Estimate corner radius

estimate_corner_radius.py

# This function estimates the corner radius of a window by checking multiple directions from each corner 
# and finding the distance where the image changes from transparent to solid. 
# It’s useful for detecting rounded corners in screenshots of macOS windows or pixel data of images etc.
def estimate_corner_radius(self, image_or_array, threshold=128, samples=8):

        import math
        import numpy as np

        # if input is a PIL Image, convert to numpy array
        if hasattr(image_or_array, 'convert'):
            arr = np.asarray(image_or_array.convert("RGBA"))
        else:
            arr = image_or_array

        height, width, _ = arr.shape
        max_radius = min(width, height) // 4

        corner_data = [((1, 1), 0),
            ((width - 2, 1), 90),
            ((1, height - 2), 270),
            ((width - 2, height - 2), 180),
        ]

        angle_offsets = np.linspace(0, 90, samples, endpoint=False)

        def _estimate_corner(corner, base_angle):
            cx, cy = corner
            radii = []
            for angle in angle_offsets + base_angle:
                rad = math.radians(angle)
                dx, dy = math.cos(rad), math.sin(rad)
                for r in range(1, max_radius):
                    x = int(round(cx + r * dx))
                    y = int(round(cy + r * dy))
                    if not (0 <= x < width and 0 <= y < height):
                        break
                    alpha = arr[y, x, 3]
                    if alpha >= threshold:
                        radii.append(r)
                        break
            return min(radii) if radii else max_radius

        corner_radii = [_estimate_corner(corner, angle) for corner, angle in corner_data]
        valid_radii = [r for r in corner_radii if r > 0]
        estimated_radius = min(valid_radii) if valid_radii else 0
        return max(0, estimated_radius)