pyflink.multimodal.expression.ImageExpressionAccessor.crop_black_border

ImageExpressionAccessor.crop_black_border(*, threshold: Optional[float] = None, detect_algorithm: Literal['auto', 'threshold', 'histogram', 'edge'] = 'auto', black_threshold: Optional[int] = None, edge_sensitivity: float = 1.0, min_border_size: int = 1, concurrency: Optional[int] = None) → pyflink.table.expression.Expression

Remove black borders from image values.

Equivalent to image_crop_black_border(). See that function for full parameter details.

Parameters

• threshold – Optional border detection threshold.

• detect_algorithm – Border detection algorithm.

• black_threshold – Pixel threshold used to classify black borders.

• edge_sensitivity – Sensitivity for detecting border edges.

• min_border_size – Minimum border size in pixels.

• concurrency – Optional execution concurrency for this operation. None uses the framework default.

Returns

A DataFrame expression that produces IMAGE values with black borders removed.