Spaces:
Sleeping
Sleeping
| import streamlit as st | |
| from PIL import Image | |
| import model as classify | |
| import numpy as np | |
| from modules.nav import Navbar | |
| Navbar() | |
| sign_names = { | |
| 0: 'Speed limit (20km/h)', | |
| 1: 'Speed limit (30km/h)', | |
| 2: 'Speed limit (50km/h)', | |
| 3: 'Speed limit (60km/h)', | |
| 4: 'Speed limit (70km/h)', | |
| 5: 'Speed limit (80km/h)', | |
| 6: 'End of speed limit (80km/h)', | |
| 7: 'Speed limit (100km/h)', | |
| 8: 'Speed limit (120km/h)', | |
| 9: 'No passing', | |
| 10: 'No passing for vehicles over 3.5 metric tons', | |
| 11: 'Right-of-way at the next intersection', | |
| 12: 'Priority road', | |
| 13: 'Yield', | |
| 14: 'Stop', | |
| 15: 'No vehicles', | |
| 16: 'Vehicles over 3.5 metric tons prohibited', | |
| 17: 'No entry', | |
| 18: 'General caution', | |
| 19: 'Dangerous curve to the left', | |
| 20: 'Dangerous curve to the right', | |
| 21: 'Double curve', | |
| 22: 'Bumpy road', | |
| 23: 'Slippery road', | |
| 24: 'Road narrows on the right', | |
| 25: 'Road work', | |
| 26: 'Traffic signals', | |
| 27: 'Pedestrians', | |
| 28: 'Children crossing', | |
| 29: 'Bicycles crossing', | |
| 30: 'Beware of ice/snow', | |
| 31: 'Wild animals crossing', | |
| 32: 'End of all speed and passing limits', | |
| 33: 'Turn right ahead', | |
| 34: 'Turn left ahead', | |
| 35: 'Ahead only', | |
| 36: 'Go straight or right', | |
| 37: 'Go straight or left', | |
| 38: 'Keep right', | |
| 39: 'Keep left', | |
| 40: 'Roundabout mandatory', | |
| 41: 'End of no passing', | |
| 42: 'End of no passing by vehicles over 3.5 metric tons'} | |
| st.title("Traffic Sign Classifier") | |
| uploaded_file = st.file_uploader("Choose an image...", type="jpg") | |
| if uploaded_file is not None: | |
| image = Image.open(uploaded_file) | |
| st.image(image, caption='Uploaded Image', use_column_width=True) | |
| st.write("") | |
| if st.button('predict'): | |
| st.write("Result...") | |
| #label = classify.predict(uploaded_file) | |
| #label = label.item() | |
| #res = sign_names.get(label) | |
| #st.markdown(res) | |