diff --git a/src/prerender.ipynb b/src/prerender.ipynb
new file mode 100644
index 0000000..15df3fc
--- /dev/null
+++ b/src/prerender.ipynb
@@ -0,0 +1,105 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/laurent_fainsin/Documents/unet/.venv/lib/python3.8/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
+      "/home/laurent_fainsin/Documents/unet/.venv/lib/python3.8/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: /home/laurent_fainsin/Documents/unet/.venv/lib/python3.8/site-packages/torchvision/image.so: undefined symbol: _ZNK3c1010TensorImpl36is_contiguous_nondefault_policy_implENS_12MemoryFormatE\n",
+      "  warn(f\"Failed to load image Python extension: {e}\")\n"
+     ]
+    }
+   ],
+   "source": [
+    "from PIL import Image\n",
+    "\n",
+    "import numpy as np\n",
+    "import albumentations as A\n",
+    "\n",
+    "from utils import RandomPaste\n",
+    "from data.dataset import SyntheticDataset\n",
+    "\n",
+    "from pathlib import Path\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "transform = A.Compose(\n",
+    "    [\n",
+    "        A.Resize(512, 512),\n",
+    "        A.Flip(),\n",
+    "        A.ColorJitter(),\n",
+    "        RandomPaste(5, \"/home/lilian/data_disk/lfainsin/spheres/\"),\n",
+    "        A.GaussianBlur(),\n",
+    "        A.ISONoise(),\n",
+    "    ],\n",
+    ")\n",
+    "\n",
+    "dataset = SyntheticDataset(image_dir=\"/home/lilian/data_disk/lfainsin/train/\", transform=transform)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "10001\r"
+     ]
+    }
+   ],
+   "source": [
+    "for i, (image, mask) in enumerate(dataset):\n",
+    "    path = f\"/home/lilian/data_disk/lfainsin/prerender/{i}/\"\n",
+    "    Path(path).mkdir(parents=True, exist_ok=True)\n",
+    "    Image.fromarray(image).save(f\"{path}/image.jpg\")\n",
+    "    Image.fromarray(mask*255).save(f\"{path}/MASK.PNG\")\n",
+    "    \n",
+    "    print(i, end=\"\\r\")\n",
+    "\n",
+    "    if i > 10000:\n",
+    "        break"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.8.0 ('.venv': poetry)",
+   "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": "3.8.0"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "dc80d2c03865715c8671359a6bf138f6c8ae4e26ae025f2543e0980b8db0ed7e"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}