def convert_job()

in gt_converter/convert_coco.py [0:0]

• 30 lines of code
• 8 McCabe index (conditional complexity)

    def convert_job(self, job_name, output_coco_json_path):
        """
        Converts a SageMaker Ground Truth job's manifest file to COCO format.
        :param job_name: Name of the GT job (str)
        :param output_coco_json_path: Path to write output file
        """
        job_description = self.sm_client.describe_labeling_job(LabelingJobName=job_name)
        job_state = job_description["LabelingJobStatus"]
        job_task_keywords = job_description["HumanTaskConfig"]["TaskKeywords"]

        if job_state == "Completed":
            if "Images" not in job_task_keywords and "Video" not in job_task_keywords:
                raise NotImplementedError(
                    "GT Conversion only supports image and video labeling tasks at the moment."
                )

            manifest_path = job_description["LabelingJobOutput"]["OutputDatasetS3Uri"]

            if "bounding boxes" in job_task_keywords:
                self._convert_bbox_manifest(
                    manifest_path, job_name, output_coco_json_path
                )
            elif "image segmentation" in job_task_keywords:
                self._convert_segmentation_manifest(
                    manifest_path, job_name, output_coco_json_path
                )

            elif "Video" in job_task_keywords and "tracking" in job_task_keywords:
                self._convert_video_tracking_manifest(
                    manifest_path, job_name, output_coco_json_path
                )

            else:
                raise ValueError(
                    "Could not determine the type of labeling job. Currently, Bounding Box and Semantic Segmentation are supported."
                )

        else:
            raise ValueError(
                "Job is not in `Completed` state. Currently: {}".format(job_state)
            )