image) | |
| st.image(display_image,width=200) | |
| if st.button("Predict"): | |
| img = np.array(display_image) | |
| img=cv2.resize(img,(150,150)) | |
| img=img/255.0 | |
| img=img.reshape(1,150,150,3) | |
| pred=model.predict(img) | |
| print(pred[0][0]) | |
| st.text(categories[np.argmax(pred)]) | |