yay enkore plus de slides

Co-authored-by: pejour <pejour@users.noreply.github.com>

docs/slides.md

@@ -2,8 +2,7 @@
 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
+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'
@@ -27,6 +26,12 @@ Sujet 6 - Reformulation du MVS par level sets
 
 ---
 
+## Level sets 2D animé
+
+<img src="figs/lvl7_2D.gif" class="m-auto mt-5"/>
+
+---
+
 ## Exemple Level sets 2D
 
 <img src="figs/lvl7_2D.png" class="m-auto h-110"/>
@@ -36,3 +41,39 @@ Sujet 6 - Reformulation du MVS par level sets
     Variational principles, surface evolution, PDEs, level set methods, and the stereo problem - Olivier Faugeras, Renaud Keriven, 1998
   </Footnote>
 </Footnotes>
+
+----
+
+## Exemple Level sets 3D
+
+<img src="figs/lvl7_3D.gif" class="m-auto -mt-1 h-125"/>
+
+---
+
+## Approximation du volume
+
+$\mu_t = \{ Q \in \mathbb{R}^3, u(Q) = t \}, t\in [0,1]\ \text{ou}\ t \in \{0, 1\}$
+
+---
+
+## Raytracing
+
+<img src="https://cdn.discordapp.com/attachments/953586522572066826/1068141883810914427/fvi2.png" class="m-auto -mt-10 h-125"/>
+
+---
+
+## Raytracing
+
+<img src="https://cdn.discordapp.com/attachments/953586522572066826/1068141884242931712/fvi4.png" class="m-auto -mt-10 h-125"/>
+
+---
+
+## Raytracing
+
+<img src="https://cdn.discordapp.com/attachments/953586522572066826/1068141884679147602/fvi6.png" class="m-auto -mt-10 h-125"/>
+
+---
+
+## Raytracing
+
+<img src="https://cdn.discordapp.com/attachments/953586522572066826/1068141885056622661/fvi8.png" class="m-auto -mt-10 h-125"/>

src/levelset.py

@@ -1,9 +1,9 @@
+import imageio.v2 as imageio
+import matplotlib.pyplot as plt
 import mcubes
 import numpy as np
-import matplotlib.pyplot as plt
-import imageio.v2 as imageio
 import perlin_noise
-
+from rich.progress import track
 
 # X, Y, Z = np.mgrid[:100, :100, :100]
 # V = np.sqrt((X - 50)**2 + (Y - 50)**2 + (Z - 50)**2)
@@ -15,25 +15,29 @@ import perlin_noise
 noise = perlin_noise.PerlinNoise(octaves=6, seed=1)
 
 X, Y = np.mgrid[:100, :100]
-V = [[10 * noise([x/100, y/100]) + np.sqrt((x-50)**2 + (y-50)**2) for y in range(100)] for x in range(100)]
+V = [[10 * noise([x / 100, y / 100]) + np.sqrt((x - 50) ** 2 + (y - 50) ** 2) for y in range(100)] for x in range(100)]
 V = np.array(V)
 V = (V - V.min()) / (V.max() - V.min())
 
 frame_list = []
-for i in np.linspace(0.05, 0.55, 100):
+for i in track(np.linspace(0.05, 0.55, 100)):
     plt.clf()
     plt.subplot(1, 2, 1)
     plt.imshow(V, cmap="gray")
     plt.contour(V, [i], colors="r")
     plt.plot([0, 0, 100, 100, 0], [0, 100, 100, 0, 0], "k-")
-    plt.axis('off')
+    plt.xlim(0, 100)
+    plt.ylim(0, 100)
+    plt.axis("off")
 
     plt.subplot(1, 2, 2)
     plt.imshow(V > i, cmap="gray")
     plt.plot([0, 0, 100, 100, 0], [0, 100, 100, 0, 0], "k-")
-    plt.axis('off')
+    plt.xlim(0, 100)
+    plt.ylim(0, 100)
+    plt.axis("off")
 
-    plt.savefig(f"/tmp/frame.png")
+    plt.savefig(f"/tmp/frame.png", dpi=300, bbox_inches="tight", pad_inches=0, transparent=True)
     frame_list.append(imageio.imread(f"/tmp/frame.png"))
 
-imageio.mimsave('picture.gif', frame_list + frame_list[::-1], fps=60)
+imageio.mimsave("docs/figs/lvl7.gif", frame_list + frame_list[::-1], fps=60)