From 6e7ebcfc41423b8a43db3033c76043dc6e12f84d Mon Sep 17 00:00:00 2001 From: "Claude Haiku 4.5 (1M context)" Date: Wed, 14 Oct 2026 06:44:47 +0200 Subject: [PATCH] Add: 05-0d GANs -- portraits adversariaux et moment NFT (jalon 4 de #16774) DCGAN sur les portraits Olivetti, execute sur GPU : test de copie par controle photo vue / jamais vue (3 montages x 3 graines), detecteur spectral (Durall et al. 2020), marche latente, longueur de description generateur contre corpus compresse. Ligne 05-0d au README du rayon. Co-Authored-By: Claude Opus 5.5 (1M context) --- .../05-0d-GANs-Portraits-Moment-NFT.ipynb | 1176 +++++++++++++++++ .../GenAI/Image/05-History/README.md | 2 + 2 files changed, 1178 insertions(+) create mode 100644 MyIA.AI.Notebooks/GenAI/Image/05-History/05-0d-GANs-Portraits-Moment-NFT.ipynb diff --git a/MyIA.AI.Notebooks/GenAI/Image/05-History/05-0d-GANs-Portraits-Moment-NFT.ipynb b/MyIA.AI.Notebooks/GenAI/Image/05-History/05-0d-GANs-Portraits-Moment-NFT.ipynb new file mode 100644 index 0000000000..e990aba7fe --- /dev/null +++ b/MyIA.AI.Notebooks/GenAI/Image/05-History/05-0d-GANs-Portraits-Moment-NFT.ipynb @@ -0,0 +1,1176 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c05d00", + "metadata": { + "papermill": { + "duration": 0.005745, + "end_time": "2026-10-14T04:37:33.343782+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:33.338037+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# 05-0d — GANs : des portraits adversariaux au moment NFT\n", + "\n", + "**Navigation** : [↑ 05-History](README.md) | [← 05-0 : Générateurs symboliques](05-0-Generateurs-Symboliques.ipynb) | [05-1 : DiscoDiffusion →](05-1-DiscoDiffusion-CLIP-Guided-Diffusion.ipynb)\n", + "\n", + "> **Notebook rétrospectif — Racines pré-Stable-Diffusion.** Quatrième jalon de\n", + "> l'[Epic #16774](https://github.com/jsboige/CoursIA/issues/16774) : le moment où\n", + "> l'art génératif cesse d'écrire ses règles et les **apprend** d'un corpus. Les jalons\n", + "> précédents (moteurs symboliques, démoscène, low-complexity art) mesuraient une\n", + "> description courte qui engendre une image riche ; ce jalon mesure ce que coûte,\n", + "> et ce que risque, une description **apprise**.\n", + "\n", + "**La thèse du notebook en une ligne** : un GAN est un programme génératif comme les\n", + "autres, mais sa description est un jeu de poids **plus lourd que son corpus**, et\n", + "la question qui a agité le marché de l'art (« qui est l'auteur ? ») a une moitié\n", + "mesurable : le générateur **copie-t-il** ses exemples ?\n", + "\n", + "## Ce qui s'est passé, dans l'ordre\n", + "\n", + "| Date | Événement | Source |\n", + "|---|---|---|\n", + "| 2014 | Goodfellow et al. publient les *Generative Adversarial Nets* : un générateur $G$ et un discriminateur $D$ jouent le jeu min-max $\\min_G \\max_D \\; \\mathbb{E}_x[\\log D(x)] + \\mathbb{E}_z[\\log(1 - D(G(z)))]$ | [arXiv:1406.2661](https://arxiv.org/abs/1406.2661) |\n", + "| 2015 | Radford, Metz et Chintala donnent les **règles d'architecture** qui rendent l'entraînement convolutif stable (DCGAN) | [arXiv:1511.06434](https://arxiv.org/abs/1511.06434) |\n", + "| 25 oct. 2018 | *Edmond de Belamy, from La Famille de Belamy*, du collectif parisien Obvious, est adjugé **432 500 $** chez Christie's New York (estimation 7 000-10 000 $). Le GAN a été nourri de 15 000 portraits peints du XIVe au XXe siècle ; la « signature » en bas à droite est la formule min-max elle-même | [Christie's](https://www.christies.com/en/stories/a-collaboration-between-two-artists-one-human-one-a-machine-0cd01f4e232f4279a525a446d60d4cd1), [NYT](https://www.nytimes.com/2018/10/25/arts/design/ai-art-sold-christies.html) |\n", + "| oct. 2018 | Robbie Barrat, qui publiait sur GitHub du code et des réseaux pré-entraînés de portraits, indique que les sorties d'Obvious sont presque identiques à celles de ses modèles : la question d'auteur se déplace du réseau vers le code et le corpus | [The Verge](https://www.theverge.com/2018/10/23/18013190/ai-art-portrait-auction-christies-belamy-obvious-robbie-barrat-gans) |\n", + "| 2021 | Boom des NFT. Les ventes génératives les plus spectaculaires ne sont pas des GANs mais des **programmes** : *Fidenza* de Tyler Hobbs (Art Blocks), dont l'exemplaire #313 se revend 1 000 ETH (environ 3,3 M$) en août 2021 | [Hypebeast](https://hypebeast.com/2021/8/art-blocks-fidenza-nft-1400-to-3-million-ethereum), [Texas Monthly](https://www.texasmonthly.com/arts-entertainment/art-blocks-generative-artists/) |\n", + "\n", + "Le rapprochement « GANs vendus à prix d'or à l'époque des NFT » condense donc deux\n", + "moments distincts : la vente GAN de référence précède de trois ans le boom NFT, et\n", + "ce boom a surtout couronné l'art génératif **par code**, c'est-à-dire l'héritier\n", + "direct des moteurs symboliques du jalon 1. Le notebook garde la technique et laisse\n", + "le marché à sa chronologie.\n", + "\n", + "## Ce que le notebook exécute\n", + "\n", + "1. Un **DCGAN** conforme aux règles de Radford et al., entraîné sur 400 portraits\n", + " (base Olivetti, AT&T Laboratories Cambridge, 40 personnes × 10 photos).\n", + "2. **La question de la copie**, posée comme une expérience contrôlée : chaque\n", + " personne a une photo vue à l'entraînement et une photo jamais vue. Un générateur\n", + " qui copie produit des images plus proches des photos vues.\n", + "3. **L'empreinte spectrale** : Durall et al. (CVPR 2020) affirment que le\n", + " suréchantillonnage convolutif empêche les GANs de reproduire le spectre des\n", + " images naturelles, au point de les détecter « jusqu'à 100 % ». On le mesure.\n", + "4. **La longueur de description**, dans le fil des jalons 1 à 3 : la taille du\n", + " générateur contre celle du corpus compressé.\n", + "\n", + "Le mode collapse sur un mélange de gaussiennes 2D n'est pas refait ici : il est\n", + "mesuré dans [ML 3.6b](../../../ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb),\n", + "qui compare GAN, VAE et diffusion sur la même cible.