| import time | |
| import streamlit as st | |
| from PIL import Image, ImageOps | |
| from src import big_cat_classifier | |
| def main(): | |
| st.set_page_config( | |
| page_title="Big Cat Classifier", | |
| layout="centered", | |
| initial_sidebar_state="collapsed", | |
| ) | |
| banner_img = Image.open("./assets/banner_img.png") | |
| st.image(banner_img) | |
| st.title("Coded with ❤️ by Smaranjit Ghose") | |
| st.text("") | |
| st.text("") | |
| st.text("") | |
| uploaded_file = st.file_uploader("Choose an image..", type=["jpg", "png", "jpeg"]) | |
| if st.button("Predict"): | |
| if uploaded_file is not None: | |
| try: | |
| img = Image.open(uploaded_file) | |
| st.subheader("Your Image:") | |
| st.image(img) | |
| st.write("") | |
| st.write("") | |
| with st.spinner("Our AI forest officer has started analyzing...."): | |
| label = big_cat_classifier.classifier(uploaded_file) | |
| time.sleep(5) | |
| st.success(f"We think this is an image of a {label}") | |
| except: | |
| st.error("We apologize something went wrong 🙇🏽♂️") | |
| else: | |
| st.error("Can you please upload an image 🙇🏽♂️") | |
| if __name__ == "__main__": | |
| main() | |