Refactor/remove asserts annotators image (#2354)
- ValueError → TypeError in all three ensure_*_image_for_* decorators (conversion.py): the decorator intercepts non-ndarray/PIL inputs before the wrapped body runs, so the inner raises were unreachable; fixing at the decorator level fixes all annotators at once - Remove 5 dead isinstance guards from key_points/annotators.py and 4 from utils/image.py (all now covered by the decorator fix) - Remove dead assert isinstance(scene, Image.Image) from RichLabelAnnotator.annotate (ensure_pil_image_for_class_method guarantees PIL.Image before inner body) - Add @ensure_cv2_image_for_class_method to VertexLabelAnnotator.annotate for PIL parity (only decorated annotator missing it) - Rewrite tests to call public API directly (no __wrapped__ bypass); replace with TestAnnotatorInputValidation class (parametrized, IDs, AAA) + parametrized test_image_utils_wrong_type_raises - Add Raises: TypeError sections to all 6 annotator .annotate() docstrings, 4 image util docstrings, and 3 decorator docstrings --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: jirka <6035284+Borda@users.noreply.github.com> Co-authored-by: claude[bot] <209825114+claude[bot]@users.noreply.github.com>
This commit is contained in:
Vikas saini
GitHub
parent
27ba0aa92f
commit
7239af5048
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@ -1616,7 +1616,6 @@ class RichLabelAnnotator(_BaseLabelAnnotator):
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```
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"""
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assert isinstance(scene, Image.Image)
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_validate_labels(labels, detections)
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draw = ImageDraw.Draw(scene)
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@ -64,6 +64,9 @@ class VertexAnnotator(BaseKeyPointAnnotator):
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The annotated image, matching the type of `scene` (`numpy.ndarray`
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or `PIL.Image.Image`)
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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```pycon
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>>> import numpy as np
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@ -84,7 +87,6 @@ class VertexAnnotator(BaseKeyPointAnnotator):
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```
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"""
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assert isinstance(scene, np.ndarray)
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if len(key_points) == 0:
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return scene
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@ -154,6 +156,9 @@ class EdgeAnnotator(BaseKeyPointAnnotator):
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The annotated image, matching the type of `scene` (`numpy.ndarray`
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or `PIL.Image.Image`)
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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Single-skeleton example:
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@ -205,7 +210,6 @@ class EdgeAnnotator(BaseKeyPointAnnotator):
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```
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"""
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assert isinstance(scene, np.ndarray)
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if len(key_points) == 0:
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return scene
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@ -416,6 +420,9 @@ class VertexEllipseAreaAnnotator(_BaseVertexEllipseAnnotator):
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Returns:
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The annotated image, matching the type of ``scene``.
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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```pycon
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>>> import numpy as np
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@ -445,7 +452,6 @@ class VertexEllipseAreaAnnotator(_BaseVertexEllipseAnnotator):
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```
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"""
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assert isinstance(scene, np.ndarray)
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if len(key_points) == 0:
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return scene
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@ -514,6 +520,9 @@ class VertexEllipseOutlineAnnotator(_BaseVertexEllipseAnnotator):
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Returns:
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The annotated image, matching the type of ``scene``.
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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```pycon
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>>> import numpy as np
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@ -544,7 +553,6 @@ class VertexEllipseOutlineAnnotator(_BaseVertexEllipseAnnotator):
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```
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"""
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assert isinstance(scene, np.ndarray)
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if len(key_points) == 0:
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return scene
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@ -616,6 +624,9 @@ class VertexEllipseHaloAnnotator(_BaseVertexEllipseAnnotator):
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Returns:
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The annotated image, matching the type of ``scene``.
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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```pycon
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>>> import numpy as np
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@ -645,7 +656,6 @@ class VertexEllipseHaloAnnotator(_BaseVertexEllipseAnnotator):
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```
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"""
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assert isinstance(scene, np.ndarray)
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if len(key_points) == 0:
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return scene
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@ -737,6 +747,7 @@ class VertexLabelAnnotator:
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self.text_padding: int = text_padding
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self.smart_position = smart_position
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@ensure_cv2_image_for_class_method
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def annotate(
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self,
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scene: ImageType,
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@ -762,6 +773,9 @@ class VertexLabelAnnotator:
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The annotated image, matching the type of `scene` (`numpy.ndarray`
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or `PIL.Image.Image`)
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Example:
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Single-skeleton example:
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@ -824,7 +838,6 @@ class VertexLabelAnnotator:
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```
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"""
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assert isinstance(scene, np.ndarray)
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font = cv2.FONT_HERSHEY_SIMPLEX
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skeletons_count, points_count, _ = key_points.xy.shape
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@ -22,6 +22,9 @@ def ensure_cv2_image_for_class_method(
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is complete.
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Assumes the annotators modify the scene in-place.
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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"""
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@functools.wraps(annotate_func)
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@ -35,7 +38,7 @@ def ensure_cv2_image_for_class_method(
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scene.paste(cv2_to_pillow(annotated_np))
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return scene
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raise ValueError(f"Unsupported image type: {type(scene)}")
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raise TypeError(f"Unsupported image type: {type(scene)}")
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return cast(F, wrapper)
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@ -59,6 +62,9 @@ def ensure_cv2_image_for_standalone_function(
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np.ndarray, converts back when processing is complete.
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Assumes the annotators do NOT modify the scene in-place.
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Raises:
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TypeError: If `image` is not a `numpy.ndarray` or `PIL.Image.Image`.
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"""
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@functools.wraps(image_processing_fun)
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@ -71,7 +77,7 @@ def ensure_cv2_image_for_standalone_function(
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annotated = image_processing_fun(scene, *args, **kwargs)
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return cv2_to_pillow(annotated)
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raise ValueError(f"Unsupported image type: {type(image)}")
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raise TypeError(f"Unsupported image type: {type(image)}")
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return cast(F, wrapper)
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@ -84,6 +90,9 @@ def ensure_pil_image_for_class_method(
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PIL image, converts back when processing is complete.