\n", + "\n", + "**Durée** : environ 6 minutes sur un GPU portable (RTX 4060), nettement plus sur\n", + "CPU (le notebook choisit le périphérique seul). Les chiffres cités dans les lectures\n", + "proviennent de l'exécution GPU committée ; une exécution CPU donne des valeurs\n", + "voisines, pas identiques." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "c05d01", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:37:33.355095Z", + "iopub.status.busy": "2026-10-14T04:37:33.354946Z", + "iopub.status.idle": "2026-10-14T04:37:42.082305Z", + "shell.execute_reply": "2026-10-14T04:37:42.081417Z" + }, + "papermill": { + "duration": 8.734647, + "end_time": "2026-10-14T04:37:42.083243+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:33.348596+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch 2.14.0+cu126 | peripherique : cuda | NVIDIA GeForce RTX 4060 Laptop GPU\n", + "corpus complet : (400, 1, 32, 32) | entrainement : (360, 1, 32, 32) | couple de controle : 40 photos vues / 40 jamais vues\n" + ] 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os, time, lzma\n", + "os.environ.setdefault(\"CUBLAS_WORKSPACE_CONFIG\", \":4096:8\")\n", + "import numpy as np\n", + "import torch, torch.nn as nn, torch.nn.functional as F\n", + "import matplotlib.pyplot as plt\n", + "from sklearn.datasets import fetch_olivetti_faces\n", + "from sklearn.linear_model import LogisticRegression\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.pipeline import make_pipeline\n", + "from sklearn.preprocessing import StandardScaler\n", + "\n", + "%matplotlib inline\n", + "torch.use_deterministic_algorithms(True, warn_only=True)\n", + "torch.backends.cudnn.benchmark = False\n", + "DEV = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", + "print(\"torch\", torch.__version__, \"| peripherique :\", DEV,\n", + " \"|\", torch.cuda.get_device_name(0) if DEV == \"cuda\" else \"CPU\")\n", + "\n", + "faces = fetch_olivetti_faces() # 400 x 64 x 64, valeurs dans [0, 1]\n", + "X = F.interpolate(torch.tensor(faces.images)[:, None], size=32, mode=\"area\") * 2 - 1\n", + "ids = faces.target\n", + "vue = np.array([np.where(ids == k)[0][1] for k in range(40)]) # 2e photo de chaque personne\n", + "non_vue = np.array([np.where(ids == k)[0][0] for k in range(40)]) # 1re photo, jamais montree\n", + "mask_train = np.ones(400, bool); mask_train[non_vue] = False\n", + "X_train360 = X[mask_train] # 9 photos par personne, dont la photo \"vue\"\n", + "X_vue, X_non_vue = X[vue], X[non_vue]\n", + "print(\"corpus complet :\", tuple(X.shape), \"| entrainement :\", tuple(X_train360.shape),\n", + " \"| couple de controle :\", len(X_vue), \"photos vues /\", len(X_non_vue), \"jamais vues\")\n", + "\n", + "fig, ax = plt.subplots(2, 10, figsize=(12, 2.6))\n", + "for j, k in enumerate(range(0, 40, 4)):\n", + " ax[0, j].imshow(X_vue[k, 0], cmap=\"gray\", vmin=-1, vmax=1)\n", + " ax[1, j].imshow(X_non_vue[k, 0], cmap=\"gray\", vmin=-1, vmax=1)\n", + " ax[0, j].axis(\"off\"); ax[1, j].axis(\"off\")\n", + "ax[0, 0].set_title(\"vue\", fontsize=9, loc=\"left\"); ax[1, 0].set_title(\"jamais vue\", fontsize=9, loc=\"left\")\n", + "plt.suptitle(\"Dix des quarante personnes : la photo montree au GAN et sa jumelle tenue a l'ecart\", fontsize=10)\n", + "plt.tight_layout(); plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c05d02", + "metadata": { + "papermill": { + "duration": 0.003706, + "end_time": "2026-10-14T04:37:42.091598+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.087892+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "Le corpus compte 400 portraits ramenés à 32×32 pixels. Le GAN en voit 360 : neuf photos par personne, dont la photo « vue » de la ligne du haut. La photo du bas, prise lors d'une autre séance, n'entre jamais dans l'entraînement. Les deux photos d'une même personne se ressemblent davantage qu'elles ne ressemblent aux autres personnes, et c'est ce qui rend le contrôle de la section 3 honnête : toute préférence d'un échantillon pour la photo vue ne peut pas venir de l'identité, puisque les deux photos la partagent." + ] + }, + { + "cell_type": "markdown", + "id": "c05d03", + "metadata": { + "papermill": { + "duration": 0.003725, + "end_time": "2026-10-14T04:37:42.099388+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.095663+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 1. Le DCGAN : cinq règles d'architecture\n", + "\n", + "Radford et al. (§3) résument ce qui rend stable un GAN convolutif :\n", + "\n", + "- remplacer le *pooling* par des convolutions à pas (discriminateur) et des\n", + " convolutions **transposées** (générateur) ;\n", + "- BatchNorm dans les deux réseaux ;\n", + "- pas de couche dense cachée ;\n", + "- ReLU dans le générateur, sauf la sortie en `tanh` ;\n", + "- LeakyReLU dans le discriminateur ;\n", + "- Adam avec un pas de $2\\cdot10^{-4}$ et $\\beta_1 = 0{,}5$ (§4, la valeur 0,9 faisait osciller l'entraînement).\n", + "\n", + "Le générateur ci-dessous accepte une seconde façon de suréchantillonner (voisin le\n", + "plus proche puis convolution), qui servira au test spectral de la section 4." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "c05d04", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:37:42.110387Z", + "iopub.status.busy": "2026-10-14T04:37:42.109867Z", + "iopub.status.idle": "2026-10-14T04:37:42.133608Z", + "shell.execute_reply": "2026-10-14T04:37:42.132670Z" + }, + "papermill": { + "duration": 0.030316, + "end_time": "2026-10-14T04:37:42.134510+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.104194+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "generateur (transposee) : 295 873 parametres\n", + "generateur (voisin ) : 223 969 parametres\n", + "discriminateur : 166 817 parametres\n" + ] + } + ], + "source": [ + "Z = 64\n", + "\n", + "class Generateur(nn.Module):\n", + " def __init__(self, up=\"transposee\"):\n", + " super().