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Merge branch 'bordel_laurent' of git.inpt.fr:tocard-inc/enseeiht/projet-be into bordel_laurent

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gdamms 2023-01-25 21:27:53 +01:00
parent 4af6119841 4b203cafc2
commit 0d52c9e351
18 changed files with 11189 additions and 163 deletions
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2
.gitignore vendored
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@ -2,6 +2,8 @@
data
assets
node_modules
*.blend1
# https://github.com/github/gitignore/blob/main/Python.gitignore

7
.vscode/extensions.json vendored Normal file
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@ -0,0 +1,7 @@
{
"recommendations": [
"editorconfig.editorconfig",
"njpwerner.autodocstring",
"ms-python.python"
]
}

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.vscode/launch.json vendored Normal file
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{
"version": "0.2.0",
"configurations": [
{
"name": "Python: Current File",
"type": "python",
"request": "launch",
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"justMyCode": true,
"env": {
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28
.vscode/settings.json vendored Normal file
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{
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"python.formatting.provider": "black",
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},
"nixEnvSelector.nixFile": "${workspaceRoot}/shell.nix",
}

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docs/package-lock.json generated Normal file
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docs/package.json Normal file
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{
"dependencies": {
"@slidev/cli": "^0.38.5",
"@slidev/theme-default": "^0.21.2",
"slidev-theme-academic": "^1.1.1"
}
}

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docs/slides.md Normal file
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---
theme: academic
class: text-white
coverAuthor: Laurent Fainsin, Damien Guillotin, Pierre-Eliot Jourdan
coverBackgroundUrl: >-
https://images.unsplash.com/photo-1655720408861-8b04c0724fd9?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8
coverBackgroundSource: unplash
coverBackgroundSourceUrl: https://unsplash.com/photos/Vc0CmuIfMg0
coverDate: '2023-01-05'
themeConfig:
paginationX: r
paginationY: t
paginationPagesDisabled:
- 1
title: Bureau d'étude de PI3D
---
# Bureau d'étude de PI3D
Sujet 6 - Reformulation du MVS par level sets
---

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flake.nix
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@ -22,6 +22,7 @@
gtk2 = pkgs.gtk2;
})
blender
nodejs
];
};
});

459
poetry.lock generated
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bokeh = ["bokeh", "chromedriver", "selenium"]
docs = ["furo", "sphinx-copybutton"]
mypy = ["contourpy[bokeh]", "docutils-stubs", "mypy (==0.991)", "types-Pillow"]
test = ["Pillow", "matplotlib", "pytest"]
test-no-images = ["pytest"]
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[package.extras]
dev = ["pyTest", "pyTest-cov"]
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name = "gitdb"
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plugins = ["setuptools"]
requirements-deprecated-finder = ["pip-api", "pipreqs"]
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]
[package.dependencies]
numpy = "*"
scipy = ">=1.0.0"
[[package]]
name = "pyparsing"
version = "3.0.9"
description = "pyparsing module - Classes and methods to define and execute parsing grammars"
category = "main"
optional = false
python-versions = ">=3.6.8"
files = [
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]
[package.extras]
diagrams = ["jinja2", "railroad-diagrams"]
[[package]]
name = "python-dateutil"
version = "2.8.2"
description = "Extensions to the standard Python datetime module"
category = "main"
optional = false
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
files = [
{file = "python-dateutil-2.8.2.tar.gz", hash = "sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86"},
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]
[package.dependencies]
six = ">=1.5"
[[package]]
name = "pyyaml"
version = "6.0"
@ -600,6 +1006,45 @@ typing-extensions = {version = ">=4.0.0,<5.0", markers = "python_version < \"3.9
[package.extras]
jupyter = ["ipywidgets (>=7.5.1,<8.0.0)"]
[[package]]
name = "scipy"
version = "1.9.3"
description = "Fundamental algorithms for scientific computing in Python"
category = "main"
optional = false
python-versions = ">=3.8"
files = [
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]
[package.dependencies]
numpy = ">=1.18.5,<1.26.0"
[package.extras]
dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
[[package]]
name = "setuptools"
version = "65.6.3"
@ -617,6 +1062,18 @@ docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "pygments-g
testing = ["build[virtualenv]", "filelock (>=3.4.0)", "flake8 (<5)", "flake8-2020", "ini2toml[lite] (>=0.9)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pip (>=19.1)", "pip-run (>=8.8)", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-timeout", "pytest-xdist", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
testing-integration = ["build[virtualenv]", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
[[package]]
name = "six"
version = "1.16.0"
description = "Python 2 and 3 compatibility utilities"
category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
files = [
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]
[[package]]
name = "smmap"
version = "5.0.0"
@ -704,4 +1161,4 @@ testing = ["coverage (>=6.2)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "70277d35aa55c1022524e37b75fcd711637ee16fb1737bc157244cf83d57efff"
content-hash = "8973ba110b5bc10710b9406373863d3874c9516bc2b82a58181727178cbd82a8"

