4384319a03
Co-authored-by: Laureηt <laurent@fainsin.bzh> Co-authored-by: pejour <pejour@users.noreply.github.com>
124 lines
4 KiB
Python
124 lines
4 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import cv2
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VOXEL_SIZE = 0.1
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X_MIN, X_MAX = -5, 5
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Y_MIN, Y_MAX = -5, 5
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x_vals = np.arange(X_MIN + VOXEL_SIZE / 2, X_MAX, VOXEL_SIZE)
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y_vals = np.arange(Y_MIN + VOXEL_SIZE / 2, Y_MAX, VOXEL_SIZE)
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image_length = 1500
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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, 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 j, x in enumerate(x_vals):
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for i, y in enumerate(y_vals):
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color = f"{hex(int(Z[i, j] * 255))[2:]}"
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if color == "0":
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color = "#003"
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else:
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color = "#" + 3 * color
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plt.fill([x - VOXEL_SIZE/2, x + VOXEL_SIZE/2, x + VOXEL_SIZE/2, x - VOXEL_SIZE/2],
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[y - VOXEL_SIZE/2, y - VOXEL_SIZE/2, y + VOXEL_SIZE/2, y + VOXEL_SIZE/2], 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)]
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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]],
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[np.sin(theta), np.cos(theta), cam_pose[1]],
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[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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x = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]])
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x = cam2world_projs[i] @ x.T
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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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plt.plot(x[0, :], x[1, :], "r-")
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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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plt.axis("off")
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plt.savefig("data/peanut/peanut_cams.png", dpi=300,
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bbox_inches="tight", pad_inches=0, transparent=True)
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plt.close()
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# draw 1d image of the scene for each camera
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for i in range(nb_cams):
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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(
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np.array([X.flatten(), Y.flatten()]).T - cam_pose, axis=1)
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pixels_sort = np.argsort(pixels_dist)[::-1]
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x0 = -1
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x1 = 1
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img = np.zeros((100, image_length, 3), dtype=np.uint8)
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mask = np.zeros((100, image_length, 3), dtype=np.uint8)
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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 = int(Z.flatten()[j] * 255)
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if color == 0:
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continue
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RT = np.linalg.inv(cam2world_projs[i])[:-1, :]
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px = np.array([[x - VOXEL_SIZE/2, y - VOXEL_SIZE/2, 1],
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[x + VOXEL_SIZE/2, y - VOXEL_SIZE/2, 1],
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[x + VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1],
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[x - VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1]])
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px = RT @ px.T
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px /= px[0, :]
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px += np.array([[0], [1.0]])
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px *= 0.5 * np.array([[1], [image_length]])
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x0 = px[1, :].min()
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x1 = px[1, :].max()
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img[:, int(x0):int(x1), :] = np.array(
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3 * [color], dtype=np.uint8)
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mask[:, int(x0):int(x1), :] = np.array([255, 255, 255], dtype=np.uint8)
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# x, y = X_MIN + 27 * VOXEL_SIZE, Y_MIN + 66 * VOXEL_SIZE
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# RT = np.linalg.inv(cam2world_projs[i])[:-1, :]
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# px = np.array([[x + VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1],
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# [x, y, 1],
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# [x + VOXEL_SIZE, y, 1],
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# [x + VOXEL_SIZE, y + VOXEL_SIZE, 1],
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# [x, y + VOXEL_SIZE, 1]])
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# px = RT @ px.T
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# px /= px[0, :]
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# px += np.array([[0], [1.0]])
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# px *= 0.5 * np.array([[1], [image_length]])
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# img[48:52, int(px[1, 0]-1):int(px[1, 0]+1), :] = np.array([255, 0, 0], dtype=np.uint8)
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# img[48:52, int(px[1, 1]-1):int(px[1, 1]+1), :] = np.array([255, 255, 0], dtype=np.uint8)
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# img[48:52, int(px[1, 2]-1):int(px[1, 2]+1), :] = np.array([0, 255, 255], dtype=np.uint8)
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# img[48:52, int(px[1, 3]-1):int(px[1, 3]+1), :] = np.array([255, 0, 255], dtype=np.uint8)
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# img[48:52, int(px[1, 4]-1):int(px[1, 4]+1), :] = np.array([0, 255, 0], dtype=np.uint8)
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cv2.imwrite(f"data/peanut/images/Image{i:04}.png", img)
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cv2.imwrite(f"data/peanut/masks/Image{i:04}.png", mask)
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