Pusho za medolinjota
Gasper Spagnolo
parent
45ce034ca9
commit
a2b30c7ed1
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@ -227,8 +227,9 @@ def two_c():
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############################################
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def ex3():
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#three_a()
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three_b()
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#three_b()
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#three_c()
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three_d()
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def three_a():
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"""
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@ -300,6 +301,96 @@ def three_b():
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plt.show()
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def three_c():
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"""
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The sinusoids don’t usually intersect in only one point, resulting in more than one detected line.
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Implement a function named nonmaxima_suppression_box that checks
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the neighborhood of each pixel and set it to 0 if it is not the maximum value in the
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neighborhood (only consider 8-neighborhood). If more neighbouring pixels have the
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maximum value, keep only one.
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"""
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SIGMA = 1
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THETA = 0.02
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T_LOW = 0.04
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T_HIGH = 0.16
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synthetic_image = np.zeros((100, 100))
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synthetic_image[10, 10] = 1
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synthetic_image[10, 20] = 1
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oneline_image = uz_image.imread_gray('./images/oneline.png', uz_image.ImageType.float64)
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rectangle_image = uz_image.imread_gray('./images/rectangle.png', uz_image.ImageType.float64)
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oneline_image_edges = uz_image.find_edges_canny(oneline_image, SIGMA, THETA, T_LOW, T_HIGH)
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rectangle_image_edges = uz_image.find_edges_canny(rectangle_image, SIGMA, THETA, T_LOW, T_HIGH)
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synthetic_image_hough = uz_image.hough_find_lines(synthetic_image, 200, 200, 0.2)
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oneline_image_hough = uz_image.hough_find_lines(oneline_image_edges, 200, 200, 0.2)
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rectangle_image_hough = uz_image.hough_find_lines(rectangle_image_edges, 200, 200, 0.2)
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fig, axs = plt.subplots(4, 3)
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axs[0, 0].imshow(synthetic_image, cmap='gray')
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axs[0, 0].set_title('Synthetic image')
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axs[2, 0].imshow(synthetic_image_hough)
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axs[0, 1].imshow(oneline_image, cmap='gray')
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axs[0, 1].set_title('Oneline image')
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axs[1, 1].imshow(oneline_image_edges, cmap='gray')
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axs[0, 2].imshow(rectangle_image, cmap='gray')
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axs[0, 2].set_title('Rectangle image')
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axs[1, 2].imshow(rectangle_image_edges, cmap='gray')
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axs[1, 0].set_visible(False)
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axs[2, 1].imshow(oneline_image_hough)
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axs[2, 2].imshow(rectangle_image_hough)
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axs[3, 0].imshow(uz_image.nonmaxima_suppression_box(synthetic_image_hough))
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axs[3, 1].imshow(uz_image.nonmaxima_suppression_box(oneline_image_hough))
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axs[3, 2].imshow(uz_image.nonmaxima_suppression_box(rectangle_image_hough))
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plt.show()
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def three_d():
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"""
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Search the parameter space and extract all the parameter pairs (ρ, ϑ) whose corresponding accumulator cell value isgreater than a specified threshold threshold.
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Draw the lines that correspond to the parameter pairs using the draw_line function
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that you can find in the supplementary material.
