2023-01-30 11:11:52 +00:00
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import matplotlib.pyplot as plt
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import numpy as np
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2023-01-31 13:51:14 +00:00
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import cv2
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2023-01-30 11:11:52 +00:00
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def f(x, y):
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return np.exp(-((x**2) + y**2) / 3)
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x_vals = np.linspace(-5, 5, 100)
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y_vals = np.linspace(-5, 5, 100)
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X, Y = np.meshgrid(x_vals, y_vals)
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Z = f(X - 2, Y) + f(X + 2, Y)
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Z = (Z > 0.4).astype(np.float32)
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Z *= np.random.rand(*Z.shape)
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for i, x in enumerate(x_vals):
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for j, y in enumerate(y_vals):
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2023-01-30 14:10:45 +00:00
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color = f"{hex(int(Z[j, i] * 255))[2:]}"
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if color == "0":
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2023-01-30 14:51:11 +00:00
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color = "#003"
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2023-01-30 14:10:45 +00:00
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else:
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color = "#" + 3 * color
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2023-01-30 11:11:52 +00:00
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plt.fill([x, x + 0.1, x + 0.1, x], [y, y, y + 0.1, y + 0.1], color=color)
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nb_cams = 32
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cam_poses = np.array(
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[[6 * np.cos(theta), 6 * np.sin(theta)] for theta in np.linspace(0, 2 * np.pi, nb_cams, endpoint=False)]
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)
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cam_rots = np.linspace(np.pi, 3 * np.pi, nb_cams, endpoint=False)
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cam2world_projs = np.array(
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[
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[[np.cos(theta), -np.sin(theta), cam_pose[0]], [np.sin(theta), np.cos(theta), cam_pose[1]], [0, 0, 1]]
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for theta, cam_pose in zip(cam_rots, cam_poses)
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]
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)
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for i in range(nb_cams):
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plt.plot(cam_poses[i][0], cam_poses[i][1], "ro")
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plt.text(cam_poses[i][0], cam_poses[i][1], str(i))
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x = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]]).T
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x = cam2world_projs[i] @ x
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plt.plot(x[0, :], x[1, :], "r-")
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2023-01-30 14:10:45 +00:00
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plt.xlim(-7, 7)
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plt.ylim(-7, 7)
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plt.axis("equal")
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2023-01-31 14:59:46 +00:00
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plt.savefig("data/peanut/peanut.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
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plt.close()
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2023-01-30 14:10:45 +00:00
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2023-01-30 11:11:52 +00:00
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# draw 1d image of the scene for each camera
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2023-01-31 15:40:40 +00:00
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for i in range(nb_cams):
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2023-01-31 14:59:46 +00:00
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2023-01-30 11:11:52 +00:00
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# sort pixels by distance to camera
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cam_pose = cam_poses[i]
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pixels_dist = np.linalg.norm(np.array([X.flatten(), Y.flatten()]).T - cam_pose, axis=1)
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2023-01-30 14:10:45 +00:00
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pixels_sort = np.argsort(pixels_dist)[::-1]
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2023-01-30 11:11:52 +00:00
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2023-01-30 14:51:11 +00:00
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x0 = -1
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x1 = 1
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2023-01-30 14:10:45 +00:00
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2023-01-31 14:59:46 +00:00
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plt.figure(f"img{i}")
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plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#000")
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plt.figure(f"mask{i}")
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plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#000")
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2023-01-30 14:10:45 +00:00
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for j in pixels_sort:
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x, y = X.flatten()[j], Y.flatten()[j]
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color = f"{hex(int(Z.flatten()[j] * 255))[2:]}"
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if color == "0":
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continue
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color = "#" + 3 * color
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px = np.array([[x, y, 1], [x + 0.1, y, 1], [x + 0.1, y + 0.1, 1], [x, y + 0.1, 1]]).T
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px = np.linalg.inv(cam2world_projs[i]) @ px
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2023-01-30 14:51:11 +00:00
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px /= px[0, :]
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2023-01-30 14:10:45 +00:00
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x0 = px[1, :].min()
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x1 = px[1, :].max()
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2023-01-31 14:59:46 +00:00
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plt.figure(f"img{i}")
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2023-01-30 14:51:11 +00:00
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plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color=color)
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2023-01-31 14:59:46 +00:00
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plt.figure(f"mask{i}")
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plt.fill([x0, x1, x1, x0], [0, 0, 0.2, 0.2], color="#fff")
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plt.figure(f"img{i}")
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2023-01-30 14:51:11 +00:00
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plt.xlim(-1, 1)
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plt.ylim(0, 0.2)
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plt.axis("off")
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2023-01-31 14:59:46 +00:00
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plt.savefig(f"data/peanut/images/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
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plt.close()
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2023-01-31 13:51:14 +00:00
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2023-01-31 14:59:46 +00:00
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plt.figure(f"mask{i}")
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plt.xlim(-1, 1)
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plt.ylim(0, 0.2)
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plt.axis("off")
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plt.savefig(f"data/peanut/masks/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
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plt.close()
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