3
pyproject.toml
View file

@ -1,5 +1,5 @@
[tool.poetry]
authors = ["Laurent Fainsin <laurentfainsin@protonmail.com>"]
authors = [""]
description = ""
license = "MIT"
name = "projet-be"
@ -12,6 +12,7 @@ rich = "^12.6.0"
opencv-python = "^4.6.0.66"
fake-bpy-module-latest = "^20230118"
matplotlib = "^3.6.3"
pymcubes = "^0.1.4"
[tool.poetry.group.dev.dependencies]
Flake8-pyproject = "^1.1.0"

59
src/blender/proj.py
View file

@ -1,25 +1,27 @@
import bpy
from mathutils import Matrix
#---------------------------------------------------------------
# ---------------------------------------------------------------
# 3x4 P matrix from Blender camera
#---------------------------------------------------------------
# ---------------------------------------------------------------
# BKE_camera_sensor_size
def get_sensor_size(sensor_fit, sensor_x, sensor_y):
if sensor_fit == 'VERTICAL':
if sensor_fit == "VERTICAL":
return sensor_y
return sensor_x
# BKE_camera_sensor_fit
def get_sensor_fit(sensor_fit, size_x, size_y):
if sensor_fit == 'AUTO':
if sensor_fit == "AUTO":
if size_x >= size_y:
return 'HORIZONTAL'
return "HORIZONTAL"
else:
return 'VERTICAL'
return "VERTICAL"
return sensor_fit
# Build intrinsic camera parameters from Blender camera data
#
# See notes on this in
@ -27,8 +29,8 @@ def get_sensor_fit(sensor_fit, size_x, size_y):
# as well as
# https://blender.stackexchange.com/a/120063/3581
def get_calibration_matrix_K_from_blender(camd):
if camd.type != 'PERSP':
raise ValueError('Non-perspective cameras not supported')
if camd.type != "PERSP":
raise ValueError("Non-perspective cameras not supported")
scene = bpy.context.scene
f_in_mm = camd.lens
scale = scene.render.resolution_percentage / 100
@ -38,10 +40,10 @@ def get_calibration_matrix_K_from_blender(camd):
sensor_fit = get_sensor_fit(
camd.sensor_fit,
scene.render.pixel_aspect_x * resolution_x_in_px,
scene.render.pixel_aspect_y * resolution_y_in_px
scene.render.pixel_aspect_y * resolution_y_in_px,
)
pixel_aspect_ratio = scene.render.pixel_aspect_y / scene.render.pixel_aspect_x
if sensor_fit == 'HORIZONTAL':
if sensor_fit == "HORIZONTAL":
view_fac_in_px = resolution_x_in_px
else:
view_fac_in_px = pixel_aspect_ratio * resolution_y_in_px
@ -52,14 +54,12 @@ def get_calibration_matrix_K_from_blender(camd):
# Parameters of intrinsic calibration matrix K
u_0 = resolution_x_in_px / 2 - camd.shift_x * view_fac_in_px
v_0 = resolution_y_in_px / 2 + camd.shift_y * view_fac_in_px / pixel_aspect_ratio
skew = 0 # only use rectangular pixels
skew = 0 # only use rectangular pixels
K = Matrix(
((s_u, skew, u_0),
( 0, s_v, v_0),
( 0, 0, 1)))
K = Matrix(((s_u, skew, u_0), (0, s_v, v_0), (0, 0, 1)))
return K
# Returns camera rotation and translation matrices from Blender.
#
# There are 3 coordinate systems involved:
@ -76,10 +76,7 @@ def get_calibration_matrix_K_from_blender(camd):
# - right-handed: positive z look-at direction
def get_3x4_RT_matrix_from_blender(cam):
# bcam stands for blender camera
R_bcam2cv = Matrix(
((1, 0, 0),
(0, -1, 0),
(0, 0, -1)))
R_bcam2cv = Matrix(((1, 0, 0), (0, -1, 0), (0, 0, -1)))
# Transpose since the rotation is object rotation,
# and we want coordinate rotation
@ -93,29 +90,29 @@ def get_3x4_RT_matrix_from_blender(cam):
# Convert camera location to translation vector used in coordinate changes
# T_world2bcam = -1*R_world2bcam @ cam.location
# Use location from matrix_world to account for constraints:
T_world2bcam = -1*R_world2bcam @ location
T_world2bcam = -1 * R_world2bcam @ location
# Build the coordinate transform matrix from world to computer vision camera
R_world2cv = R_bcam2cv@R_world2bcam
T_world2cv = R_bcam2cv@T_world2bcam
R_world2cv = R_bcam2cv @ R_world2bcam
T_world2cv = R_bcam2cv @ T_world2bcam
# put into 3x4 matrix
RT = Matrix((
R_world2cv[0][:] + (T_world2cv[0],),
R_world2cv[1][:] + (T_world2cv[1],),
R_world2cv[2][:] + (T_world2cv[2],)
))
RT = Matrix(
(R_world2cv[0][:] + (T_world2cv[0],), R_world2cv[1][:] + (T_world2cv[1],), R_world2cv[2][:] + (T_world2cv[2],))
)
return RT
def get_3x4_P_matrix_from_blender(cam):
K = get_calibration_matrix_K_from_blender(cam.data)
RT = get_3x4_RT_matrix_from_blender(cam)
return K@RT, K, RT
return K @ RT, K, RT
# ----------------------------------------------------------
if __name__ == "__main__":
# Insert your camera name here
cam = bpy.data.objects['Camera']
cam = bpy.data.objects["Camera"]
P, K, RT = get_3x4_P_matrix_from_blender(cam)
print("K")
print(K)
@ -132,5 +129,5 @@ if __name__ == "__main__":
# Bonus code: save the 3x4 P matrix into a plain text file
# Don't forget to import numpy for this
#nP = numpy.matrix(P)
#numpy.savetxt("/tmp/P3x4.txt", nP) # to select precision, use e.g. fmt='%.2f'
# nP = numpy.matrix(P)
# numpy.savetxt("/tmp/P3x4.txt", nP) # to select precision, use e.g. fmt='%.2f'