__init__()\n", + " def bloc(i, o, derniere=False):\n", + " if up == \"transposee\":\n", + " conv = nn.ConvTranspose2d(i, o, 4, 2, 1, bias=derniere)\n", + " else: # voisin le plus proche puis convolution 3x3\n", + " conv = nn.Sequential(nn.Upsample(scale_factor=2, mode=\"nearest\"),\n", + " nn.Conv2d(i, o, 3, 1, 1, bias=derniere))\n", + " return [conv] + ([nn.Tanh()] if derniere else [nn.BatchNorm2d(o), nn.ReLU(True)])\n", + " self.net = nn.Sequential(\n", + " nn.ConvTranspose2d(Z, 128, 4, 1, 0, bias=False), nn.BatchNorm2d(128), nn.ReLU(True), # 1 -> 4\n", + " *bloc(128, 64), *bloc(64, 32), *bloc(32, 1, derniere=True)) # 4 -> 32\n", + " def forward(self, z):\n", + " return self.net(z[:, :, None, None])\n", + "\n", + "class Discriminateur(nn.Module):\n", + " def __init__(self):\n", + " super().__init__()\n", + " self.net = nn.Sequential(\n", + " nn.Conv2d(1, 32, 4, 2, 1), nn.LeakyReLU(0.2, True),\n", + " nn.Conv2d(32, 64, 4, 2, 1, bias=False), nn.BatchNorm2d(64), nn.LeakyReLU(0.2, True),\n", + " nn.Conv2d(64, 128, 4, 2, 1, bias=False), nn.BatchNorm2d(128), nn.LeakyReLU(0.2, True),\n", + " nn.Conv2d(128, 1, 4, 1, 0))\n", + " def forward(self, x):\n", + " return self.net(x).view(-1)\n", + "\n", + "def n_params(m):\n", + " return sum(p.numel() for p in m.parameters())\n", + "\n", + "for up in [\"transposee\", \"voisin\"]:\n", + " print(f\"generateur ({up:10s}) : {n_params(Generateur(up)):>7,d} parametres\".replace(\",\", \" \"))\n", + "print(f\"discriminateur : {n_params(Discriminateur()):>7,d} parametres\".replace(\",\", \" \"))" + ] + }, + { + "cell_type": "markdown", + "id": "c05d05", + "metadata": { + "papermill": { + "duration": 0.003489, + "end_time": "2026-10-14T04:37:42.141621+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.138132+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "Le générateur à convolutions transposées compte 295 873 paramètres, la variante « voisin puis convolution » 223 969 (un noyau 3×3 au lieu de 4×4 à chaque étage), le discriminateur 166 817. Ces nombres reviennent en section 6 : ils fixent la longueur de description du programme génératif." + ] + }, + { + "cell_type": "markdown", + "id": "c05d06", + "metadata": { + "papermill": { + "duration": 0.003393, + "end_time": "2026-10-14T04:37:42.148435+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.145042+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 2. Entraîner le jeu min-max\n", + "\n", + "La boucle suit Goodfellow et al. avec la perte **non saturante** du générateur\n", + "(maximiser $\\log D(G(z))$ plutôt que minimiser $\\log(1-D(G(z)))$, §3 du papier : le\n", + "gradient ne s'éteint pas quand le discriminateur gagne trop tôt).\n", + "\n", + "Un détail qui coûte cher s'il est oublié : on **échantillonne en mode entraînement**.\n", + "En mode `eval`, la BatchNorm du générateur utilise ses moyennes glissantes, qui ne\n", + "suivent pas un générateur en mouvement ; sur ce montage, les visages deviennent alors\n", + "une texture bruitée. Le prototype de ce notebook est tombé dans ce piège avant\n", + "d'être corrigé." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "c05d07", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:37:42.157521Z", + "iopub.status.busy": "2026-10-14T04:37:42.157132Z", + "iopub.status.idle": "2026-10-14T04:38:25.177112Z", + "shell.execute_reply": "2026-10-14T04:38:25.175922Z" + }, + "papermill": { + "duration": 43.025937, + "end_time": "2026-10-14T04:38:25.177791+00:00", + "exception": false, + "start_time": "2026-10-14T04:37:42.151854+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "entrainement principal : 2500 iterations en 43 s\n", + "perte D : debut 0.201 -> fin 0.080\n", + "perte G : debut 3.392 -> fin 3.874\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ITERS, BATCH = 2500, 64\n", + "Z_FIXE = torch.randn(400, Z, generator=torch.Generator().manual_seed(1234))\n", + "\n", + "def entrainer(Xt, up=\"transposee\", graine=0, iters=ITERS):\n", + " torch.manual_seed(graine); np.random.seed(graine)\n", + " g, d = Generateur(up).to(DEV), Discriminateur().to(DEV)\n", + " og = torch.optim.Adam(g.parameters(), 2e-4, betas=(0.5, 0.999))\n", + " od = torch.optim.Adam(d.parameters(), 2e-4, betas=(0.5, 0.999))\n", + " bce = nn.BCEWithLogitsLoss()\n", + " un, zero = torch.ones(BATCH, device=DEV), torch.zeros(BATCH, device=DEV)\n", + " Xt = Xt.to(DEV); pertes = []\n", + " for it in range(iters):\n", + " x = Xt[torch.randint(0, len(Xt), (BATCH,), device=DEV)]\n", + " faux = g(torch.randn(BATCH, Z, device=DEV))\n", + " ld = bce(d(x), un) + bce(d(faux.detach()), zero)\n", + " od.zero_grad(); ld.backward(); od.step()\n", + " lg = bce(d(faux), un) # perte non saturante\n", + " og.zero_grad(); lg.backward(); og.step()\n", + " pertes.append((ld.item(), lg.item()))\n", + " with torch.no_grad():\n", + " echantillons = g(Z_FIXE.to(DEV)).cpu() # mode entrainement : stats du lot\n", + " return g, echantillons, np.array(pertes)\n", + "\n", + "t0 = time.time()\n", + "G_principal, S_principal, pertes = entrainer(X_train360, \"transposee\", graine=0)\n", + "print(f\"entrainement principal : {ITERS} iterations en {time.time() - t0:.0f} s\")\n", + "print(f\"perte D : debut {pertes[:100, 0].mean():.3f} -> fin {pertes[-100:, 0].mean():.3f}\")\n", + "print(f\"perte G : debut {pertes[:100, 1].mean():.3f} -> fin {pertes[-100:, 1].mean():.3f}\")\n", + "\n", + "def plus_proche(S, R):\n", + " dist = torch.cdist(S.flatten(1), R.flatten(1))\n", + " return dist.min(1).values, dist.argmin(1)\n", + "\n", + "_, idx = plus_proche(S_principal[:12], X_train360)\n", + "fig, ax = plt.subplots(2, 12, figsize=(13, 2.6))\n", + "for i in range(12):\n", + " ax[0, i].imshow(S_principal[i, 0], cmap=\"gray\", vmin=-1, vmax=1)\n", + " ax[1, i].imshow(X_train360[idx[i], 0], cmap=\"gray\", vmin=-1, vmax=1)\n", + " ax[0, i].axis(\"off\"); ax[1, i].axis(\"off\")\n", + "ax[0, 0].set_title(\"genere\", fontsize=9, loc=\"left\"); ax[1, 0].set_title(\"plus proche du corpus\", fontsize=9, loc=\"left\")\n", + "plt.suptitle(\"Douze portraits generes et, dessous, la photo d'entrainement la plus proche (distance pixel)\", fontsize=10)\n", + "plt.tight_layout(); plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c05d08", + "metadata": { + "papermill": { + "duration": 0.006239, + "end_time": "2026-10-14T04:38:25.189307+00:00", + "exception": false, + "start_time": "2026-10-14T04:38:25.183068+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "L'entraînement principal prend moins d'une minute sur le GPU. Les pertes ne racontent pas une convergence : celle du discriminateur baisse (0,201 → 0,080 en moyenne sur 100 itérations) pendant que celle du générateur monte (3,392 → 3,874). Le discriminateur gagne le jeu, ce qui est l'état ordinaire d'un GAN et la raison pour laquelle sa courbe de perte ne sert pas de critère d'arrêt.