pathology/shared_libs/ml/inference_pipeline/inference_pubsub_message.py (47 lines of code) (raw):
# Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Pub/Sub message to be processed by inference pipeline."""
import dataclasses
import enum
import math
from typing import List, Optional, Union
import dataclasses_json
class PubSubValidationError(Exception):
pass
@dataclasses_json.dataclass_json
@dataclasses.dataclass(frozen=True)
class DicomImageRef:
dicomweb_path: str
study_instance_uid: str
series_instance_uid: str
def __post_init__(self):
if not self.dicomweb_path:
raise PubSubValidationError('Missing DICOMweb path in image ref.')
if not self.study_instance_uid:
raise PubSubValidationError('Missing study instance UID in image ref.')
if not self.series_instance_uid:
raise PubSubValidationError('Missing series instance UID in image ref.')
@dataclasses_json.dataclass_json
@dataclasses.dataclass(frozen=True)
class InferenceConfig:
"""Inference configuration."""
@dataclasses_json.dataclass_json
@dataclasses.dataclass(frozen=True)
class InferencePubSubMessage:
image_refs: List[DicomImageRef]
config: InferenceConfig
# Additional payload to pass through, not used in inference pipeline.
additional_payload: Optional[str] = None
def __post_init__(self):
if not self.image_refs:
raise PubSubValidationError('Missing image refs.')
@dataclasses_json.dataclass_json
@dataclasses.dataclass(frozen=True)
class OutputPubSubMessage:
"""Pub/Sub message output by inference pipeline, if configured."""
# Metadata for input DICOM(s) used to run inference on.
dicom_store_path: str
study_instance_uid: str
series_instance_uid: str
sop_instance_uids: List[str]
# Inference model metadata.
model_name: str
model_version: str
# Pipeline runtime metadata.
pipeline_start_time: float
pipeline_runtime: float
# Inference results.
heatmap_image_path: Optional[str]
predictions_path: Optional[str]
whole_slide_score: Optional[float]
# Additional pass-through payload from input inference pub/sub message.
additional_payload: Optional[str]