effdet_validation_end.py

from objdetecteval.metrics.coco_metrics import get_coco_stats

@patch
def validation_epoch_end(self: EfficientDetModel, outputs):
    """Compute and log training loss and accuracy at the epoch level."""

    validation_loss_mean = torch.stack(
        [output["loss"] for output in outputs]
    ).mean()

    (
        predicted_class_labels,
        image_ids,
        predicted_bboxes,
        predicted_class_confidences,
        targets,
    ) = self.aggregate_prediction_outputs(outputs)

    truth_image_ids = [target["image_id"].detach().item() for target in targets]
    truth_boxes = [
        target["bboxes"].detach()[:, [1, 0, 3, 2]].tolist() for target in targets
    ] # convert to xyxy for evaluation
    truth_labels = [target["labels"].detach().tolist() for target in targets]

    stats = get_coco_stats(
        prediction_image_ids=image_ids,
        predicted_class_confidences=predicted_class_confidences,
        predicted_bboxes=predicted_bboxes,
        predicted_class_labels=predicted_class_labels,
        target_image_ids=truth_image_ids,
        target_bboxes=truth_boxes,
        target_class_labels=truth_labels,
    )['All']

    return {"val_loss": validation_loss_mean, "metrics": stats}