\n", + "\n", + "Les échantillons sont pourtant des visages : yeux, nez, bouche, lunettes, pose frontale et cadrage de la base. On y voit aussi le style reconnaissable des GANs d'époque : des textures granuleuses, des taches là où les lunettes se mêlent au visage, des symétries approximatives. Ce sont les « distorsions » qu'Obvious revendiquait comme un attribut du modèle. Les photos placées dessous sont les voisines les plus proches en distance pixel : sur cette grille, elles ressemblent aux échantillons par la pose, l'éclairage ou les lunettes, sans en être des copies." + ] + }, + { + "cell_type": "markdown", + "id": "c05d09", + "metadata": { + "papermill": { + "duration": 0.005941, + "end_time": "2026-10-14T04:38:25.200700+00:00", + "exception": false, + "start_time": "2026-10-14T04:38:25.194759+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 3. Le générateur copie-t-il ?\n", + "\n", + "La question d'auteur soulevée par la vente de 2018 a une moitié qui se mesure. Si\n", + "un générateur recopie ses exemples, ses images sont plus proches des photos **qu'il\n", + "a vues** que d'autres photos des **mêmes personnes** qu'il n'a jamais vues. Le couple\n", + "(vue, jamais vue) neutralise l'identité : seule la mémorisation peut faire pencher\n", + "la balance.\n", + "\n", + "Pour chaque échantillon, on compare sa distance à la photo vue la plus proche et à\n", + "la photo jamais vue la plus proche (40 de chaque côté). Sans mémorisation, la\n", + "fraction d'échantillons plus proches du côté « vu » vaut environ 1/2.\n", + "\n", + "Trois montages, trois graines chacun (0, 1, 42) :\n", + "\n", + "- **360 portraits**, suréchantillonnage par convolution transposée ;\n", + "- **360 portraits**, voisin le plus proche puis convolution ;\n", + "- **40 portraits** seulement, une photo par personne : le corpus de *Belamy* était\n", + " 375 fois plus grand que celui-ci." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c05d10", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:38:25.212494Z", + "iopub.status.busy": "2026-10-14T04:38:25.212251Z", + "iopub.status.idle": "2026-10-14T04:44:13.199412Z", + "shell.execute_reply": "2026-10-14T04:44:13.197825Z" + }, + "papermill": { + "duration": 348.002641, + "end_time": "2026-10-14T04:44:13.208371+00:00", + "exception": false, + "start_time": "2026-10-14T04:38:25.205730+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "9 entrainements mesures en 348 s\n", + "\n", + "montage graine med. dist. vue med. dist. jamais vue fraction penchant vers vu\n", + "360 portraits, transposee 0 7.75 7.88 0.553\n", + "360 portraits, transposee 1 7.82 7.87 0.505\n", + "360 portraits, transposee 42 7.88 7.96 0.527\n", + "360 portraits, voisin 0 7.77 7.72 0.498\n", + "360 portraits, voisin 1 7.75 7.74 0.485\n", + "360 portraits, voisin 42 7.92 7.85 0.510\n", + "40 portraits, transposee 0 7.29 7.71 0.720\n", + "40 portraits, transposee 1 7.07 7.53 0.757\n", + "40 portraits, transposee 42 7.63 7.89 0.683\n", + "\n", + "360 portraits, transposee fraction penchant vers vu : moyenne 0.528, ecart-type 0.024\n", + "360 portraits, voisin fraction penchant vers vu : moyenne 0.498, ecart-type 0.012\n", + "40 portraits, transposee fraction penchant vers vu : moyenne 0.720, ecart-type 0.037\n" + ] + } + ], + "source": [ + "MONTAGES = [(\"360 portraits, transposee\", X_train360, \"transposee\"),\n", + " (\"360 portraits, voisin\", X_train360, \"voisin\"),\n", + " (\"40 portraits, transposee\", X_vue, \"transposee\")]\n", + "GRAINES = [0, 1, 42]\n", + "\n", + "resultats, echantillons = [], {}\n", + "t0 = time.time()\n", + "for nom, Xt, up in MONTAGES:\n", + " for graine in GRAINES:\n", + " if nom.startswith(\"360 portraits, transposee\") and graine == 0:\n", + " S = S_principal # deja entraine en section 2\n", + " else:\n", + " _, S, _ = entrainer(Xt, up, graine)\n", + " echantillons[(nom, graine)] = S\n", + " d_vue, _ = plus_proche(S, X_vue)\n", + " d_non_vue, _ = plus_proche(S, X_non_vue)\n", + " resultats.append(dict(montage=nom, graine=graine,\n", + " d_vue=d_vue.median().item(), d_non_vue=d_non_vue.median().item(),\n", + " penche_vu=(d_vue < d_non_vue).float().mean().item()))\n", + "print(f\"{len(resultats)} entrainements mesures en {time.time() - t0:.0f} s\\n\")\n", + "\n", + "print(f\"{'montage':28s} {'graine':>6s} {'med. dist. vue':>15s} {'med. dist. jamais vue':>22s} {'fraction penchant vers vu':>26s}\")\n", + "for r in resultats:\n", + " print(f\"{r['montage']:28s} {r['graine']:>6d} {r['d_vue']:>15.2f} {r['d_non_vue']:>22.2f} {r['penche_vu']:>26.3f}\")\n", + "print()\n", + "for nom, _, _ in MONTAGES:\n", + " v = np.array([r[\"penche_vu\"] for r in resultats if r[\"montage\"] == nom])\n", + " print(f\"{nom:28s} fraction penchant vers vu : moyenne {v.mean():.3f}, ecart-type {v.std(ddof=1):.3f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "c05d11", + "metadata": { + "papermill": { + "duration": 0.007586, + "end_time": "2026-10-14T04:44:13.224920+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:13.217334+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "Les trois graines suffisent à séparer deux régimes.\n", + "\n", + "- **Avec 360 portraits, pas de copie mesurable.