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| # 1. app.py | |
| # Main Streamlit app for UI and user interaction | |
| import streamlit as st | |
| from PIL import Image | |
| from dataset_utils import preprocess_image, DatasetHandler | |
| from model_utils import BugClassifier | |
| st.set_page_config( | |
| page_title="Bug-O-Scope 🔍🐞", | |
| page_icon="🔍", | |
| layout="wide" | |
| ) | |
| def load_model(): | |
| return BugClassifier() | |
| def main(): | |
| st.title("Bug-O-Scope 🔍🐞") | |
| st.markdown( | |
| """ | |
| Welcome to Bug-O-Scope! Upload a photo of an insect to identify it and learn about its ecological importance. | |
| """ | |
| ) | |
| st.sidebar.header("About Bug-O-Scope") | |
| st.sidebar.markdown( | |
| """ | |
| Bug-O-Scope is powered by AI to help you: | |
| - Identify insects | |
| - Learn about species | |
| - Understand their ecological roles | |
| """ | |
| ) | |
| model = load_model() | |
| tab1, tab2 = st.tabs(["Single Bug Analysis", "Bug Comparison"]) | |
| with tab1: | |
| single_bug_analysis(model) | |
| with tab2: | |
| st.markdown("Bug comparison feature coming soon!") | |
| def single_bug_analysis(model): | |
| uploaded_file = st.file_uploader("Upload a bug photo", type=['png', 'jpg', 'jpeg']) | |
| if uploaded_file: | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption="Uploaded Image", use_container_width=True) | |
| with st.spinner("Analyzing your bug..."): | |
| prediction, confidence = model.predict(image) | |
| st.success("Analysis Complete!") | |
| st.markdown(f"**Identified Species**: {prediction}") | |
| st.markdown(f"**Confidence**: {confidence:.2f}%") | |
| if prediction != "Unknown Insect": | |
| species_info = model.get_species_info(prediction) | |
| st.markdown("### About This Species") | |
| st.markdown(species_info) | |
| if __name__ == "__main__": | |
| main() |