14
src/blender/render.py
View file

@ -54,14 +54,16 @@ for i, (phi, theta) in enumerate(poses):
# save camera matrices
with open(EXPORT_PATH / "cameras" / f"{i:04d}.pickle", "wb") as f:
pickle.dump({
"P": np.array(P),
"K": np.array(K),
"RT": np.array(RT),
}, f)
pickle.dump(
{
"P": np.array(P),
"K": np.array(K),
"RT": np.array(RT),
},
f,
)
print(f"Saved camera matrices: {i:04d}.pickle")
# render the frame
bpy.context.scene.frame_current = i
bpy.ops.render.render(write_still=False)

28
src/borders.py
View file

@ -25,21 +25,33 @@ def update_border(voxel_values, idx=None):
z_p1 = voxel_values[:, :, :-1]
z_p1 = np.concatenate((np.zeros((z_p1.shape[0], z_p1.shape[1], 1)), z_p1), axis=2)
return np.logical_or.reduce((voxel_values != x_m1, voxel_values != x_p1,
voxel_values != y_m1, voxel_values != y_p1,
voxel_values != z_m1, voxel_values != z_p1))
return np.logical_or.reduce(
(
voxel_values != x_m1,
voxel_values != x_p1,
voxel_values != y_m1,
voxel_values != y_p1,
voxel_values != z_m1,
voxel_values != z_p1,
)
)
# TODO: update only concidered voxels (idx)
if __name__ == '__main__':
voxel_values = np.array([[[np.sqrt(x**2 + y**2 + z**2) < 20 for z in np.arange(-10, 10, 1.0)] for y in np.arange(-10, 10, 1.0)] for x in np.arange(-10, 10, 1.0)])
if __name__ == "__main__":
voxel_values = np.array(
[
[[np.sqrt(x**2 + y**2 + z**2) < 20 for z in np.arange(-10, 10, 1.0)] for y in np.arange(-10, 10, 1.0)]
for x in np.arange(-10, 10, 1.0)
]
)
border = update_border(voxel_values)
# Plot voxel grid that are the border
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.scatter(np.where(voxel_values)[0], np.where(voxel_values)[1], np.where(voxel_values)[2], c='r', marker='o')
ax.scatter(np.where(border)[0], np.where(border)[1], np.where(border)[2], c='b', marker='o', s=1)
ax = fig.add_subplot(111, projection="3d")
ax.scatter(np.where(voxel_values)[0], np.where(voxel_values)[1], np.where(voxel_values)[2], c="r", marker="o")
ax.scatter(np.where(border)[0], np.where(border)[1], np.where(border)[2], c="b", marker="o", s=1)
plt.show()

