# Copyright The PyTorch Lightning team. # # 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. from collections.abc import Sequence from typing import Literal, Union from torch import Tensor def _input_validator( preds: Sequence[dict[str, Tensor]], targets: Sequence[dict[str, Tensor]], iou_type: Union[Literal["bbox", "segm"], tuple[Literal["bbox", "segm"], ...]] = "bbox", ignore_score: bool = False, ) -> None: """Ensure the correct input format of `preds` and `targets`.""" if isinstance(iou_type, str): iou_type = (iou_type,) name_map = {"bbox": "boxes", "segm": "masks"} if any(tp not in name_map for tp in iou_type): raise Exception(f"IOU type {iou_type} is not supported") item_val_name = [name_map[tp] for tp in iou_type] if not isinstance(preds, Sequence): raise ValueError(f"Expected argument `preds` to be of type Sequence, but got {preds}") if not isinstance(targets, Sequence): raise ValueError(f"Expected argument `target` to be of type Sequence, but got {targets}") if len(preds) != len(targets): raise ValueError( f"Expected argument `preds` and `target` to have the same length, but got {len(preds)} and {len(targets)}" ) for k in [*item_val_name, "labels"] + (["scores"] if not ignore_score else []): if any(k not in p for p in preds): raise ValueError(f"Expected all dicts in `preds` to contain the `{k}` key") for k in [*item_val_name, "labels"]: if any(k not in p for p in targets): raise ValueError(f"Expected all dicts in `target` to contain the `{k}` key") for ivn in item_val_name: if not all(isinstance(pred[ivn], Tensor) for pred in preds): raise ValueError(f"Expected all {ivn} in `preds` to be of type Tensor") if not ignore_score and not all(isinstance(pred["scores"], Tensor) for pred in preds): raise ValueError("Expected all scores in `preds` to be of type Tensor") if not all(isinstance(pred["labels"], Tensor) for pred in preds): raise ValueError("Expected all labels in `preds` to be of type Tensor") for ivn in item_val_name: if not all(isinstance(target[ivn], Tensor) for target in targets): raise ValueError(f"Expected all {ivn} in `target` to be of type Tensor") if not all(isinstance(target["labels"], Tensor) for target in targets): raise ValueError("Expected all labels in `target` to be of type Tensor") for i, item in enumerate(targets): for ivn in item_val_name: if item[ivn].size(0) != item["labels"].size(0): raise ValueError( f"Input '{ivn}' and labels of sample {i} in targets have a" f" different length (expected {item[ivn].size(0)} labels, got {item['labels'].size(0)})" ) if ignore_score: return for i, item in enumerate(preds): for ivn in item_val_name: if not (item[ivn].size(0) == item["labels"].size(0) == item["scores"].size(0)): raise ValueError( f"Input '{ivn}', labels and scores of sample {i} in predictions have a" f" different length (expected {item[ivn].size(0)} labels and scores," f" got {item['labels'].size(0)} labels and {item['scores'].size(0)})" ) def _fix_empty_tensors(boxes: Tensor) -> Tensor: """Empty tensors can cause problems in DDP mode, this methods corrects them.""" if boxes.numel() == 0 and boxes.ndim == 1: return boxes.unsqueeze(0) return boxes def _validate_iou_type_arg( iou_type: Union[Literal["bbox", "segm"], tuple[Literal["bbox", "segm"], ...]] = "bbox", ) -> tuple[Literal["bbox", "segm"], ...]: """Validate that iou type argument is correct.""" allowed_iou_types = ("segm", "bbox") if isinstance(iou_type, str): iou_type = (iou_type,) if any(tp not in allowed_iou_types for tp in iou_type): raise ValueError( f"Expected argument `iou_type` to be one of {allowed_iou_types} or a tuple of, but got {iou_type}" ) return iou_type