** La fraction d'échantillons plus proches de la photo vue vaut 0,528 en moyenne (écart-type 0,024) avec les convolutions transposées et 0,498 (écart-type 0,012) avec le voisin le plus proche, soit le hasard à quelques centièmes près. Les distances médianes aux photos vues et jamais vues diffèrent au plus de 0,13.\n", + "- **Avec 40 portraits, la copie apparaît.** La fraction monte à 0,720 en moyenne (écart-type 0,037), et à chaque graine la distance médiane à la photo vue est plus petite que la distance à la photo jamais vue (7,29 contre 7,71, 7,07 contre 7,53, 7,63 contre 7,89). Avec une seule photo par personne, le générateur s'approche des photos qu'il a vues plutôt que des visages en général.\n", + "\n", + "La question d'auteur de 2018 a donc une moitié mesurable, et sa réponse dépend du rapport entre la capacité du générateur et la taille du corpus. Ce montage ne dit rien du cas *Belamy* lui-même : 15 000 portraits, soit 375 fois notre petit corpus, un autre réseau et une autre résolution. Il montre seulement que la question se mesure, et comment." + ] + }, + { + "cell_type": "markdown", + "id": "c05d12", + "metadata": { + "papermill": { + "duration": 0.005722, + "end_time": "2026-10-14T04:44:13.238289+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:13.232567+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 4. L'empreinte spectrale\n", + "\n", + "Durall, Keuper et Keuper (CVPR 2020) affirment que le suréchantillonnage\n", + "convolutif empêche un générateur de reproduire la distribution spectrale des\n", + "images naturelles, et qu'un simple classifieur sur le spectre détecte les images\n", + "générées « jusqu'à 100 % » sur les bancs publics. On mesure les deux moitiés :\n", + "\n", + "- le **profil radial** du spectre de puissance (moyenne azimutale de $|\\hat{x}|^2$,\n", + " en log10), réel contre généré ;\n", + "- un **détecteur** : régression logistique sur ce profil (17 valeurs par image),\n", + " 400 portraits réels contre 400 générés, précision en validation croisée à 5 plis.\n", + " 0,5 = indiscernable." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "c05d13", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:13.249710Z", + "iopub.status.busy": "2026-10-14T04:44:13.249397Z", + "iopub.status.idle": "2026-10-14T04:44:14.912026Z", + "shell.execute_reply": "2026-10-14T04:44:14.911009Z" + }, + "papermill": { + "duration": 1.669572, + "end_time": "2026-10-14T04:44:14.912697+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:13.243125+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "montage graine precision du detecteur exces hautes freq. (log10)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "360 portraits, transposee 0 0.643 0.083\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "360 portraits, transposee 1 0.626 0.065\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "360 portraits, transposee 42 0.655 0.057\n", + "360 portraits, voisin 0 0.710 0.083\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "360 portraits, voisin 1 0.764 0.093\n", + "360 portraits, voisin 42 0.711 0.084\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "40 portraits, transposee 0 0.912 0.224\n", + "40 portraits, transposee 1 0.875 0.174\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "40 portraits, transposee 42 0.831 0.184\n", + "\n", + "360 portraits, transposee detecteur : moyenne 0.641, min 0.626, max 0.655\n", + "360 portraits, voisin detecteur : moyenne 0.728, min 0.710, max 0.764\n", + "40 portraits, transposee detecteur : moyenne 0.873, min 0.831, max 0.912\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def profil_radial(imgs):\n", + " x = imgs.squeeze(1).numpy()\n", + " P = np.abs(np.fft.fftshift(np.fft.fft2(x), axes=(-2, -1))) ** 2\n", + " n = x.shape[-1]\n", + " yy, xx = np.indices((n, n))\n", + " r = np.hypot(yy - n / 2, xx - n / 2).astype(int)\n", + " prof = np.stack([np.bincount(r.ravel(), p.ravel()) / np.bincount(r.ravel()) for p in P])\n", + " return np.log10(prof[:, : n // 2 + 1])\n", + "\n", + "P_reel = profil_radial(X)\n", + "\n", + "def detecter(S):\n", + " feats = np.vstack([P_reel, profil_radial(S)])\n", + " y = np.r_[np.zeros(len(P_reel)), np.ones(len(S))]\n", + " clf = make_pipeline(StandardScaler(), LogisticRegression(max_iter=2000))\n", + " return cross_val_score(clf, feats, y, cv=5).mean()\n", + "\n", + "print(f\"{'montage':28s} {'graine':>6s} {'precision du detecteur':>23s} {'exces hautes freq. (log10)':>27s}\")\n", + "for r in resultats:\n", + " S = echantillons[(r[\"montage\"], r[\"graine\"])]\n", + " r[\"detect\"] = detecter(S)\n", + " r[\"exces_hf\"] = (profil_radial(S).mean(0) - P_reel.mean(0))[-4:].mean()\n", + " print(f\"{r['montage']:28s} {r['graine']:>6d} {r['detect']:>23.3f} {r['exces_hf']:>27.3f}\")\n", + "print()\n", + "for nom, _, _ in MONTAGES:\n", + " v = np.array([r[\"detect\"] for r in resultats if r[\"montage\"] == nom])\n", + " print(f\"{nom:28s} detecteur : moyenne {v.mean():.3f}, min {v.min():.3f}, max {v.max():.3f}\")\n", + "\n", + "freqs = np.arange(P_reel.shape[1])\n", + "plt.figure(figsize=(7, 4))\n", + "plt.plot(freqs, P_reel.mean(0), \"k-\", lw=2.5, label=\"400 portraits reels\")\n", + "for (nom, _, _), c in zip(MONTAGES, [\"C0\", \"C1\", \"C3\"]):\n", + " prof = np.mean([profil_radial(echantillons[(nom, g)]).mean(0) for g in GRAINES], axis=0)\n", + " plt.plot(freqs, prof, color=c, lw=1.5, label=nom)\n", + "plt.xlabel(\"frequence radiale (cycles par image)\"); plt.ylabel(\"log10 puissance moyenne\")\n", + "plt.title(\"Profil spectral radial : reel contre genere (moyenne sur 3 graines)\")\n", + "plt.legend(fontsize=8); plt.grid(alpha=0.3); plt.tight_layout(); plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c05d14", + "metadata": { + "papermill": { + "duration": 0.005551, + "end_time": "2026-10-14T04:44:14.925637+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:14.920086+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "La courbe confirme l'observation de Durall et al. dans sa direction : les profils générés suivent le réel aux basses fréquences et s'en écartent vers le haut du spectre, où ils portent trop d'énergie. L'excès sur les quatre dernières fréquences va de 0,057 à 0,093 (en log10) pour les montages à 360 portraits et de 0,174 à 0,224 pour le montage à 40 portraits.