^j`bddlmZddlZddlZddlmZ d ddZ d ddZ y) ) annotationsNc|||S|Dcgc]}tj|}}t||Dcgc]\}}|||k\r |||kr|c}}Scc}wcc}}w)aM Filters a list of polygons based on their area. Args: polygons: A list of polygons, where each polygon is represented by a NumPy array of shape `(N, 2)`, containing the `x`, `y` coordinates of the points. min_area: The minimum area threshold. Only polygons with an area greater than or equal to this value will be included in the output. If set to None, no minimum area constraint will be applied. max_area: The maximum area threshold. Only polygons with an area less than or equal to this value will be included in the output. If set to None, no maximum area constraint will be applied. Returns: A new list of polygons containing only those with areas within the specified thresholds. )cv2 contourAreazip)polygonsmin_areamax_areapolygonaresareas o/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/supervision/detection/utils/polygons.pyfilter_polygons_by_arears|2H,4< =COOG $ =D =!40  GT   0  !1   > s AAc|dks|dk\r td|dkr tdttt|d|z zd}t||kr|Sd}|}t||kDrT||z }t j t j||dd}t|dkr |S|}t||kDrT|S) u Approximates a given polygon by reducing a certain percentage of points. This function uses the Ramer-Douglas-Peucker algorithm to simplify the input polygon by reducing the number of points while preserving the general shape. Args: polygon: A 2D NumPy array of shape `(N, 2)` containing the `x`, `y` coordinates of the input polygon's points. percentage: The percentage of points to be removed from the input polygon, in the range `[0, 1)`. epsilon_step: Approximation accuracy step, must be positive. Epsilon is the maximum distance between the original curve and its approximation. Returns: A new 2D NumPy array of shape `(M, 2)` containing the `x`, `y` coordinates of the approximated polygon's points. `M` is at most `floor(N * (1 - percentage))` (minimum 3). Because epsilon advances in discrete `epsilon_step` increments, `M` may be noticeably smaller than the budget when a single step crosses the target band. At least 3 points are always kept; when further simplification would collapse the polygon below 3 points the last valid approximation is returned and `M` may exceed the budget. Raises: ValueError: If `percentage` is outside the range `[0, 1)`. ValueError: If `epsilon_step` is not positive. Examples: Reduce a polygon to at most half its original point count: >>> import numpy as np >>> polygon = np.array([[0, 0], [10, 0], [10, 10], [0, 10], ... [5, 10], [5, 5], [3, 7], [1, 9]]) >>> result = approximate_polygon(polygon, percentage=0.5) >>> result.shape[1] 2 >>> len(result) <= max(int(len(polygon) * 0.5), 3) True Polygon already at or below target — returned unchanged: >>> tiny = np.array([[0, 0], [5, 0], [2, 4]]) >>> approximate_polygon(tiny, percentage=0.5) is tiny True rz'Percentage must be in the range [0, 1).zepsilon_step must be positive.T)closed)axis) ValueErrormaxintlennpsqueezer approxPolyDP)r percentage epsilon_step target_pointsepsilonapproximated_points candidates rapproximate_polygonr",sfA~qBCCq9::CLA N;A   ( ! "] 2 )NN)rlist[npt.NDArray[np.number]]r float | Noner r%returnr$)g?)r npt.NDArray[np.number]rfloatrr(r&r') __future__rrnumpyr numpy.typingtypingnptrr"r#rr/st"  "!!*!!!" !JOSH #H16HFKHHr#