Files
visual-semiotic-ai-analysis/scripts/sync_label_studio_annotations.py
Brian Bjarke Jensen b6b35448b0
Code Quality Pipeline / code-quality (pull_request) Successful in 37s
Test Python Package / test (pull_request) Successful in 31s
code quality fixes
2025-09-18 23:50:36 +02:00

130 lines
5.4 KiB
Python

"""Script to convert Label Studio output JSON files to an Annotation."""
import json
from uuid import UUID
from dotenv import load_dotenv
from python_repositories.adapters import MinioAdapter
from data_store.dto import Annotation
from data_store.repositories import AnnotationRepository
def list_label_studio_output_files(minio_adapter: MinioAdapter) -> list[str]:
"""List the Label Studio output files in MinIO."""
# Check input
if not isinstance(minio_adapter, MinioAdapter):
raise ValueError("minio_adapter must be an instance of MinioAdapter")
if not minio_adapter.is_connected:
raise ConnectionError("minio_adapter must be connected to MinIO")
# List objects with the Label Studio output prefix
prefix = "label-studio-output/"
return minio_adapter._list_objects(prefix)
def get_label_studio_output(minio_adapter: MinioAdapter, object_name: str) -> dict:
"""Get a Label Studio output file from MinIO."""
# Check input
if not isinstance(minio_adapter, MinioAdapter):
raise ValueError("minio_adapter must be an instance of MinioAdapter")
if not minio_adapter.is_connected:
raise ConnectionError("minio_adapter must be connected to MinIO")
if not isinstance(object_name, str) or len(object_name) == 0:
raise ValueError("object_name must be a non-empty string")
# Get object from MinIO
buffer = minio_adapter._get(object_name)
if buffer is None:
raise FileNotFoundError(f"File not found in MinIO: {object_name}")
# Convert buffer to JSON
data: dict = json.load(buffer)
return data
def convert_label_studio_output(label_studio_output: dict) -> tuple[Annotation, UUID]:
"""Convert Label Studio output to Annotation and corresponding job ID."""
# Check input
if not isinstance(label_studio_output, dict):
raise ValueError("label_studio_output must be a dictionary")
# Extract job id
image_path = label_studio_output["task"]["data"]["image"]
job_id_str = image_path.rsplit("/")[-1].split(".")[0]
job_id = UUID(job_id_str)
# Extract relevant information from the Label Studio output
annotation_data: dict[str, str | None | bool] = {}
for elem in label_studio_output["result"]:
# Extract key and value
key = elem["from_name"]
choices = elem["value"]["choices"]
# Check for presence of uncertainty flag
uncertainty_key = f"{key}_uncertainty"
uncertainty_value = bool("uncertain" in choices)
if uncertainty_value:
choices.remove("uncertain")
# If no choices left, set to None
value: str | None = choices[0] if choices else None
# Store in annotation data
annotation_data[key] = value
annotation_data[uncertainty_key] = uncertainty_value
# Create the Annotation object
annotation = Annotation(**annotation_data) # type: ignore[arg-type]
return annotation, job_id
def sync_label_studio_annotations(
minio_adapter: MinioAdapter,
annotation_repository: AnnotationRepository,
) -> None:
"""Sync Label Studio output files to AnnotationRepository."""
# Check inputs
if not isinstance(minio_adapter, MinioAdapter):
raise ValueError("minio_adapter must be an instance of MinioAdapter")
if not minio_adapter.is_connected:
raise ConnectionError("minio_adapter must be connected to MinIO")
if not isinstance(annotation_repository, AnnotationRepository):
raise ValueError(
"annotation_repository must be an instance of AnnotationRepository"
)
if not annotation_repository.is_connected:
raise ConnectionError("annotation_repository must be connected to MinIO")
# List annotations in repository
annotation_ids = annotation_repository.list_all()
print(f"Found {len(annotation_ids)} annotations in repository.")
# Count Label Studio output files
label_studio_files = list_label_studio_output_files(minio_adapter)
print(f"Found {len(label_studio_files)} Label Studio output files.")
# Stop early if equal number of annotations and Label Studio files
if len(annotation_ids) == len(label_studio_files):
print("No new Label Studio output files to process. Exiting.")
return
# Process each Label Studio output file
for file_name in label_studio_files:
print(f"Processing file: {file_name}")
# Get Label Studio output
try:
label_studio_output = get_label_studio_output(
minio_adapter,
file_name,
)
except Exception as exc:
print(f"Failed to get Label Studio output for {file_name}: {exc}")
continue
# Convert to Annotation
try:
annotation, job_id = convert_label_studio_output(label_studio_output)
except Exception as exc:
print(f"Failed to convert Label Studio output for {file_name}: {exc}")
continue
# Store Annotation in repository
try:
annotation_repository.put(annotation, job_id)
except Exception as exc:
print(f"Failed to store annotation for {file_name}: {exc}")
continue
print(f"Successfully processed and stored annotation for {file_name}.")
if __name__ == "__main__":
# Load environment variables from .env file
load_dotenv()
# Connect to data sources
with MinioAdapter() as minio_adapter, AnnotationRepository() as annotation_repo:
sync_label_studio_annotations(minio_adapter, annotation_repo)