40
src/fvi.py
View file

@ -92,7 +92,7 @@ def fast_voxel_intersect(start_, end_, origin_, step_, shape_) -> tuple[list, li
return intersections, voxels, voxels_idx
if __name__ == '__main__':
if __name__ == "__main__":
import matplotlib.pyplot as plt
def update_figure():
@ -102,18 +102,30 @@ if __name__ == '__main__':
# Plot hitted voxels
for voxel in voxels:
plt.fill([voxel[0], voxel[0] + step[0], voxel[0] + step[0], voxel[0]],
[voxel[1], voxel[1], voxel[1] + step[1], voxel[1] + step[1]],
color='#e25', alpha=0.5)
plt.fill(
[voxel[0], voxel[0] + step[0], voxel[0] + step[0], voxel[0]],
[voxel[1], voxel[1], voxel[1] + step[1], voxel[1] + step[1]],
color="#e25",
alpha=0.5,
)
for voxel_id in voxels_idx:
plt.fill([
origin[0] + voxel_id[0] * step[0], origin[0] + (voxel_id[0] + 1) * step[0],
origin[0] + (voxel_id[0] + 1) * step[0], origin[0] + voxel_id[0] * step[0]
], [
origin[1] + voxel_id[1] * step[1], origin[1] + voxel_id[1] * step[1],
origin[1] + (voxel_id[1] + 1) * step[1], origin[1] + (voxel_id[1] + 1) * step[1]
], color='#2e3', alpha=0.5)
plt.fill(
[
origin[0] + voxel_id[0] * step[0],
origin[0] + (voxel_id[0] + 1) * step[0],
origin[0] + (voxel_id[0] + 1) * step[0],
origin[0] + voxel_id[0] * step[0],
],
[
origin[1] + voxel_id[1] * step[1],
origin[1] + voxel_id[1] * step[1],
origin[1] + (voxel_id[1] + 1) * step[1],
origin[1] + (voxel_id[1] + 1) * step[1],
],
color="#2e3",
alpha=0.5,
)
# Plot line segment
plt.plot([start[0], end[0]], [start[1], end[1]], 'k-')
@ -127,7 +139,7 @@ if __name__ == '__main__':
plt.plot(end[0], end[1], 'ro')
# Plot voxel grid
plt.axis('equal')
plt.axis("equal")
plt.xlim((-10, 10))
plt.ylim((-10, 10))
plt.xticks(origin[0] + step[0] * np.arange(shape[0] + 1))
@ -137,7 +149,7 @@ if __name__ == '__main__':
def onkey(event):
global start, end
if event.key == ' ':
if event.key == " ":
start = np.random.rand(2) * 20 - 10
end = np.random.rand(2) * 20 - 10
update_figure()
@ -155,6 +167,6 @@ if __name__ == '__main__':
# Plot
fig = plt.figure()
fig.canvas.mpl_connect('key_press_event', onkey)
fig.canvas.mpl_connect("key_press_event", onkey)
update_figure()
plt.show()

