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| import copy | |
| import matplotlib | |
| import matplotlib.colors as mcolors | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| def plot_images(imgs, titles=None, cmaps="gray", dpi=100, size=6, pad=0.5): | |
| """Plot a set of images horizontally. | |
| Args: | |
| imgs: a list of NumPy or PyTorch images, RGB (H, W, 3) or mono (H, W). | |
| titles: a list of strings, as titles for each image. | |
| cmaps: colormaps for monochrome images. | |
| """ | |
| n = len(imgs) | |
| if not isinstance(cmaps, (list, tuple)): | |
| cmaps = [cmaps] * n | |
| figsize = (size * n, size * 3 / 4) if size is not None else None | |
| fig, ax = plt.subplots(1, n, figsize=figsize, dpi=dpi) | |
| if n == 1: | |
| ax = [ax] | |
| for i in range(n): | |
| ax[i].imshow(imgs[i], cmap=plt.get_cmap(cmaps[i])) | |
| ax[i].get_yaxis().set_ticks([]) | |
| ax[i].get_xaxis().set_ticks([]) | |
| ax[i].set_axis_off() | |
| for spine in ax[i].spines.values(): # remove frame | |
| spine.set_visible(False) | |
| if titles: | |
| ax[i].set_title(titles[i]) | |
| fig.tight_layout(pad=pad) | |
| return fig | |
| def plot_lines( | |
| lines, fig, line_colors="orange", point_colors="cyan", ps=4, lw=2, indices=(0, 1) | |
| ): | |
| """Plot lines and endpoints for existing images. | |
| Args: | |
| lines: list of ndarrays of size (N, 2, 2). | |
| colors: string, or list of list of tuples (one for each keypoints). | |
| ps: size of the keypoints as float pixels. | |
| lw: line width as float pixels. | |
| indices: indices of the images to draw the matches on. | |
| """ | |
| if not isinstance(line_colors, list): | |
| line_colors = [line_colors] * len(lines) | |
| if not isinstance(point_colors, list): | |
| point_colors = [point_colors] * len(lines) | |
| # fig = plt.gcf() | |
| ax = fig.axes | |
| assert len(ax) > max(indices) | |
| axes = [ax[i] for i in indices] | |
| fig.canvas.draw() | |
| # Plot the lines and junctions | |
| for a, l, lc, pc in zip(axes, lines, line_colors, point_colors): | |
| for i in range(len(l)): | |
| line = matplotlib.lines.Line2D( | |
| (l[i, 1, 1], l[i, 0, 1]), | |
| (l[i, 1, 0], l[i, 0, 0]), | |
| zorder=1, | |
| c=lc, | |
| linewidth=lw, | |
| ) | |
| a.add_line(line) | |
| pts = l.reshape(-1, 2) | |
| a.scatter(pts[:, 1], pts[:, 0], c=pc, s=ps, linewidths=0, zorder=2) | |
| return fig | |
| def plot_color_line_matches(lines, fig, lw=2, indices=(0, 1)): | |
| """Plot line matches for existing images with multiple colors. | |
| Args: | |
| lines: list of ndarrays of size (N, 2, 2). | |
| lw: line width as float pixels. | |
| indices: indices of the images to draw the matches on. | |
| """ | |
| n_lines = len(lines[0]) | |
| cmap = plt.get_cmap("nipy_spectral", lut=n_lines) | |
| colors = np.array([mcolors.rgb2hex(cmap(i)) for i in range(cmap.N)]) | |
| np.random.shuffle(colors) | |
| ax = fig.axes | |
| assert len(ax) > max(indices) | |
| axes = [ax[i] for i in indices] | |
| fig.canvas.draw() | |
| # Plot the lines | |
| for a, l in zip(axes, lines): | |
| for i in range(len(l)): | |
| line = matplotlib.lines.Line2D( | |
| (l[i, 1, 1], l[i, 0, 1]), | |
| (l[i, 1, 0], l[i, 0, 0]), | |
| zorder=1, | |
| c=colors[i], | |
| linewidth=lw, | |
| ) | |
| a.add_line(line) | |
| return fig | |