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Replace reduce_labels with do_reduce_labels (#21218)

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* Replace reduce_labels with do_reduce_labels

* Replace only for __init__ and preprocess

* Update tests
This commit is contained in:
amyeroberts
2023-01-23 17:21:33 +00:00
committed by GitHub
parent 1eda4a4102
commit 354ea44340
5 changed files with 75 additions and 29 deletions
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46
src/transformers/models/maskformer/image_processing_maskformer.py
View File

@@ -373,7 +373,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
ignore_index (`int`, *optional*):
Label to be assigned to background pixels in segmentation maps. If provided, segmentation map pixels
denoted with 0 (background) will be replaced with `ignore_index`.
reduce_labels (`bool`, *optional*, defaults to `False`):
do_reduce_labels (`bool`, *optional*, defaults to `False`):
Whether or not to decrement all label values of segmentation maps by 1. Usually used for datasets where 0
is used for background, and background itself is not included in all classes of a dataset (e.g. ADE20k).
The background label will be replaced by `ignore_index`.
@@ -394,7 +394,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
image_mean: Union[float, List[float]] = None,
image_std: Union[float, List[float]] = None,
ignore_index: Optional[int] = None,
reduce_labels: bool = False,
do_reduce_labels: bool = False,
**kwargs
):
if "size_divisibility" in kwargs:
@@ -415,6 +415,13 @@ class MaskFormerImageProcessor(BaseImageProcessor):
self._max_size = kwargs.pop("max_size")
else:
self._max_size = 1333
if "reduce_labels" in kwargs:
warnings.warn(
"The `reduce_labels` argument is deprecated and will be removed in v4.27. Please use "
"`do_reduce_labels` instead.",
FutureWarning,
)
do_reduce_labels = kwargs.pop("reduce_labels")
size = size if size is not None else {"shortest_edge": 800, "longest_edge": self._max_size}
size = get_size_dict(size, max_size=self._max_size, default_to_square=False)
@@ -430,7 +437,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else IMAGENET_DEFAULT_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.ignore_index = ignore_index
self.reduce_labels = reduce_labels
self.do_reduce_labels = do_reduce_labels
@classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
@@ -463,6 +470,15 @@ class MaskFormerImageProcessor(BaseImageProcessor):
)
return self.size["longest_edge"]
@property
def reduce_labels(self):
warnings.warn(
"The `reduce_labels` property is deprecated and will be removed in v4.27. Please use "
"`do_reduce_labels` instead.",
FutureWarning,
)
return self.do_reduce_labels
def resize(
self,
image: np.ndarray,
@@ -532,6 +548,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
instance_id_to_semantic_id: Optional[Dict[int, int]] = None,
ignore_index: Optional[int] = None,
reduce_labels: bool = False,
**kwargs
):
reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
ignore_index = ignore_index if ignore_index is not None else self.ignore_index
@@ -645,16 +662,26 @@ class MaskFormerImageProcessor(BaseImageProcessor):
image_mean: Optional[Union[float, List[float]]] = None,
image_std: Optional[Union[float, List[float]]] = None,
ignore_index: Optional[int] = None,
reduce_labels: Optional[bool] = None,
do_reduce_labels: Optional[bool] = None,
return_tensors: Optional[Union[str, TensorType]] = None,
data_format: Union[str, ChannelDimension] = ChannelDimension.FIRST,
**kwargs
) -> BatchFeature:
if "pad_and_return_pixel_mask" in kwargs:
warnings.warn(
"The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version",
"The `pad_and_return_pixel_mask` argument is deprecated and will be removed in v4.27",
FutureWarning,
)
if "reduce_labels" in kwargs:
warnings.warn(
"The `reduce_labels` argument is deprecated and will be removed in v4.27. Please use"
" `do_reduce_labels` instead.",
FutureWarning,
)
if do_reduce_labels is not None:
raise ValueError(
"Cannot use both `reduce_labels` and `do_reduce_labels`. Please use `do_reduce_labels` instead."
)
do_resize = do_resize if do_resize is not None else self.do_resize
size = size if size is not None else self.size
@@ -667,7 +694,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
image_mean = image_mean if image_mean is not None else self.image_mean
image_std = image_std if image_std is not None else self.image_std
ignore_index = ignore_index if ignore_index is not None else self.ignore_index
reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
do_reduce_labels = do_reduce_labels if do_reduce_labels is not None else self.do_reduce_labels
if do_resize is not None and size is None or size_divisor is None:
raise ValueError("If `do_resize` is True, `size` and `size_divisor` must be provided.")
@@ -720,7 +747,7 @@ class MaskFormerImageProcessor(BaseImageProcessor):
for segmentation_map in segmentation_maps
]
encoded_inputs = self.encode_inputs(
images, segmentation_maps, instance_id_to_semantic_id, ignore_index, reduce_labels, return_tensors
images, segmentation_maps, instance_id_to_semantic_id, ignore_index, do_reduce_labels, return_tensors
)
return encoded_inputs
@@ -842,13 +869,12 @@ class MaskFormerImageProcessor(BaseImageProcessor):
`annotations` are provided). They identify the labels of `mask_labels`, e.g. the label of
`mask_labels[i][j]` if `class_labels[i][j]`.
"""
ignore_index = self.ignore_index if ignore_index is None else ignore_index
reduce_labels = self.reduce_labels if reduce_labels is None else reduce_labels
if "pad_and_return_pixel_mask" in kwargs:
warnings.warn(
"The `pad_and_return_pixel_mask` argument has no effect and will be removed in v4.27", FutureWarning
)
ignore_index = self.ignore_index if ignore_index is None else ignore_index
reduce_labels = self.do_reduce_labels if reduce_labels is None else reduce_labels
pixel_values_list = [to_numpy_array(pixel_values) for pixel_values in pixel_values_list]
encoded_inputs = self.pad(pixel_values_list, return_tensors=return_tensors)