92
src/intersec_line_voxel.py
View file

@ -1,14 +1,10 @@
import numpy as np
import matplotlib.pyplot as plt
from itertools import product
import matplotlib.pyplot as plt
import numpy as np
def check_line_voxel(
px, py, pz,
dx, dy, dz,
vx, vy, vz,
c
):
def check_line_voxel(px, py, pz, dx, dy, dz, vx, vy, vz, c):
"""Check if a line intersects a voxel.
Parameters:
@ -17,7 +13,6 @@ def check_line_voxel(
- vx, vy, vz: line direction coordinates
- c: voxel size
"""
# Compute the intersection bounds
kx1 = (px - dx) / vx
ky1 = (py - dy) / vy
@ -27,54 +22,27 @@ def check_line_voxel(
kz2 = (pz - dz + c) / vz
# Order the bounds
kxmin = np.min(np.concatenate([
kx1[:, np.newaxis],
kx2[:, np.newaxis]
], axis=1), axis=1)
kymin = np.min(np.concatenate([
ky1[:, np.newaxis],
ky2[:, np.newaxis]
], axis=1), axis=1)
kzmin = np.min(np.concatenate([
kz1[:, np.newaxis],
kz2[:, np.newaxis]
], axis=1), axis=1)
kxmax = np.max(np.concatenate([
kx1[:, np.newaxis],
kx2[:, np.newaxis]
], axis=1), axis=1)
kymax = np.max(np.concatenate([
ky1[:, np.newaxis],
ky2[:, np.newaxis]
], axis=1), axis=1)
kzmax = np.max(np.concatenate([
kz1[:, np.newaxis],
kz2[:, np.newaxis]
], axis=1), axis=1)
kxmin = np.min(np.concatenate([kx1[:, np.newaxis], kx2[:, np.newaxis]], axis=1), axis=1)
kymin = np.min(np.concatenate([ky1[:, np.newaxis], ky2[:, np.newaxis]], axis=1), axis=1)
kzmin = np.min(np.concatenate([kz1[:, np.newaxis], kz2[:, np.newaxis]], axis=1), axis=1)
kxmax = np.max(np.concatenate([kx1[:, np.newaxis], kx2[:, np.newaxis]], axis=1), axis=1)
kymax = np.max(np.concatenate([ky1[:, np.newaxis], ky2[:, np.newaxis]], axis=1), axis=1)
kzmax = np.max(np.concatenate([kz1[:, np.newaxis], kz2[:, np.newaxis]], axis=1), axis=1)
# Check if the bounds overlap
kmax = np.min(np.concatenate([
kxmax[:, np.newaxis],
kymax[:, np.newaxis],
kzmax[:, np.newaxis]
], axis=1), axis=1)
kmin = np.max(np.concatenate([
kxmin[:, np.newaxis],
kymin[:, np.newaxis],
kzmin[:, np.newaxis]
], axis=1), axis=1)
kmax = np.min(np.concatenate([kxmax[:, np.newaxis], kymax[:, np.newaxis], kzmax[:, np.newaxis]], axis=1), axis=1)
kmin = np.max(np.concatenate([kxmin[:, np.newaxis], kymin[:, np.newaxis], kzmin[:, np.newaxis]], axis=1), axis=1)
return kmin <= kmax
c = 1.0
points = np.array([[x, y, z] for x, y, z in product(
np.arange(-5.0, 4.0, c),
np.arange(-5.0, 4.0, c),
np.arange(-5.0, 4.0, c))
])
points = np.array(
[[x, y, z] for x, y, z in product(np.arange(-5.0, 4.0, c), np.arange(-5.0, 4.0, c), np.arange(-5.0, 4.0, c))]
)
while True:
fig = plt.figure()
ax = plt.axes(projection='3d')
ax = plt.axes(projection="3d")
d = np.random.rand(3) * 1 - 0.5
v = np.random.rand(3) * 1 - 0.5
@ -90,20 +58,20 @@ while True:
if not bool_vect[i]:
continue
ax.plot([px, px+c], [py, py], [pz, pz], 'b')
ax.plot([px, px+c], [py, py], [pz+c, pz+c], 'b')
ax.plot([px, px+c], [py+c, py+c], [pz, pz], 'b')
ax.plot([px, px+c], [py+c, py+c], [pz+c, pz+c], 'b')
ax.plot([px, px], [py, py+c], [pz, pz], 'b')
ax.plot([px, px], [py, py+c], [pz+c, pz+c], 'b')
ax.plot([px+c, px+c], [py, py+c], [pz, pz], 'b')
ax.plot([px+c, px+c], [py, py+c], [pz+c, pz+c], 'b')
ax.plot([px, px], [py, py], [pz, pz+c], 'b')
ax.plot([px, px], [py+c, py+c], [pz, pz+c], 'b')
ax.plot([px+c, px+c], [py, py], [pz, pz+c], 'b')
ax.plot([px+c, px+c], [py+c, py+c], [pz, pz+c], 'b')
ax.plot([px, px + c], [py, py], [pz, pz], "b")
ax.plot([px, px + c], [py, py], [pz + c, pz + c], "b")
ax.plot([px, px + c], [py + c, py + c], [pz, pz], "b")
ax.plot([px, px + c], [py + c, py + c], [pz + c, pz + c], "b")
ax.plot([px, px], [py, py + c], [pz, pz], "b")
ax.plot([px, px], [py, py + c], [pz + c, pz + c], "b")
ax.plot([px + c, px + c], [py, py + c], [pz, pz], "b")
ax.plot([px + c, px + c], [py, py + c], [pz + c, pz + c], "b")
ax.plot([px, px], [py, py], [pz, pz + c], "b")
ax.plot([px, px], [py + c, py + c], [pz, pz + c], "b")
ax.plot([px + c, px + c], [py, py], [pz, pz + c], "b")
ax.plot([px + c, px + c], [py + c, py + c], [pz, pz + c], "b")
# plot line
ax.plot([dx, dx+vx], [dy, dy+vy], [dz, dz+vz], 'g')
ax.plot([dx, dx + vx], [dy, dy + vy], [dz, dz + vz], "g")
plt.show()

