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    Home»Machine Learning»Hough Transform 学习笔记. Image and parameter space | by Yong Han | Jul, 2025
    Machine Learning

    Hough Transform 学习笔记. Image and parameter space | by Yong Han | Jul, 2025

    Team_AIBS NewsBy Team_AIBS NewsJuly 23, 2025No Comments1 Min Read
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    import numpy as np
    import matplotlib.pyplot as plt
    from typing import Record, Tuple
    from PIL import Picture
    import cv2

    def plot_points_and_lines_with_grid(
    ax: plt.Axes,
    ax_labels = [“x”, “y”],
    scatter_arg_kwarg_pair: Tuple = None,
    line_arg_kwarg_pairs: Record[Tuple] = None,
    limits: Record[int] = [-5, 5, -5, 5]
    ):
    “””_summary_

    https://stackoverflow.com/questions/13430231/how-i-can-get-cartesian-coordinate-system-in-matplotlib

    Args:
    ax (_type_): _description_
    scatter_arg_kwarg_pair (Tuple, optionally available): _description_. Defaults to None.
    line_arg_kwarg_pairs (Record[Tuple], optionally available): _description_. Defaults to None.
    label_size (int, optionally available): _description_. Defaults to 14.

    Returns:
    _type_: _description_
    “””

    # Plot factors
    if scatter_arg_kwarg_pair will not be None:
    scatter_args, scatter_kwargs = scatter_arg_kwarg_pair
    ax.scatter(*scatter_args, **scatter_kwargs)

    # Plot traces
    if line_arg_kwarg_pairs will not be None:
    for line_args, line_kwargs in line_arg_kwarg_pairs:
    ax.plot(*line_args, **line_kwargs)

    # Choose size of axes and the house between tick labels
    xmin, xmax, ymin, ymax = limits
    ticks_frequency = 1

    # Set an identical scales for each axes
    ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), facet=’equal’)

    # Set backside and left spines as x and y axes of coordinate system…



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