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# 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
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