62
src/main.py
View file

@ -1,9 +1,10 @@
import cv2
import numpy as np
from itertools import product
import pickle
from itertools import product
import cv2
import matplotlib.pyplot as plt
import mcubes
import numpy as np
from rich.progress import track
from borders import update_border
@ -16,10 +17,16 @@ Z_MIN, Z_MAX = -0.05, 0.05
nb_frame = 24
points = np.array([[x, y, z, 1.0] for x, y, z in product(
np.arange(X_MIN, X_MAX, VOXEL_SIZE),
np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
np.arange(Z_MIN, Z_MAX, VOXEL_SIZE))])
points = np.array(
[
[x, y, z, 1.0]
for x, y, z in product(
np.arange(X_MIN, X_MAX, VOXEL_SIZE),
np.arange(Y_MIN, Y_MAX, VOXEL_SIZE),
np.arange(Z_MIN, Z_MAX, VOXEL_SIZE),
)
]
)
mask = 255
@ -28,10 +35,10 @@ proj_mats = []
frames = []
for k in range(nb_frame):
frame = cv2.imread(f'data/torus/masks/Image{k:04}.png', cv2.IMREAD_GRAYSCALE)
frames.append(cv2.imread(f'data/torus/images/Image{k:04}.png', cv2.IMREAD_GRAYSCALE))
frame = cv2.imread(f"data/torus/masks/Image{k:04}.png", cv2.IMREAD_GRAYSCALE)
frames.append(cv2.imread(f"data/torus/images/Image{k:04}.png", cv2.IMREAD_GRAYSCALE))
with open(f"data/torus/cameras/{k:04d}.pickle", 'rb') as file:
with open(f"data/torus/cameras/{k:04d}.pickle", "rb") as file:
matrices = pickle.load(file)
proj_mat = matrices["P"]
proj_mats.append(proj_mat)
@ -39,16 +46,23 @@ for k in range(nb_frame):
positions.append(position)
cam_points = proj_mat @ points.T
cam_points /= cam_points[2,:]
cam_points /= cam_points[2, :]
cam_points = np.round(cam_points).astype(np.int32)
visible = np.logical_and.reduce((0 <= cam_points[0,:], cam_points[0,:] < frame.shape[1], 0 <= cam_points[1,:], cam_points[1,:] < frame.shape[0]))
cam_points = cam_points[:,visible]
points = points[visible,:]
visible = np.logical_and.reduce(
(
0 <= cam_points[0, :],
cam_points[0, :] < frame.shape[1],
0 <= cam_points[1, :],
cam_points[1, :] < frame.shape[0],
)
)
cam_points = cam_points[:, visible]
points = points[visible, :]
solid = frame[cam_points[1,:],cam_points[0,:]] == mask
cam_points = cam_points[:,solid]
points = points[solid,:]
solid = frame[cam_points[1, :], cam_points[0, :]] == mask
cam_points = cam_points[:, solid]
points = points[solid, :]
# for cam_point in cam_points.T:
# cv2.circle(frame, (cam_point[0], cam_point[1]), 2, (255*is_in[k], 0, 255*(not is_in[k])))
@ -73,7 +87,7 @@ for k in range(nb_frame):
voxel = np.zeros((int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE), int((Z_MAX-Z_MIN)/VOXEL_SIZE)))
idx = np.floor_divide(points[:, :3] - np.array([X_MIN, Y_MIN, Z_MIN]), VOXEL_SIZE).astype(int)
