streamlit-image-annotation 0.3.0

streamlit components for image annotation

Streamlit Image Annotation

Streamlit component for image annotation.

Features

• You can easily launch an image annotation tool using streamlit.
• By customizing the pre- and post-processing, you can achieve your preferred annotation workflow.
• Currently supports classification and detection tasks.
• Simple UI that is easy to navigate.

Install

pip install streamlit-image-annotation

Example Usage

If you want to see other use cases, please check inside the examples folder.

from glob import glob
import pandas as pd
import streamlit as st
from streamlit_image_annotation import classification

label_list = ['deer', 'human', 'dog', 'penguin', 'framingo', 'teddy bear']
image_path_list = glob('image/*.jpg')
if 'result_df' not in st.session_state:
    st.session_state['result_df'] = pd.DataFrame.from_dict({'image': image_path_list, 'label': [0]*len(image_path_list)}).copy()

num_page = st.slider('page', 0, len(image_path_list)-1, 0)
label = classification(image_path_list[num_page], 
                        label_list=label_list, 
                        default_label_index=int(st.session_state['result_df'].loc[num_page, 'label']))

if label is not None and label['label'] != st.session_state['result_df'].loc[num_page, 'label']:
    st.session_state['result_df'].loc[num_page, 'label'] = label_list.index(label['label'])
st.table(st.session_state['result_df'])

Future Work

• Refactoring of the source code.
• Addition of docs about API.
• Addition of example code.
• Addition of segmentation and point tasks.