Spaces:
Runtime error
Runtime error
| import streamlit as st | |
| import os | |
| from PIL import Image | |
| from transformers import pipeline # Hugging Face pipeline for object detection | |
| import time # To simulate a delay (for model processing) | |
| # Define the path to the folder where images are stored | |
| FIRE_SHOT_FOLDER = os.path.join(os.getcwd(), 'FireShot') | |
| # Get list of images from the FireShot folder | |
| image_files = [f for f in os.listdir(FIRE_SHOT_FOLDER) if f.endswith(('jpg', 'jpeg', 'png'))] | |
| if image_files: | |
| # Create a selectbox for the user to select an image | |
| selected_image = st.selectbox("Select an image from the FireShot folder", image_files) | |
| # Load and display the selected image | |
| if selected_image: | |
| img_path = os.path.join(FIRE_SHOT_FOLDER, selected_image) | |
| img = Image.open(img_path) | |
| st.image(img, caption=f"Selected Image: {selected_image}", use_column_width=True) | |
| # Add a button to start the object detection | |
| if st.button("Run Tree Detection"): | |
| # Show loading spinner while processing the model | |
| with st.spinner("Running YOLO model to detect trees..."): | |
| # Simulate loading time (you can remove this when using an actual model) | |
| time.sleep(3) # Simulate delay (this line can be removed) | |
| # Load YOLO model from Hugging Face | |
| model = pipeline('object-detection', model="blah-blah-treecounter") | |
| # Perform object detection on the selected image | |
| results = model(img_path) | |
| # Simulate counting trees based on the detected objects | |
| tree_count = sum(1 for obj in results if obj['label'].lower() == 'tree') | |
| # Display the results in a button to be clicked | |
| if st.button("Show Results"): | |
| st.write(f"### Detected Trees: {tree_count}") | |
| st.json(results) # Display full detection results in JSON format if needed | |
| else: | |
| st.info("No images found in FireShot folder.") | |