\n", + "\n", + "Le détecteur, lui, ne reproduit pas les « jusqu'à 100 % » du papier à cette échelle. Sa précision moyenne vaut 0,641 pour les convolutions transposées et 0,728 pour le voisin le plus proche, contre 0,873 pour le montage à 40 portraits. Trois écarts avec la lecture naïve du papier sont à retenir.\n", + "\n", + "1. Sur des images de 32×32, le profil radial n'a que 17 valeurs, et le signal tient dans les dernières.\n", + "2. Remplacer la convolution transposée par le voisin le plus proche **n'efface pas** l'empreinte : ici, elle est même un peu plus détectable (0,728 contre 0,641). L'artefact n'appartient donc pas à un seul opérateur de suréchantillonnage.\n", + "3. Le générateur le plus détectable est celui qui copie le plus. Peu de données donnent à la fois plus de mémorisation et une signature spectrale plus nette." + ] + }, + { + "cell_type": "markdown", + "id": "c05d15", + "metadata": { + "papermill": { + "duration": 0.010335, + "end_time": "2026-10-14T04:44:14.944419+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:14.934084+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 5. Le geste qui a fait l'esthétique GAN : l'interpolation latente\n", + "\n", + "Le style reconnaissable des GANs d'époque tient autant à leurs défauts qu'à un\n", + "geste : **marcher dans l'espace latent**. Entre deux vecteurs $z_a$ et $z_b$, le\n", + "générateur produit une suite continue de visages qui n'existent pas, ce que les\n", + "artistes du GAN ont exploité en vidéo et en séries. Radford et al. (§6.1) en font\n", + "même un test : une marche latente sans saut brusque indique un générateur qui n'a\n", + "pas simplement mémorisé des points isolés." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c05d16", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:14.962500Z", + "iopub.status.busy": "2026-10-14T04:44:14.962279Z", + "iopub.status.idle": "2026-10-14T04:44:15.261627Z", + "shell.execute_reply": "2026-10-14T04:44:15.260228Z" + }, + "papermill": { + "duration": 0.307736, + "end_time": "2026-10-14T04:44:15.262407+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:14.954671+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ecart pixel entre deux pas successifs : [2.32 2.7 2.86 2.59 2.33 1.79 1.51 1.36]\n", + "plus grand saut / saut median : 1.23\n" + ] + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "torch.manual_seed(7)\n", + "za, zb = torch.randn(1, Z), torch.randn(1, Z)\n", + "t = torch.linspace(0, 1, 9)[:, None]\n", + "lot = torch.cat([(1 - t) * za + t * zb, torch.randn(55, Z)]) # le lot complete les stats de BatchNorm\n", + "with torch.no_grad():\n", + " marche = G_principal(lot.to(DEV)).cpu()[:9]\n", + "sauts = (marche[1:] - marche[:-1]).flatten(1).norm(dim=1)\n", + "print(\"ecart pixel entre deux pas successifs :\", np.round(sauts.numpy(), 2))\n", + "print(f\"plus grand saut / saut median : {sauts.max().item() / sauts.median().item():.2f}\")\n", + "\n", + "fig, ax = plt.subplots(1, 9, figsize=(12, 1.7))\n", + "for i in range(9):\n", + " ax[i].imshow(marche[i, 0], cmap=\"gray\", vmin=-1, vmax=1); ax[i].axis(\"off\")\n", + " ax[i].set_title(f\"t={t[i, 0]:.2f}\", fontsize=8)\n", + "plt.suptitle(\"Marche lineaire de z_a a z_b dans l'espace latent\", fontsize=10)\n", + "plt.tight_layout(); plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c05d17", + "metadata": { + "papermill": { + "duration": 0.006233, + "end_time": "2026-10-14T04:44:15.275903+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.269670+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "La marche latente passe d'un visage à un autre sans saut. L'écart pixel entre deux pas successifs reste entre 1,36 et 2,86, et le plus grand saut ne vaut que 1,23 fois le saut médian. Le générateur n'a pas appris une table de points isolés, ce qui recoupe la section 3 (pas de copie à 360 portraits).\n", + "\n", + "Visuellement, l'interpolation traverse des visages intermédiaires qui n'existent dans aucune photo, avec les textures et les taches typiques du modèle. C'est ce matériau que les artistes du GAN ont mis en série et en vidéo." + ] + }, + { + "cell_type": "markdown", + "id": "c05d18", + "metadata": { + "papermill": { + "duration": 0.008869, + "end_time": "2026-10-14T04:44:15.291881+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.283012+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## 6. La longueur de description, au retour du fil\n", + "\n", + "Les jalons 1 à 3 mesuraient un **petit programme** qui engendre une **grande image**.\n", + "On pose la même mesure au GAN : combien d'octets faut-il pour décrire le générateur,\n", + "et combien pour décrire le corpus qu'il imite ?" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c05d19", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:15.306416Z", + "iopub.status.busy": "2026-10-14T04:44:15.306160Z", + "iopub.status.idle": "2026-10-14T04:44:15.425979Z", + "shell.execute_reply": "2026-10-14T04:44:15.425156Z" + }, + "papermill": { + "duration": 0.128314, + "end_time": "2026-10-14T04:44:15.426859+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.298545+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "generateur (float32) : 1 183 492 octets\n", + "corpus de 360 portraits brut : 368 640 octets\n", + "corpus compresse (LZMA -9) : 286 312 octets\n", + "generateur / corpus compresse : x4.13\n", + "une image 32x32 en niveaux de gris : 1024 octets ; le generateur en decrit 'une infinite', mais pese autant que 1155 images brutes\n" + ] + } + ], + "source": [ + "octets_G = n_params(G_principal) * 4 # poids en float32\n", + "corpus_u8 = ((X_train360 + 1) / 2 * 255).round().clamp(0, 255).byte().numpy().tobytes()\n", + "corpus_lzma = len(lzma.compress(corpus_u8, preset=9))\n", + "\n", + "print(f\"generateur (float32) : {octets_G:>9,d} octets\".replace(\",\", \" \"))\n", + "print(f\"corpus