riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-04 13:20:12 +06:00
Code Issues Actions 21 Packages Projects Releases Wiki Activity

use decorator

Browse Source
This commit is contained in:
yaswant19 2025-07-02 00:50:16 +05:30
parent e0a0381631
commit ec29b730ec
2 changed files with 3 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
src/transformers/models/eomt/image_processing_eomt.py
View File

@ -858,7 +858,6 @@ class EomtImageProcessor(BaseImageProcessor):
): ):
"""Post-processes model outputs into final panoptic segmentation prediction.""" """Post-processes model outputs into final panoptic segmentation prediction."""
# `mask_threshold` and `overlap_mask_area_threshold` args are unused and only present for Pipeline compatability.
size = size if size is not None else self.size size = size if size is not None else self.size
masks_queries_logits = outputs.masks_queries_logits # [batch_size, num_queries, height, width] masks_queries_logits = outputs.masks_queries_logits # [batch_size, num_queries, height, width]
@ -904,13 +903,12 @@ class EomtImageProcessor(BaseImageProcessor):
results.append({"segmentation": segmentation, "segments_info": segments}) results.append({"segmentation": segmentation, "segments_info": segments})
return results return results
@filter_out_non_signature_kwargs()
def post_process_instance_segmentation( def post_process_instance_segmentation(
self, self,
outputs, outputs,
target_sizes: list[tuple[int, int]], target_sizes: list[tuple[int, int]],
threshold: float = 0.5, threshold: float = 0.5,
mask_threshold: float = 0.5,
overlap_mask_area_threshold: float = 0.8,
size: Optional[dict[str, int]] = None, size: Optional[dict[str, int]] = None,
): ):
"""Post-processes model outputs into Instance Segmentation Predictions.""" """Post-processes model outputs into Instance Segmentation Predictions."""

5
src/transformers/models/eomt/image_processing_eomt_fast.py
View File

@ -41,6 +41,7 @@ from ...processing_utils import Unpack
from ...utils import ( from ...utils import (
TensorType, TensorType,
auto_docstring, auto_docstring,
filter_out_non_signature_kwargs,
is_torch_available, is_torch_available,
is_torchvision_available, is_torchvision_available,
is_torchvision_v2_available, is_torchvision_v2_available,
@ -511,18 +512,16 @@ class EomtImageProcessorFast(BaseImageProcessorFast):
results.append({"segmentation": segmentation, "segments_info": segments}) results.append({"segmentation": segmentation, "segments_info": segments})
return results return results
@filter_out_non_signature_kwargs()
def post_process_instance_segmentation( def post_process_instance_segmentation(
self, self,
outputs, outputs,
target_sizes: list[tuple[int, int]], target_sizes: list[tuple[int, int]],
threshold: float = 0.8, threshold: float = 0.8,
mask_threshold: float = 0.5,
overlap_mask_area_threshold: float = 0.8,
size: Optional[dict[str, int]] = None, size: Optional[dict[str, int]] = None,
): ):
"""Post-processes model outputs into Instance Segmentation Predictions.""" """Post-processes model outputs into Instance Segmentation Predictions."""
# `mask_threshold` and `overlap_mask_area_threshold` args are unused and only present for Pipeline compatability.
size = size if size is not None else self.size size = size if size is not None else self.size
masks_queries_logits = outputs.masks_queries_logits masks_queries_logits = outputs.masks_queries_logits