voxel[idx[:,0], idx[:,1], idx[:,2]] = 1
voxel[idx[:, 0], idx[:, 1], idx[:, 2]] = 1
border = update_border(voxel)
@ -86,14 +100,15 @@ border = update_border(voxel)
origin = np.array([X_MIN, Y_MIN, Z_MIN])
step = np.array([VOXEL_SIZE, VOXEL_SIZE, VOXEL_SIZE])
shape = np.array([int((X_MAX-X_MIN)/VOXEL_SIZE), int((Y_MAX-Y_MIN)/VOXEL_SIZE), int((Z_MAX-Z_MIN)/VOXEL_SIZE)])
shape = np.array(
[int((X_MAX - X_MIN) / VOXEL_SIZE), int((Y_MAX - Y_MIN) / VOXEL_SIZE), int((Z_MAX - Z_MIN) / VOXEL_SIZE)]
)
for idx in track(np.argwhere(border)):
# coordonnées du centre du voxel
start = np.array([
X_MIN + (idx[0] + 0.5) * VOXEL_SIZE,
Y_MIN + (idx[1] + 0.5) * VOXEL_SIZE,
Z_MIN + (idx[2] + 0.5) * VOXEL_SIZE])
start = np.array(
[X_MIN + (idx[0] + 0.5) * VOXEL_SIZE, Y_MIN + (idx[1] + 0.5) * VOXEL_SIZE, Z_MIN + (idx[2] + 0.5) * VOXEL_SIZE]
)
# array qui contiendra les nuances de gris des frames qui voient le voxel
values = []
@ -129,6 +144,5 @@ for idx in track(np.argwhere(border)):
voxel[idx[0], idx[1], idx[2]] = 0
vertices, triangles = mcubes.marching_cubes(voxel, 0)
mcubes.export_obj(vertices, triangles, "result.obj")

14
src/matrices_reader.py
View file

@ -12,23 +12,25 @@ def matrices_reader(path: str) -> list[np.ndarray]:
list[np.ndarray]: list of projection matrix
"""
with open(path, 'r') as f:
with open(path, "r") as f:
lines = f.readlines()
k = 0
world_matrices = []
while k+3 < len(lines):
while k + 3 < len(lines):
# Match matrices one by one
mat_str = ""
for line in lines[k:k+4]:
for line in lines[k : k + 4]:
mat_str += line
float_reg = r"(-|\d|\.|e)+"
res = re.search(
f"Matrix\(\(\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n\ +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\)\)\)", mat_str)
f"Matrix\(\(\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\),\n\ +\(({float_reg}), ({float_reg}), ({float_reg}), ({float_reg})\)\)\)",
mat_str,
)
# Convert string to np.ndarray
values = [float(res.group(i)) for i in range(1,len(res.groups()) + 1, 2)]
world_mat = np.array([[values[4*i + j] for j in range(4)] for i in range(3)])
values = [float(res.group(i)) for i in range(1, len(res.groups()) + 1, 2)]
world_mat = np.array([[values[4 * i + j] for j in range(4)] for i in range(3)])
world_matrices.append(world_mat)
k += 4

3
src/test.py
View file

@ -4,8 +4,7 @@ nb_frame = 24
for k in range(nb_frame):
with open(f"/tmp/cameras/{k:04d}.pickle", 'rb') as file:
with open(f"/tmp/cameras/{k:04d}.pickle", "rb") as file:
proj_mat = pickle.load(file)["P"]
print(k, proj_mat)