de 360 portraits brut : {len(corpus_u8):>9,d} octets\".replace(\",\", \" \"))\n", + "print(f\"corpus compresse (LZMA -9) : {corpus_lzma:>9,d} octets\".replace(\",\", \" \"))\n", + "print(f\"generateur / corpus compresse : x{octets_G / corpus_lzma:.2f}\")\n", + "print(f\"une image 32x32 en niveaux de gris : {32 * 32} octets ; \"\n", + " f\"le generateur en decrit 'une infinite', mais pese autant que {octets_G // (32 * 32)} images brutes\")" + ] + }, + { + "cell_type": "markdown", + "id": "c05d20", + "metadata": { + "papermill": { + "duration": 0.0065, + "end_time": "2026-10-14T04:44:15.440109+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.433609+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Lecture du résultat\n", + "\n", + "Le générateur pèse 1 183 492 octets en float32, et le corpus qu'il imite 368 640 octets brut ou 286 312 octets compressé par LZMA. Le programme génératif est donc **4,13 fois plus lourd** que les données qu'il résume.\n", + "\n", + "C'est l'inverse exact de la démoscène et du low-complexity art des jalons 2 et 3, où quelques centaines d'octets engendraient une image riche. Le générateur peut certes produire une infinité de portraits, mais sa description vaut 1 155 images brutes, plus de trois fois le corpus. Ce qu'il a gagné ne se mesure pas en compression : il échantillonne des visages **nouveaux**, que le corpus ne contient pas. L'exercice 3 demande de combien on peut réduire cet écart." + ] + }, + { + "cell_type": "markdown", + "id": "c05d21", + "metadata": { + "papermill": { + "duration": 0.006198, + "end_time": "2026-10-14T04:44:15.452582+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.446384+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Exercices\n", + "\n", + "### Exercice 1 — Un détecteur de copie plus fin\n", + "\n", + "La fraction « penchant vers vu » regarde la photo la plus proche de chaque côté.\n", + "Un critère classique de détection de copie regarde plutôt le **rapport** $d_1/d_2$\n", + "entre la distance à la photo d'entraînement la plus proche et à la deuxième plus\n", + "proche : une copie quasi exacte donne un rapport très petit.\n", + "\n", + "Calculez la distribution de $d_1/d_2$ (sur `X_vue`) pour les échantillons du montage\n", + "« 40 portraits » et du montage « 360 portraits, transposee » (graine 0), et dites si\n", + "ce critère sépare mieux les deux montages que la fraction de la section 3." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c05d22", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:15.466232Z", + "iopub.status.busy": "2026-10-14T04:44:15.465930Z", + "iopub.status.idle": "2026-10-14T04:44:15.470460Z", + "shell.execute_reply": "2026-10-14T04:44:15.469673Z" + }, + "papermill": { + "duration": 0.012485, + "end_time": "2026-10-14T04:44:15.471144+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.458659+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Exercice a completer : comparer les medianes de d1/d2 pour les deux montages\n" + ] + } + ], + "source": [ + "# Exercice 1 -- rapport d1/d2 contre le corpus vu\n", + "# Indice : torch.cdist(S.flatten(1), X_vue.flatten(1)).topk(2, largest=False) donne d1 et d2\n", + "S40 = echantillons[(\"40 portraits, transposee\", 0)]\n", + "S360 = echantillons[(\"360 portraits, transposee\", 0)]\n", + "rapport_40 = None # TODO etudiant\n", + "rapport_360 = None # TODO etudiant\n", + "print(\"Exercice a completer : comparer les medianes de d1/d2 pour les deux montages\")" + ] + }, + { + "cell_type": "markdown", + "id": "c05d23", + "metadata": { + "papermill": { + "duration": 0.006219, + "end_time": "2026-10-14T04:44:15.483835+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.477616+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Exercice 2 — Plus longtemps, plus de copie ?\n", + "\n", + "La mémorisation dépend aussi de la durée d'entraînement. Réentraînez le montage\n", + "« 40 portraits » (graine 0) pour 500, 1 500 et 2 500 itérations (`entrainer(X_vue,\n", + "\"transposee\", 0, iters=...)`), et tracez la fraction « penchant vers vu » en\n", + "fonction du nombre d'itérations. La copie apparaît-elle d'un coup ou\n", + "progressivement ?" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "c05d24", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:15.498027Z", + "iopub.status.busy": "2026-10-14T04:44:15.497783Z", + "iopub.status.idle": "2026-10-14T04:44:15.501898Z", + "shell.execute_reply": "2026-10-14T04:44:15.501033Z" + }, + "papermill": { + "duration": 0.012086, + "end_time": "2026-10-14T04:44:15.502585+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.490499+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Exercice a completer : entrainer pour chaque budget et mesurer la fraction\n" + ] + } + ], + "source": [ + "# Exercice 2 -- fraction \"penchant vers vu\" en fonction de la duree d'entrainement\n", + "budgets = [500, 1500, 2500]\n", + "fractions = [] # TODO etudiant : une valeur par budget\n", + "print(\"Exercice a completer : entrainer pour chaque budget et mesurer la fraction\")" + ] + }, + { + "cell_type": "markdown", + "id": "c05d25", + "metadata": { + "papermill": { + "duration": 0.009116, + "end_time": "2026-10-14T04:44:15.518070+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.508954+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Exercice 3 — Compresser le générateur\n", + "\n", + "La section 6 compte les poids en float32. Quantifiez les poids du générateur sur\n", + "8 bits (par tenseur : $w \\mapsto \\mathrm{round}((w - \\min)/(\\max - \\min) \\cdot 255)$,\n", + "puis l'inverse), générez à nouveau les 400 échantillons de `Z_FIXE`, et mesurez\n", + "(a) la nouvelle longueur de description, (b) l'écart pixel moyen avec les\n", + "échantillons d'origine. Le générateur passe-t-il sous la taille du corpus\n", + "compressé ?" