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fixed issue in precision converting annotations with "force_mask=True" #1746

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fixed issue in precision converting annotations with "force_mask=True" #1746

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4e669b6
changing polygon format conversion
0xD4rky Dec 16, 2024
fd4e84e
reformating polygon type conversion
0xD4rky Dec 16, 2024
b593c1e
fix(pre_commit): 🎨 auto format pre-commit hooks
pre-commit-ci[bot] Dec 16, 2024
45e0259
handling mask dimension
0xD4rky Dec 17, 2024
d93e2e8
handling mask dimension
0xD4rky Dec 17, 2024
373b661
handling mask dimensions
0xD4rky Dec 17, 2024
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24 changes: 11 additions & 13 deletions supervision/dataset/formats/yolo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@
from supervision.config import ORIENTED_BOX_COORDINATES
from supervision.dataset.utils import approximate_mask_with_polygons
from supervision.detection.core import Detections
from supervision.detection.utils import polygon_to_mask, polygon_to_xyxy
from supervision.detection.utils import polygon_to_xyxy
from supervision.utils.file import (
list_files_with_extensions,
read_txt_file,
Expand Down Expand Up @@ -45,15 +45,14 @@ def _parse_polygon(values: List[str]) -> np.ndarray:


def _polygons_to_masks(
polygons: List[np.ndarray], resolution_wh: Tuple[int, int]
polygon: list[np.ndarray], resolution_wh: Tuple[int, int]
) -> np.ndarray:
return np.array(
[
polygon_to_mask(polygon=polygon, resolution_wh=resolution_wh)
for polygon in polygons
],
dtype=bool,
)
polygon_int = np.round(polygon).astype(np.int32)
mask = np.zeros((resolution_wh[1], resolution_wh[0]), dtype=np.uint8)

cv2.fillPoly(mask, [polygon_int], 1)
mask = mask[None, ...]
return mask.astype(bool)


def _with_mask(lines: List[str]) -> bool:
Expand Down Expand Up @@ -114,10 +113,8 @@ def yolo_annotations_to_detections(
if not with_masks:
return Detections(class_id=class_id, xyxy=xyxy, data=data)

polygons = [
(polygon * np.array(resolution_wh)).astype(int) for polygon in relative_polygon
]
mask = _polygons_to_masks(polygons=polygons, resolution_wh=resolution_wh)
polygons = [(polygon * np.array(resolution_wh)) for polygon in relative_polygon]
mask = _polygons_to_masks(polygon=polygons, resolution_wh=resolution_wh)
return Detections(class_id=class_id, xyxy=xyxy, data=data, mask=mask)


Expand Down Expand Up @@ -145,6 +142,7 @@ def load_yolo_annotations(
where pairs of [x, y] are box corners.

Returns:

Tuple[List[str], List[str], Dict[str, Detections]]:
A tuple containing a list of class names, a dictionary with
image names as keys and images as values, and a dictionary
Expand Down