AAAHAAAHAHHAHAHAHAHAHHAHAHAH
Co-authored-by: Damien Guillotin <damguillotin@gmail.com> Co-authored-by: pejour <pejour@users.noreply.github.com>
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@ -53,7 +53,7 @@ $\mathcal{V}_t = \{ \textbf{Q} \in \mathbb{R}^3, u(\textbf{Q}) = t \}, \quad t\i
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<img src="figs/lvl7_2D.png" class="m-auto h-110"/>
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<span class="absolute bottom-0 font-extralight mb-1 mr-2 right-0 text-xs">Variational principles, surface evolution, PDEs, level set methods, and the stereo problem - Olivier Faugeras, Renaud Keriven, 1998</span>
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<a href="https://hal.inria.fr/inria-00073673/document" class="absolute bottom-0 font-extralight mb-1 mr-2 right-0 text-xs">Variational principles, surface evolution, PDEs, level set methods, and the stereo problem - Olivier Faugeras, Renaud Keriven, 1998</a>
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---
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@ -67,18 +67,34 @@ $\mathcal{V}_t = \{ \textbf{Q} \in \mathbb{R}^3, u(\textbf{Q}) = t \}, \quad t\i
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## Mise à jour du volume
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consensus blabla
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- Sélection des voxels sur la bordure du "marbre"
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- Vérification de la visibilité du voxel par toutes les caméras
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- Récupération des couleurs / niveaux de gris visibles par les caméras
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- Consensus sur la couleur / niveau de gris du voxel étudié
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- Remplissage si consensus, creusage sinon
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---
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## Initialisation du volume
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ones ou alors shape from silouhette
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- Définition d'une taille limite:
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- $x \in [-1, 1]$
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- $y \in [-1, 1]$
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- $z \in [-1, 1]$
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- Définition d'une résolution (un pas): $5.10^{-2}$
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- Initialisation des valeurs du marbre:
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- Uniforme (`np.zeros` ou `np.ones`)
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- Shape From Silouhette (BE4)
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---
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## Exemple Shape from Silouhette
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<img src="https://www.researchgate.net/profile/Silvio-Savarese/publication/221625880/figure/fig1/AS:652956261158913@1532688312594/Shape-from-Silhouettes-The-silhouette-and-camera-location-for-each-view-forms-a-cone.png" class="m-auto mt-2 h-110">
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<a href="https://ieeexplore.ieee.org/document/1024034" class="absolute bottom-0 font-extralight mb-1 mr-2 right-0 text-xs">Implementation of a Shadow Carving System for Shape Capture, doi: 10.1109/TDPVT.2002.1024034</a>
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---
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## Raytracing
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51
src/draw.py
51
src/draw.py
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@ -19,7 +19,11 @@ 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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color = f"#{hex(int(Z[j, i] * 255))[2:]}{hex(int(Z[j, i] * 255))[2:]}{hex(int(Z[j, i] * 255))[2:]}"
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color = f"{hex(int(Z[j, i] * 255))[2:]}"
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if color == "0":
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color = "#f00"
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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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@ -44,16 +48,43 @@ for i in range(nb_cams):
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plt.plot(x[0, :], x[1, :], "r-")
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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(np.array([X.flatten(), Y.flatten()]).T - cam_pose, axis=1)
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X_ = X.flatten()[np.argsort(pixels_dist)]
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Y_ = Y.flatten()[np.argsort(pixels_dist)]
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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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# draw 1d image of the scene for each camera
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for i in range(2):
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plt.figure()
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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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pixels_sort = np.argsort(pixels_dist)[::-1]
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px = np.array([[-5, -5, 1], [5, -5, 1], [5, 5, 1], [-5, 5, 1]]).T
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px = np.linalg.inv(cam2world_projs[i]) @ px
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px /= px[1, :]
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x0 = px[1, :].min()
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x1 = px[1, :].max()
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plt.fill([x0, x1, x1, x0], [0, 0, 1, 1], color="r")
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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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px /= px[1, :]
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x0 = px[1, :].min()
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x1 = px[1, :].max()
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plt.fill([x0, x1, x1, x0], [0, 0, 1, 1], color=color)
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plt.axis("equal")
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plt.show()
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