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "c05d26", + "metadata": { + "execution": { + "iopub.execute_input": "2026-10-14T04:44:15.532089Z", + "iopub.status.busy": "2026-10-14T04:44:15.531842Z", + "iopub.status.idle": "2026-10-14T04:44:15.541918Z", + "shell.execute_reply": "2026-10-14T04:44:15.541026Z" + }, + "papermill": { + "duration": 0.018174, + "end_time": "2026-10-14T04:44:15.542619+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.524445+00:00", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Exercice a completer : quantifier, regenerer, comparer a corpus_lzma\n" + ] + } + ], + "source": [ + "# Exercice 3 -- quantification 8 bits du generateur\n", + "import copy\n", + "G_q = copy.deepcopy(G_principal)\n", + "# TODO etudiant : quantifier puis dequantifier chaque tenseur de G_q.parameters()\n", + "octets_q = None # TODO etudiant\n", + "print(\"Exercice a completer : quantifier, regenerer, comparer a corpus_lzma\")" + ] + }, + { + "cell_type": "markdown", + "id": "c05d29", + "metadata": { + "papermill": { + "duration": 0.006233, + "end_time": "2026-10-14T04:44:15.555856+00:00", + "exception": false, + "start_time": "2026-10-14T04:44:15.549623+00:00", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Références\n", + "\n", + "- I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, Y. Bengio, *Generative Adversarial Nets*, NeurIPS 2014. [arXiv:1406.2661](https://arxiv.org/abs/1406.2661)\n", + "- A. Radford, L. Metz, S. Chintala, *Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks*, ICLR 2016. [arXiv:1511.06434](https://arxiv.org/abs/1511.06434)\n", + "- R. Durall, M. Keuper, J. Keuper, *Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions*, CVPR 2020. [arXiv:2003.01826](https://arxiv.org/abs/2003.01826)\n", + "- F. Samaria, A. Harter, *Parameterisation of a stochastic model for human face identification*, IEEE WACV 1994 (base Olivetti / AT&T, via `sklearn.datasets.fetch_olivetti_faces`).\n", + "- Christie's, *Obvious and the interface between art and artificial intelligence* (2018) ; The Verge, *How three French students used borrowed code to put the first AI portrait in Christie's* (23 oct. 2018) ; Hypebeast, *Art Block Bought for $1,400 Sells at $3.3 Million USD* (août 2021).\n", + "\n", + "**Rattachements** : Epic #16774 (jalon 4) · [ML 3.6b](../../../ML/DataScienceWithAgents/03-DeepLearning/3.6b-Modeles-Generatifs-PyTorch.ipynb) pour le mode collapse." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.15" + }, + "papermill": { + "default_parameters": {}, + "duration": 406.674753, + "end_time": "2026-10-14T04:44:18.452658+00:00", + "environment_variables": {}, + "exception": null, + "input_path": "05-0d-GANs-Portraits-Moment-NFT.ipynb", + "output_path": "05-0d-GANs-Portraits-Moment-NFT.ipynb", + "parameters": {}, + "start_time": "2026-10-14T04:37:31.777905+00:00", + "version": "2.7.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/MyIA.AI.Notebooks/GenAI/Image/05-History/README.md b/MyIA.AI.Notebooks/GenAI/Image/05-History/README.md index c9a4747a62..efe29ecfaa 100644 --- a/MyIA.AI.Notebooks/GenAI/Image/05-History/README.md +++ b/MyIA.AI.Notebooks/GenAI/Image/05-History/README.md @@ -9,6 +9,7 @@ Notebooks rétrospectifs : les outils d'avant Stable Diffusion (2021-2022) qui o | # | Notebook | Contenu | Publication | |---|----------|---------|-------------| | 0 | [05-0-Generateurs-Symboliques](05-0-Generateurs-Symboliques.ipynb) | Les moteurs symboliques d'avant l'apprentissage : tortue Logo (rosace), L-systèmes (Koch quadratique), automates cellulaires (règle 110, Game of Life) — la description courte engendre l'image riche, mesuré comme un ratio de compression (x1030 / x2365) | Abelson & diSessa (Turtle, années 60-80) ; Lindenmayer 1968 ; Conway 1970 ; Wolfram 1982 | +| 0d | [05-0d-GANs-Portraits-Moment-NFT](05-0d-GANs-Portraits-Moment-NFT.ipynb) | Les GANs, de Goodfellow à *Edmond de Belamy* (Christie's 2018) : un DCGAN entraîné sur les portraits Olivetti, puis trois mesures. (1) Le générateur copie-t-il ? On le teste avec un contrôle photo vue / photo jamais vue de la même personne. (2) L'empreinte spectrale de Durall et al. permet-elle de détecter les images générées ? (3) Combien pèse le générateur face au corpus compressé ? Le notebook ajoute une marche dans l'espace latent et distingue la vente GAN de 2018 du boom NFT de 2021, qui a surtout couronné l'art génératif par code | Goodfellow et al. 2014 ([arXiv:1406.2661](https://arxiv.org/abs/1406.2661)) ; Radford et al. 2015 ([arXiv:1511.06434](https://arxiv.org/abs/1511.06434)) ; Durall et al. 2020 ([arXiv:2003.01826](https://arxiv.org/abs/2003.01826)) | | 2 | [05-2-CLIPasso-Semantic-Sketching](05-2-CLIPasso-Semantic-Sketching.ipynb) | Le sketching sémantique : abstraction contrôlée par le nombre de traits (grilles 32/16/8/4 — chameau du papier + robot masqué U²-Net), coût du fond non extrait (A/B masqué/brut), contraste sémantique vs signal (Canny) | Vinker et al., SIGGRAPH 2022 ([arXiv:2202.05822](https://arxiv.org/abs/2202.05822)) | | 1 | [05-1-DiscoDiffusion-CLIP-Guided-Diffusion](05-1-DiscoDiffusion-CLIP-Guided-Diffusion.ipynb) | La CLIP-guided diffusion pré-Stable-Diffusion : UNet KL-openai 512 pixel-space + CLIP ViT-L/14 comme fonction de perte (cutouts, distance sphérique), conditionnement de Song et al., grille `clip_gs` × `sat_scale`, même prompt contre Z-Image (ce que l'espace latent a changé) | Crowson 2021 ; Dhariwal & Nichol 2021 ([arXiv:2105.05233](https://arxiv.org/abs/2105.05233)) ; Radford et al. 2021 ([arXiv:2103.00020](https://arxiv.org/abs/2103.00020)) | @@ -35,4 +36,5 @@ Notebooks rétrospectifs : les outils d'avant Stable Diffusion (2021-2022) qui o ## Prérequis - Environnement Python du cours (torch CUDA) ; +- 05-0d : la base de portraits Olivetti se télécharge au premier appel de `sklearn.datasets.fetch_olivetti_faces` ; le notebook tourne aussi sur CPU, plus lentement ; - Outils locaux hors repo (voir la cellule d'installation du notebook) : clone du [code officiel CLIPasso](https://github.com/yael-vinker/CLIPasso) (MIT) + compilation MSVC de [diffvg](https://github.com/BachiLi/diffvg) — les adaptations d'exécution sont documentées dans le notebook.