to3i
101 linhas
3.1 KiB
Python
101 linhas
3.1 KiB
Python
import numpy as np
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import matplotlib.pyplot as plt
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from scipy import ndimage as ndi
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def show_line_skeleton(lbl_ind_x, skeleton):
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# display results
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fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(12, 4), sharex=True, sharey=True,
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subplot_kw={'adjustable': 'box-forced'})
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ax = axes.ravel()
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ax[0].imshow(lbl_ind_x, cmap=plt.cm.gray)
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ax[0].axis('off')
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ax[0].set_title('original', fontsize=20)
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ax[1].imshow(skeleton, cmap=plt.cm.gray)
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ax[1].axis('off')
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ax[1].set_title('skeleton', fontsize=20)
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ax[2].imshow(ndi.label(skeleton, structure=np.ones((3, 3)))[0], cmap=plt.cm.spectral)
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ax[2].axis('off')
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ax[2].set_title('skeleton', fontsize=20)
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fig.tight_layout()
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def show_hough_transform_w_lines(lbl_ind_x, center_im, h, theta, d, line_hypos, color):
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# Generating figure 1
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fig, axes = plt.subplots(1, 3, figsize=(15, 6),
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subplot_kw={'adjustable': 'box-forced'}) # (25, 15)
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ax = axes.ravel()
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ax[0].imshow(center_im, cmap='gray')
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ax[0].set_title('Input image')
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ax[0].set_axis_off()
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ax[1].imshow(np.log(1 + h),
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extent=[np.rad2deg(theta[-1]), np.rad2deg(theta[0]), d[-1], d[0]],
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cmap='gray', aspect=1 / 1.5)
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ax[1].set_title('Hough transform')
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ax[1].set_xlabel('Angles (degrees)')
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ax[1].set_ylabel('Distance (pixels)')
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ax[1].axis('image')
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ax[2].imshow(lbl_ind_x, cmap='gray')
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for idx, line_rec in line_hypos.groupby('label').mean().iterrows():
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angle = line_rec.angle
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dist = line_rec.dist
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y0 = (dist - 0 * np.cos(angle)) / np.sin(angle)
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y1 = (dist - lbl_ind_x.shape[1] * np.cos(angle)) / np.sin(angle)
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ax[2].plot((0, lbl_ind_x.shape[1]), (y0, y1), '-', color=color[int(idx)], linewidth=2)
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ax[2].set_xlim((0, lbl_ind_x.shape[1]))
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ax[2].set_ylim((lbl_ind_x.shape[0], 0))
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ax[2].set_axis_off()
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ax[2].set_title('Detected lines')
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# ax[2].imshow(lbl_ind, cmap='gray')
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# ax[2].set_title('Input image')
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# ax[2].set_axis_off()
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def show_probabilistic_hough(lbl_ind_x, center_im, line_segs, ls_labels, group2line, color):
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fig, axes = plt.subplots(1, 2, figsize=(15, 5))
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ax = axes.ravel()
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ax[0].imshow(center_im, cmap='gray')
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ax[0].set_title('Input image')
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# ax[1].imshow(lbl_ind_x, cmap='gray')
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# ax[1].set_title('line det')
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ax[1].imshow(lbl_ind_x * 0)
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for line, li in zip(line_segs, ls_labels):
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p0, p1 = line
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ax[1].plot((p0[0], p1[0]), (p0[1], p1[1]), color=color[int(group2line[li])], linewidth=2)
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ax[1].text(p0[0], p0[1], '{}'.format(group2line[li]),
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bbox=dict(facecolor='blue', alpha=0.5), fontsize=8, color='white')
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ax[1].set_xlim((0, lbl_ind_x.shape[1]))
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ax[1].set_ylim((lbl_ind_x.shape[0], 0))
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ax[1].set_title('Probabilistic Hough')
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def show_line_segms(image_label_overlay, segm_labels):
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fig, axes = plt.subplots(1, 2, figsize=(15, 9)) # 25, 15
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ax = axes.ravel()
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ax[0].imshow(image_label_overlay, cmap='gray')
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ax[0].set_title('Input image')
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ax[1].imshow(segm_labels)
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ax[1].set_title('Line segments')
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