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| import base64 | |
| import clip | |
| import io | |
| import json | |
| import os | |
| import pandas as pd | |
| from PIL import Image | |
| import streamlit as st | |
| import sys | |
| import torch | |
| import uuid | |
| from utils import get_local_files | |
| sys.path.append(os.path.dirname(os.path.abspath(__file__))) | |
| def data_annotations(): | |
| def add_annotations_dialog(selected_image): | |
| if not os.path.exists("annotations/"): | |
| os.makedirs("annotations/") | |
| annotation_project_key = st.session_state.get('annotation_project_key', None) | |
| if not annotation_project_key: | |
| annotation_project_key = str(uuid.uuid4()) | |
| st.session_state['annotation_project_key'] = annotation_project_key | |
| if not os.path.exists(f"annotations/{annotation_project_key}/"): | |
| os.makedirs(f"annotations/{annotation_project_key}/") | |
| with open(f"annotations/{annotation_project_key}/annotations.json", "w") as f: | |
| json.dump({}, f) | |
| with open(f"annotations/{annotation_project_key}/annotations.json", "r") as f: | |
| annotations_dict: dict = json.load(f) | |
| current_image_annotation = annotations_dict.get(f"images/{selected_image['file_name']}", None) | |
| if not current_image_annotation: | |
| current_image_annotation = "" | |
| st.image(f"images/{selected_image['file_name']}") | |
| annotation = st.text_area("Add Annotations", value=current_image_annotation, height=100, key="annotation_text_area") | |
| if st.button("Add Annotations", key="add_annotations_dialog"): | |
| if annotation.strip() == "" or annotation is None: | |
| st.warning("Please add annotations.") | |
| else: | |
| annotations_dict[f"images/{selected_image['file_name']}"] = annotation | |
| with open(f"annotations/{annotation_project_key}/annotations.json", "w") as f: | |
| json.dump(annotations_dict, f, indent=4) | |
| st.toast("Annotations added successfully.", icon="🎉") | |
| st.rerun() | |
| st.title("Data Annotations") | |
| files = get_local_files("images/", extensions=["jpg", "jpeg", "png"], get_details=True) | |
| if not files: | |
| st.warning("No images found in the data directory.") | |
| return | |
| st.write(f"Total {len(files)} images found in the data directory.") | |
| files_df = pd.DataFrame(files) | |
| files_df['Image'] = files_df['file_name'].apply(lambda x: f"data:image/{x.split('.')[-1]};base64,{base64.b64encode(open(f'images/{x}', 'rb').read()).decode()}") | |
| files_df = files_df[["Image", "file_name", "file_size", "file_created"]] | |
| if "annotation_project_key" in st.session_state: | |
| annotation_project_key = st.session_state['annotation_project_key'] | |
| if os.path.exists(f"annotations/{annotation_project_key}/annotations.json"): | |
| with open(f"annotations/{annotation_project_key}/annotations.json", "r") as f: | |
| annotations_dict: dict = json.load(f) | |
| files_df["Annotation"] = files_df["file_name"].apply(lambda x: annotations_dict.get(f"images/{x}", "")) | |
| event = st.dataframe(files_df, hide_index=True, use_container_width=True, column_config={"Image" : st.column_config.ImageColumn('Image', pinned=True)}, selection_mode="single-row", on_select='rerun', key="image_table") | |
| if len(event.selection['rows']): | |
| selected_image = files[event.selection['rows'][0]] | |
| add_annotations_dialog(selected_image) |