40
src/transformers/models/oneformer/image_processing_oneformer.py
View File

@@ -373,7 +373,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
ignore_index (`int`, *optional*):
Label to be assigned to background pixels in segmentation maps. If provided, segmentation map pixels
denoted with 0 (background) will be replaced with `ignore_index`.
reduce_labels (`bool`, *optional*, defaults to `False`):
do_reduce_labels (`bool`, *optional*, defaults to `False`):
Whether or not to decrement all label values of segmentation maps by 1. Usually used for datasets where 0
is used for background, and background itself is not included in all classes of a dataset (e.g. ADE20k).
The background label will be replaced by `ignore_index`.
@@ -399,7 +399,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
image_mean: Union[float, List[float]] = None,
image_std: Union[float, List[float]] = None,
ignore_index: Optional[int] = None,
reduce_labels: bool = False,
do_reduce_labels: bool = False,
repo_path: str = "shi-labs/oneformer_demo",
class_info_file: str = None,
num_text: Optional[int] = None,
@@ -413,6 +413,14 @@ class OneFormerImageProcessor(BaseImageProcessor):
size = size if size is not None else {"shortest_edge": 800, "longest_edge": self._max_size}
size = get_size_dict(size, max_size=self._max_size, default_to_square=False)
if "reduce_labels" in kwargs:
warnings.warn(
"The `reduce_labels` argument is deprecated and will be removed in v4.27. "
"Please use `do_reduce_labels` instead.",
FutureWarning,
)
do_reduce_labels = kwargs.pop("reduce_labels")
super().__init__(**kwargs)
self.do_resize = do_resize
self.size = size
@@ -423,7 +431,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
self.image_mean = image_mean if image_mean is not None else IMAGENET_DEFAULT_MEAN
self.image_std = image_std if image_std is not None else IMAGENET_DEFAULT_STD
self.ignore_index = ignore_index
self.reduce_labels = reduce_labels
self.do_reduce_labels = do_reduce_labels
self.class_info_file = class_info_file
self.repo_path = repo_path
self.metadata = prepare_metadata(repo_path, class_info_file)
@@ -499,6 +507,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
instance_id_to_semantic_id: Optional[Dict[int, int]] = None,
ignore_index: Optional[int] = None,
reduce_labels: bool = False,
**kwargs
):
reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
ignore_index = ignore_index if ignore_index is not None else self.ignore_index
@@ -607,16 +616,28 @@ class OneFormerImageProcessor(BaseImageProcessor):
image_mean: Optional[Union[float, List[float]]] = None,
image_std: Optional[Union[float, List[float]]] = None,
ignore_index: Optional[int] = None,
reduce_labels: Optional[bool] = None,
do_reduce_labels: Optional[bool] = None,
return_tensors: Optional[Union[str, TensorType]] = None,
data_format: Union[str, ChannelDimension] = ChannelDimension.FIRST,
**kwargs
) -> BatchFeature:
if "pad_and_return_pixel_mask" in kwargs:
warnings.warn(
"The `pad_and_return_pixel_mask` argument is deprecated and will be removed in a future version",
"The `pad_and_return_pixel_mask` argument is deprecated and will be removed in v4.27",
FutureWarning,
)
if "reduce_labels" in kwargs:
warnings.warn(
"The `reduce_labels` argument is deprecated and will be removed in a v4.27. Please use"
" `do_reduce_labels` instead.",
FutureWarning,
)
if do_reduce_labels is not None:
raise ValueError(
"You cannot use both `reduce_labels` and `do_reduce_labels` arguments. Please use"
" `do_reduce_labels` instead."
)
do_reduce_labels = kwargs.pop("reduce_labels")
do_resize = do_resize if do_resize is not None else self.do_resize
size = size if size is not None else self.size
@@ -628,7 +649,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
image_mean = image_mean if image_mean is not None else self.image_mean
image_std = image_std if image_std is not None else self.image_std
ignore_index = ignore_index if ignore_index is not None else self.ignore_index
reduce_labels = reduce_labels if reduce_labels is not None else self.reduce_labels
do_reduce_labels = do_reduce_labels if do_reduce_labels is not None else self.do_reduce_labels
if do_resize is not None and size is None:
raise ValueError("If `do_resize` is True, `size` must be provided.")
@@ -684,7 +705,7 @@ class OneFormerImageProcessor(BaseImageProcessor):
segmentation_maps,
instance_id_to_semantic_id,
ignore_index,
reduce_labels,
do_reduce_labels,
return_tensors,
)
return encoded_inputs
@@ -910,14 +931,13 @@ class OneFormerImageProcessor(BaseImageProcessor):
- **text_inputs** -- Optional list of text string entries to be fed to a model (when `annotations` are
provided). They identify the binary masks present in the image.
"""
ignore_index = self.ignore_index if ignore_index is None else ignore_index
reduce_labels = self.reduce_labels if reduce_labels is None else reduce_labels
if "pad_and_return_pixel_mask" in kwargs:
warnings.warn(
"The `pad_and_return_pixel_mask` argument has no effect and will be removed in v4.27", FutureWarning
)
ignore_index = self.ignore_index if ignore_index is None else ignore_index
reduce_labels = self.do_reduce_labels if reduce_labels is None else reduce_labels
pixel_values_list = [to_numpy_array(pixel_values) for pixel_values in pixel_values_list]
pad_size = get_max_height_width(pixel_values_list)
encoded_inputs = self.pad(pixel_values_list, return_tensors=return_tensors)