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Assumes the annotators modify the scene in-place.
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Raises:
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TypeError: If `scene` is not a `numpy.ndarray` or `PIL.Image.Image`.
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"""
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@functools.wraps(annotate_func)
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@ -97,7 +106,7 @@ def ensure_pil_image_for_class_method(
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if isinstance(scene, Image.Image):
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return cast(ImageType, annotate_func(self, scene, *args, **kwargs))
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raise ValueError(f"Unsupported image type: {type(scene)}")
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raise TypeError(f"Unsupported image type: {type(scene)}")
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return cast(F, wrapper)
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@ -105,6 +105,7 @@ def scale_image(image: ImageType, scale_factor: float) -> ImageType:
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type.
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Raises:
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TypeError: If `image` is not a `numpy.ndarray` or `PIL.Image.Image`.
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ValueError: If scale factor is non-positive.
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Examples:
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@ -132,7 +133,6 @@ def scale_image(image: ImageType, scale_factor: float) -> ImageType:
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{ align=center width="1000" }
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""" # noqa E501 // docs
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assert isinstance(image, np.ndarray)
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if scale_factor <= 0:
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raise ValueError("Scale factor must be positive.")
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@ -161,6 +161,9 @@ def resize_image(
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Resized image matching input
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type.
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Raises:
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TypeError: If `image` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Examples:
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```pycon
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>>> import numpy as np
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@ -190,7 +193,6 @@ def resize_image(
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{ align=center width="1000" }
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""" # noqa E501 // docs
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assert isinstance(image, np.ndarray)
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if keep_aspect_ratio:
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image_ratio = image.shape[1] / image.shape[0]
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target_ratio = resolution_wh[0] / resolution_wh[1]
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@ -227,6 +229,9 @@ def letterbox_image(
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Returns:
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Letterboxed image matching input type.
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Raises:
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TypeError: If `image` is not a `numpy.ndarray` or `PIL.Image.Image`.
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Note:
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For BGRA inputs, the alpha channel in the padding region is set to
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0 (fully transparent). Grayscale inputs receive scalar padding
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@ -252,7 +257,6 @@ def letterbox_image(
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{ align=center width="1000" }
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""" # noqa E501 // docs
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assert isinstance(image, np.ndarray)
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color = unify_to_bgr(color=color)
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resized_image = resize_image(
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image=image, resolution_wh=resolution_wh, keep_aspect_ratio=True
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@ -372,6 +376,7 @@ def tint_image(
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type.
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Raises:
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TypeError: If `image` is not a `numpy.ndarray` or `PIL.Image.Image`.
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ValueError: If opacity is outside range [0.0, 1.0].
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Examples:
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@ -389,7 +394,6 @@ def tint_image(
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{ align=center width="1000" }
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""" # noqa E501 // docs
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assert isinstance(image, np.ndarray)
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if not 0.0 <= opacity <= 1.0:
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raise ValueError("opacity must be between 0.0 and 1.0")
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@ -502,3 +502,30 @@ class TestVertexLabelAnnotator:
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def test_resolve_color_list_wrong_length_raises(self, colors, points_count):
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with pytest.raises(ValueError, match="Number of colors"):
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sv.VertexLabelAnnotator._resolve_color_list(colors, points_count)
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class TestAnnotatorInputValidation:
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"""Verify that all keypoint annotators reject invalid scene types."""
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@pytest.mark.parametrize(
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("annotator_class", "kwargs"),
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[
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pytest.param(sv.VertexAnnotator, {}, id="VertexAnnotator"),
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pytest.param(sv.EdgeAnnotator, {}, id="EdgeAnnotator"),
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pytest.param(sv.VertexEllipseAnnotator, {}, id="VertexEllipseAnnotator"),
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pytest.param(
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sv.VertexEllipseOutlineAnnotator, {}, id="VertexEllipseOutlineAnnotator"
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),
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pytest.param(
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sv.VertexEllipseHaloAnnotator, {}, id="VertexEllipseHaloAnnotator"
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),
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pytest.param(sv.VertexLabelAnnotator, {}, id="VertexLabelAnnotator"),
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],
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)
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def test_annotate_wrong_scene_type_raises(
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self, annotator_class, kwargs, sample_key_points
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):
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"""Wrong scene type raises TypeError."""
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annotator = annotator_class(**kwargs)
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with pytest.raises(TypeError, match="Unsupported image type"):
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annotator.annotate(scene="not_an_image", key_points=sample_key_points)
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@ -7,6 +7,8 @@ from supervision.utils.image import (
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get_image_resolution_wh,
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letterbox_image,
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resize_image,
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scale_image,
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tint_image,
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)
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@ -193,3 +195,20 @@ def test_crop_image(image, xyxy, expected_size):
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def test_get_image_resolution_wh(image, expected):
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resolution = get_image_resolution_wh(image)
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assert resolution == expected
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@pytest.mark.parametrize(
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("func", "kwargs"),
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[
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pytest.param(scale_image, {"scale_factor": 1.0}, id="scale_image"),
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pytest.param(resize_image, {"resolution_wh": (10, 10)}, id="resize_image"),
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pytest.param(
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letterbox_image, {"resolution_wh": (10, 10)}, id="letterbox_image"
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),
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pytest.param(tint_image, {}, id="tint_image"),
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],
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)
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def test_image_utils_wrong_type_raises(func, kwargs):
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"""Wrong image type raises TypeError via decorator."""
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with pytest.raises(TypeError, match="Unsupported image type"):
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func(image="not_an_image", **kwargs)
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