le 2d preque réussi ?
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gdamms
parent
dd20e360fb
commit
cf1f2d76a9
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@ -2,11 +2,9 @@ import numpy as np
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import matplotlib.pyplot as plt
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def update_border(voxel_values, idx=None):
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def update_border(voxel_values):
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voxel_values = voxel_values > 0
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if idx is None:
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if len(voxel_values.shape) == 3:
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x_m1 = voxel_values[1:, :, :]
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x_m1 = np.concatenate((x_m1, np.zeros((1, x_m1.shape[1], x_m1.shape[2]))), axis=0)
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@ -36,7 +34,27 @@ def update_border(voxel_values, idx=None):
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)
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)
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# TODO: update only concidered voxels (idx)
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elif len(voxel_values.shape) == 2:
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x_m1 = voxel_values[1:, :]
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x_m1 = np.concatenate((x_m1, np.zeros((1, x_m1.shape[1]))), axis=0)
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x_p1 = voxel_values[:-1, :]
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x_p1 = np.concatenate((np.zeros((1, x_p1.shape[1])), x_p1), axis=0)
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y_m1 = voxel_values[:, 1:]
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y_m1 = np.concatenate((y_m1, np.zeros((y_m1.shape[0], 1))), axis=1)
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y_p1 = voxel_values[:, :-1]
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y_p1 = np.concatenate((np.zeros((y_p1.shape[0], 1)), y_p1), axis=1)
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return np.logical_or.reduce(
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(
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voxel_values != x_m1,
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voxel_values != x_p1,
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voxel_values != y_m1,
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voxel_values != y_p1,
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)
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)
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if __name__ == "__main__":
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28
src/draw.py
28
src/draw.py
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@ -1,5 +1,6 @@
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import matplotlib.pyplot as plt
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import numpy as np
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import cv2
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def f(x, y):
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@ -17,6 +18,7 @@ Z = (Z > 0.4).astype(np.float32)
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Z *= np.random.rand(*Z.shape)
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start = np.array([-3.75, -0.25])
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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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color = f"{hex(int(Z[j, i] * 255))[2:]}"
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@ -25,7 +27,7 @@ for i, x in enumerate(x_vals):
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else:
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color = "#" + 3 * color
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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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# plt.plot(start[0], start[1], "ro")
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nb_cams = 32
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cam_poses = np.array(
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@ -50,10 +52,11 @@ for i in range(nb_cams):
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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.show()
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# draw 1d image of the scene for each camera
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for i in [0, 8, 16, 24]:
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for i in range(13, 21):
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plt.figure(f"cam {i}")
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# sort pixels by distance to camera
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cam_pose = cam_poses[i]
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@ -84,7 +87,24 @@ for i in [0, 8, 16, 24]:
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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/images/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
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plt.savefig(f"/tmp/Image{i:04}.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
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# plt.close()
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plt.show()
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RT = np.linalg.inv(cam2world_projs[i])[:-1, :]
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proj = RT @ np.array([start[0], start[1], 1.0])
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proj /= proj[0]
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plt.plot(proj[1], 0.1, "ro")
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plt.figure()
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frame = cv2.imread(f"/tmp/Image{i:04}.png")
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proj += np.array([0, 1.0])
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proj *= 0.5 * np.array([1, frame.shape[1]])
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proj = np.round(proj).astype(np.int32)
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plt.imshow(frame, cmap="gray")
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plt.plot(proj[1], frame.shape[0] / 2, "ro")
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plt.show()
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# plt.show()
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224
src/sfs2d.py
Normal file
224
src/sfs2d.py
Normal file
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@ -0,0 +1,224 @@
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import numpy as np
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import cv2
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import matplotlib.pyplot as plt
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from itertools import product
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from rich.progress import track
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from borders import update_border
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from fvi import fast_voxel_intersect
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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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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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def plot_camera(cam2world_proj, name, color):
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points = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]]).T
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points = cam2world_proj @ points
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plt.plot(points[0, 0], points[1, 0], color=color, marker="o")
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plt.plot(points[0, :], points[1, :], color=color, linestyle="-")
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plt.text(points[0, 0], points[1, 0], s=name, color=color)
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def plot_voxels(voxels, color, alpha, background):
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if background:
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plt.fill([X_MIN, X_MAX, X_MAX, X_MIN], [Y_MIN, Y_MIN, Y_MAX, Y_MAX], color="#000")
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for i, j in np.argwhere(voxels):
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x, y = X_MIN + i * VOXEL_SIZE, Y_MIN + j * VOXEL_SIZE
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plt.fill([x, x + VOXEL_SIZE, x + VOXEL_SIZE, x], [y, y, y + VOXEL_SIZE, y + VOXEL_SIZE], color=color, alpha=alpha)
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nb_frame = 32
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points = np.array(
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[
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[x, y, 1.0]
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for x, y in product(
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np.arange(X_MIN, X_MAX, VOXEL_SIZE),
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np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
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)
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]
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)
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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_frame, endpoint=False)]
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)
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cam_rots = np.linspace(np.pi, 3 * np.pi, nb_frame, 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]], [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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mask = 255
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positions = []
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proj_mats = []
