Manim&Napari

Manim_Star_in_Napari.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from manim import *\n",
    "\n",
    "paramp   = \"-v WARNING  -qh --format=png -r 1000,1000 NapariExample \"\n",
    "#paramp   = \"-v WARNING  -qh  -r 1000,1000 NapariExample \""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%manim $paramp \n",
    "\n",
    "class NapariExample(Scene):\n",
    "    def construct(self):\n",
    "        self.camera.background_color = WHITE\n",
    "        star = Star(color=BLACK)\n",
    "        star.set_opacity(1)\n",
    "        star.scale_to_fit_height(0.00000001)\n",
    "        self.add(star)\n",
    "        self.play(star.animate.scale_to_fit_height(4), rate_func=linear)\n",
    "        self.play(star.animate.scale_to_fit_height(0.00000001), rate_func=linear)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0, 255], dtype=uint8)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from pathlib import Path\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import napari\n",
    "\n",
    "root = Path.cwd() / \"media\"\n",
    "all_imgs = []\n",
    "for path in sorted(root.rglob(\"*.png\")):\n",
    "    if \"NapariExample\" in path.name:\n",
    "        with Image.open(path) as img:\n",
    "            my_img = np.array(img.convert('L'))\n",
    "            my_img  = my_img > 128\n",
    "            all_imgs.append(~my_img)\n",
    "all_imgs = np.array(all_imgs, dtype= \"uint8\")*255\n",
    "np.unique(all_imgs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(120, 1000, 1000)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_imgs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import napari\n",
    "\n",
    "viewer = napari.Viewer(ndisplay=3)\n",
    "viewer.add_labels(all_imgs, scale=[1, 2, 2] , seed=0.03 , opacity=1)\n",
    "viewer.camera.angles = (-12, 24, 62)\n",
    "viewer.camera.zoom = 1"
   ]
  }
 ],
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