4
src/transformers/models/segformer/image_processing_segformer.py
View File

@@ -122,8 +122,8 @@ class SegformerImageProcessor(BaseImageProcessor):
@classmethod
def from_dict(cls, image_processor_dict: Dict[str, Any], **kwargs):
"""
Overrides the `from_dict` method from the base class to make sure `reduce_labels` is updated if image processor
is created using from_dict and kwargs e.g. `SegformerImageProcessor.from_pretrained(checkpoint,
Overrides the `from_dict` method from the base class to make sure `do_reduce_labels` is updated if image
processor is created using from_dict and kwargs e.g. `SegformerImageProcessor.from_pretrained(checkpoint,
reduce_labels=True)`
"""
image_processor_dict = image_processor_dict.copy()

6
tests/models/maskformer/test_image_processing_maskformer.py
View File

@@ -53,7 +53,7 @@ class MaskFormerFeatureExtractionTester(unittest.TestCase):
image_mean=[0.5, 0.5, 0.5],
image_std=[0.5, 0.5, 0.5],
num_labels=10,
reduce_labels=True,
do_reduce_labels=True,
ignore_index=255,
):
self.parent = parent
@@ -74,7 +74,7 @@ class MaskFormerFeatureExtractionTester(unittest.TestCase):
self.height = 3
self.width = 4
self.num_labels = num_labels
self.reduce_labels = reduce_labels
self.do_reduce_labels = do_reduce_labels
self.ignore_index = ignore_index
def prepare_feat_extract_dict(self):
@@ -86,7 +86,7 @@ class MaskFormerFeatureExtractionTester(unittest.TestCase):
"image_std": self.image_std,
"size_divisor": self.size_divisor,
"num_labels": self.num_labels,
"reduce_labels": self.reduce_labels,
"do_reduce_labels": self.do_reduce_labels,
"ignore_index": self.ignore_index,
}

8
tests/models/oneformer/test_image_processing_oneformer.py
View File

@@ -69,7 +69,7 @@ class OneFormerImageProcessorTester(unittest.TestCase):
image_mean=[0.5, 0.5, 0.5],
image_std=[0.5, 0.5, 0.5],
num_labels=10,
reduce_labels=False,
do_reduce_labels=False,
ignore_index=255,
repo_path="shi-labs/oneformer_demo",
class_info_file="ade20k_panoptic.json",
@@ -97,7 +97,7 @@ class OneFormerImageProcessorTester(unittest.TestCase):
self.height = 3
self.width = 4
self.num_labels = num_labels
self.reduce_labels = reduce_labels
self.do_reduce_labels = do_reduce_labels
self.ignore_index = ignore_index
def prepare_feat_extract_dict(self):
@@ -108,7 +108,7 @@ class OneFormerImageProcessorTester(unittest.TestCase):
"image_mean": self.image_mean,
"image_std": self.image_std,
"num_labels": self.num_labels,
"reduce_labels": self.reduce_labels,
"do_reduce_labels": self.do_reduce_labels,
"ignore_index": self.ignore_index,
"class_info_file": self.class_info_file,
"metadata": self.metadata,
@@ -180,7 +180,7 @@ class OneFormerImageProcessingTest(FeatureExtractionSavingTestMixin, unittest.Te
self.assertTrue(hasattr(image_processor, "num_text"))
self.assertTrue(hasattr(image_processor, "repo_path"))
self.assertTrue(hasattr(image_processor, "metadata"))
self.assertTrue(hasattr(image_processor, "reduce_labels"))
self.assertTrue(hasattr(image_processor, "do_reduce_labels"))
def test_batch_feature(self):
pass