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frames = []
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for k in range(nb_frame):
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frame = cv2.imread(
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f"data/peanut/masks/Image{k:04}.png", cv2.IMREAD_GRAYSCALE)[0, :]
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frames.append(cv2.imread(f"data/peanut/images/Image{k:04}.png", cv2.IMREAD_GRAYSCALE)[0, :])
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# print(f"frame.shape: {frame.shape}")
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RT = np.linalg.inv(cam2world_projs[k])[:-1, :]
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# a = np.array([0.0, 0.0, 1.0])
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cam_points = RT @ points.T
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cam_points /= cam_points[0]
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cam_points += np.array([[0], [1.0]])
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cam_points *= 0.5 * np.array([[1], [frame.shape[0]]])
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cam_points = np.round(cam_points).astype(np.int32)
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# print(f"cam_points: {cam_points}")
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visible = np.logical_and.reduce(
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(
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0 <= cam_points[1, :],
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cam_points[1, :] < frame.shape[0],
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)
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)
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cam_points = cam_points[:, visible]
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points = points[visible, :]
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solid = frame[cam_points[1, :]] == mask
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cam_points = cam_points[:, solid]
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points = points[solid, :]
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voxel = np.zeros((int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE)))
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idx = np.floor_divide(points[:, :2] - np.array([X_MIN, Y_MIN]), VOXEL_SIZE).astype(int)
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voxel[idx[:, 0], idx[:, 1]] = 1
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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.swapaxes(Z, 0, 1)
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plt.figure()
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plt.axis("equal")
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plot_voxels(Z, "#fff", 1.0, True)
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plot_voxels(voxel, "#00f", 0.5, False)
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for i in range(nb_frame):
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plot_camera(cam2world_projs[i], str(i), "#f00")
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origin = np.array([X_MIN, Y_MIN])
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step = np.array([VOXEL_SIZE, VOXEL_SIZE])
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shape = np.array([int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE)])
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for _ in range(5):
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border = update_border(voxel)
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plt.figure()
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plt.axis("equal")
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plot_voxels(voxel, "#fff", 1.0, True)
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# plot_voxels(border, "#00f", 0.5, False)
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for i in range(nb_frame):
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plot_camera(cam2world_projs[i], str(i), "#f00")
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for i, j in track(np.argwhere(border)):
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x, y = X_MIN + i * VOXEL_SIZE, Y_MIN + j * VOXEL_SIZE
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start = np.array([x, y]) + 0.5 * step
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# plt.fill([x, x + VOXEL_SIZE, x + VOXEL_SIZE, x], [y, y, y + VOXEL_SIZE, y + VOXEL_SIZE], "#0f0", alpha=0.7)
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values = []
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for k in range(nb_frame):
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# plot_camera(cam2world_projs[k], str(k), "#0f0")
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end = cam_poses[k]
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_, _, voxels_intersected = fast_voxel_intersect(start, end, origin, step, shape)
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voxels_intersected = np.array(voxels_intersected, dtype=np.int32)
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# for voxel_id in voxels_intersected:
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# if not voxel[voxel_id[0], voxel_id[1]]:
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# continue
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# plt.fill(
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# [
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# origin[0] + voxel_id[0] * step[0],
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# origin[0] + (voxel_id[0] + 1) * step[0],
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# origin[0] + (voxel_id[0] + 1) * step[0],
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# origin[0] + voxel_id[0] * step[0],
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# ],
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# [
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# origin[1] + voxel_id[1] * step[1],
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# origin[1] + voxel_id[1] * step[1],
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# origin[1] + (voxel_id[1] + 1) * step[1],
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# origin[1] + (voxel_id[1] + 1) * step[1],
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# ],
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# color="#f00",
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# alpha=0.3,
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# )
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if len(voxels_intersected) == 0:
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visible = True
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else:
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visible = voxel[voxels_intersected[:, 0], voxels_intersected[:, 1]].sum() == 0
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if visible:
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RT = np.linalg.inv(cam2world_projs[k])[:-1, :]
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proj = RT @ np.array([start[0], start[1], 1.0])
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proj /= proj[0]
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proj += np.array([0, 1.0])
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proj *= 0.5 * np.array([1, frames[k].shape[0]])
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proj = np.round(proj).astype(np.int32)
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values.append(frames[k][proj[1]])
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# plt.figure()
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# plt.imshow(np.repeat(frames[k][np.newaxis, :], 100, axis=0), cmap="gray")
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# plt.plot(proj[1], 50, "ro")
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# plt.show()
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# else:
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# plot_camera(cam2world_projs[k], str(k), "#f00")
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if np.std(values) < 2.0:
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voxel[i, j] = 1
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color = "#0f0"
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else:
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voxel[i, j] = 0
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color = "#f00"
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plt.fill(
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[
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origin[0] + i * step[0],
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origin[0] + (i + 1) * step[0],
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origin[0] + (i + 1) * step[0],
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origin[0] + i * step[0],
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],
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[
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origin[1] + j * step[1],
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origin[1] + j * step[1],
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origin[1] + (j + 1) * step[1],
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origin[1] + (j + 1) * step[1],
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],
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color=color,
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alpha=0.3,
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)
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plt.figure()
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plt.axis("equal")
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plot_voxels(Z, "#fff", 1.0, True)
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plot_voxels(voxel, "#00f", 0.5, False)
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plt.show()
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