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"""
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SIGMA = 1
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THETA = 0.02
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T_LOW = 0.04
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T_HIGH = 0.16
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synthetic_image = np.zeros((100, 100))
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synthetic_image[10, 10] = 1
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synthetic_image[10, 20] = 1
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oneline_image = uz_image.imread_gray('./images/oneline.png', uz_image.ImageType.float64)
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rectangle_image = uz_image.imread_gray('./images/rectangle.png', uz_image.ImageType.float64)
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oneline_image_edges = uz_image.find_edges_canny(oneline_image, SIGMA, THETA, T_LOW, T_HIGH)
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rectangle_image_edges = uz_image.find_edges_canny(rectangle_image, SIGMA, THETA, T_LOW, T_HIGH)
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synthetic_image_hough = uz_image.hough_find_lines(synthetic_image, 360, 360, 0.2)
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oneline_image_hough = uz_image.hough_find_lines(oneline_image_edges, 360, 360, 0.2)
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rectangle_image_hough = uz_image.hough_find_lines(rectangle_image_edges, 360, 360 , 0.2)
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synthetic_image_hough_nonmax = uz_image.nonmaxima_suppression_box(synthetic_image_hough)
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oneline_image_hough_nonmax = uz_image.nonmaxima_suppression_box(oneline_image_hough)
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rectangle_image_hough_nonmax = uz_image.nonmaxima_suppression_box(rectangle_image_hough)
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fig, axs = plt.subplots(1, 3)
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axs[0].imshow(oneline_image)
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neighbour_pairs = uz_image.retrieve_hough_pairs(oneline_image_hough_nonmax, np.max(oneline_image_hough_nonmax)*0.3, 360, 360)
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for neighbour in neighbour_pairs:
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xs, ys = uz_image.get_line_to_plot(neighbour[0], neighbour[1], oneline_image_hough_nonmax.shape[0], oneline_image_hough_nonmax.shape[1])
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axs[0].plot(xs, ys, 'r', linewidth=0.7)
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plt.show()
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# ######## #
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# SOLUTION #
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# ######## #
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@ -589,9 +589,9 @@ def find_edges_nms(image: Union[npt.NDArray[np.float64], npt.NDArray[np.uint8]],
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if i == 0 or i == 7:
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return (0, 1), (0, -1)
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elif i == 1 or i == 2:
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return (-1, 1), (1, -1)
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elif i == 3 or i == 4:
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return (-1, 0), (1, 0)
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elif i == 3 or i == 4:
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return (-1, 1), (1, -1)
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elif i == 5 or i == 6:
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return (-1, -1), (1, 1)
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raise ValueError(f"Angle {angle} is not in range")
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@ -692,3 +692,85 @@ def hough_find_lines(image: Union[npt.NDArray[np.float64], npt.NDArray[np.uint8]
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return accumulator
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def nonmaxima_suppression_box(image: npt.NDArray[np.uint64]) -> npt.NDArray[np.uint64]:
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"""
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Accepts: image with sinusoids in hough space
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Returns: image with sinusoids
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"""
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image = image.copy()
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def get_neighbours() -> list[tuple[int, int]]:
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neighbours = []
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for i in range(-1, 2):
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for j in range(-1, 2):
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if i != 0 or j != 0:
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neighbours.append((i, j))
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return neighbours
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for y in range(1, image.shape[0]-1):
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for x in range(1, image.shape[1]-1):
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for neighbour in get_neighbours():
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if image[y, x] < image[y+neighbour[0], x+neighbour[1]]:
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image[y, x] = 0
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break
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return image
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def retrieve_hough_pairs(image: npt.NDArray[np.uint64], treshold: int, n_bins_theta: int, n_bins_rho) -> list[tuple[int, int]]:
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"""
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Accepts: image with sinusoids in hough space, treshold
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Returns: list of pairs of sinusoids
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"""
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theta_values = np.linspace(-np.pi/2, np.pi/2, n_bins_theta)
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rho_values = np.linspace(-np.sqrt(image.shape[0]**2 + image.shape[1]**2), np.sqrt(image.shape[0]**2 + image.shape[1]**2), n_bins_rho)
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image = image.copy()
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image[image < treshold] = 0
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y_s, x_s = np.nonzero(image)
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pairs = []
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for i in range(len(x_s)):
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x = x_s[i] # theta values
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y = y_s[i] # rho values
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theta = theta_values[x]
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rho = rho_values[y]
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pairs.append((rho, theta))
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return pairs
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def get_line_to_plot(rho, theta, h, w):
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"""
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Accepts: rho, theta, image height h, image width w
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Returns: line to plot
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usage example: plt.plot(uz_image.get_line_to_plot(rho, theta, h, w), 'r', linewidth=.7)
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"""
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c = np.cos(theta)
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s = np.sin(theta)
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xs = []
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ys = []
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if s != 0:
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y = int(rho / s)
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if 0 <= y < h:
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xs.append(0)
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ys.append(y)
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y = int((rho - w * c) / s)
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if 0 <= y < h:
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xs.append(w - 1)
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ys.append(y)
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if c != 0:
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x = int(rho / c)
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if 0 <= x < w:
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xs.append(x)
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ys.append(0)
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x = int((rho - h * s) / c)
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if 0 <= x < w:
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xs.append(x)
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ys.append(h - 1)
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return xs[:2], ys[:2]
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